Search Results (457)

To advance global climate governance, this study investigates the carbon emission efficiency (CEE) of 110 Chinese resource-based cities (RBCs) using a super-efficiency SBM-GML model combined with kernel density estimation and spatial analysis (2006–2022). Spatial Durbin model (SDM) and geographically and temporally weighted regression (GTWR) further elucidate the driving mechanisms. The results show that (1) RBCs achieved modest CEE growth (3.8% annual average), driven primarily by regenerative cities (4.8% growth). Regional disparities persisted due to decoupling between technological efficiency and technological progress, causing fluctuating growth rates; (2) CEE exhibited high-value clustering in the northeastern and eastern regions, contrasting with low-value continuity in the central and western areas. Regional convergence emerged through technology diffusion, narrowing spatial disparities; (3) energy intensity and government intervention directly hinder CEE improvement, while rigid industrial structures and expanded production cause negative spatial spillovers, increasing regional carbon lock-in risks. Conversely, trade openness and innovation level promote cross-regional emission reductions; (4) the influencing factors exhibit strong spatiotemporal heterogeneity, with varying magnitudes and directions across regions and development stages. The findings provide a spatial governance framework to facilitate improvements in CEE in RBCs, emphasizing industrial structure optimization, inter-regional technological alliances, and policy coordination to accelerate low-carbon transitions. Full article

Given the growing adverse effects of drought on water resources, agriculture, and various sectors, assessing and evaluating drought and producing high-quality drought maps despite the data scarcity to better understand its impacts and develop effective mitigation strategies is essential. Considering the existing gaps related to drought evaluation, especially in scarce data regions, this research aims to evaluate the efficiency of acceptable time period for drought studies (10–20 years), evaluate the performance of ERA5-LAND and IMERG-NASA precipitation data in estimating the Standardized Precipitation Index (SPI) using different statistical metrics and the innovative drought classification matrix (IDCM), and finally produce and compare high-quality and accurate drought characteristics maps resulted from in situ stations, ERA5-LAND, and IMERG-NASA. The Kocaeli province in Türkiye, which has limited data and is a scarce data region, has been selected as an application. The results ensure that an acceptable time period can be sufficient and provide reliable accuracy for assessing drought with RMSE ranging between 0.09 and 0.23 standard deviation and IDCM ranging between 85% and 97%. NASA IMERG data gave more accurate drought results than ERA5-LAND, and the Pearson correlation ranges between 0.57 and 0.89. Also, in situ data showed longer drought duration, while ERA5-LAND and NASA had higher intensity. This article enables policymakers and decision-makers to manage and plan water resources within the city boundary, ensuring sustainable agricultural, economic, and industrial activities and supporting effective climate change adaptation strategies. Full article

Tourism ecological efficiency (TEE) is a significant indicator of the development level of green and intensive tourism. However, conventional directional and radial TEE measurement approaches overlook critical factors such as intermediate process influences and input–output slack variables, potentially leading to biased estimates. Urban areas are key to coordinating tourism across provinces, so accurately assessing the TEE is vital for sustainable regional tourism. This study uses an improved TEE measurement model to measure the TEE of the Guangdong–Fujian–Zhejiang (GFZ) coastal city clusters from 2010 to 2021. The improved TEE measurement model is a three-stage super-efficiency SBM approach. It then uses standard deviation ellipses and geographic detectors to analyze the TEE’s spatiotemporal characteristics and influencing factors. The findings indicate the following: (1) The three-stage super-efficiency SBM approach improves the accuracy and validity of measurement results by removing external environmental variables. (2) During the study period, the TEE values of the GFZ coastal city clusters were above average (except for Meizhou, where the efficiency improved). Temporally, the TEE values of 75% of the cities showed an increasing trend; spatially, the high-value areas increased significantly, the middle- and low-value areas decreased, and the center of gravity shifted to the north and south. (3) The years 2016–2021 saw an increase in external development factors and the use of external resources. The study’s findings can serve as scientific benchmarks for TEE measurement, as well as the low-carbon and environmentally friendly growth of tourism in urban agglomerations. Full article

Motivated by China’s new urbanization and ecological civilization construction initiatives, the Shenyang Municipal Committee has recently has proposed an ambitious goal of advancing the construction of a Park City with northern characteristics. The scientifically planned urban landscape is essential for balancing ecological protection with sustainable development,. This plan is crucial for driving the realization of the Park City initiative. This study employed ArcGIS 10.8 and Fragstats 4.2 to systematically examine land use transitions and landscape pattern dynamics in Shenyang’s main urban area (2000–2020). The results indicated that Shenyang’s urban core has experienced significant southward expansion across the Hun River over the last two decades. This expansion resulted in a substantial increase in constructed land of 490.84 km² (from 15.78% to 29.19% in total coverage). Conversely, cultivated land, forest land, and grassland exhibited negative dynamic rates of −0.99%, −0.54%, and −1.02%, respectively, with 76.89% of cultivated land converted to construction land. Landscape pattern indices revealed intensified fragmentation: the number of patches rose by 163, while the largest patch area, landscape aggregation index, and contagion index decreased by 16.74%, 0.40%, and 5.84%, respectively. However, the landscape division index increased by 0.12%, with Shannon’s diversity index and evenness index increasing by 0.19 and 0.11, respectively. These metrics demonstrated the positive correlation between urbanization intensity and landscape pattern alterations. The examination of the dynamic land use patterns in Shenyang integrated seven crucial indicators to assess the development of the emerging Park City. Results indicated challenges including urban land expansion, cultivated land loss, limited resources, and uneven green space distribution. The findings revealed the negative correlation between land use pattern evolution and Park City requirements. The research suggested strategies at the macro-, meso-, and micro-scales to address these issues and reconcile urbanization pressures with sustainable Park City development in Shenyang. Full article

The synergistic advancement of “Digital China” and “Beautiful China” represents a pivotal national strategy for achieving high-quality economic development and a low-carbon transition. To illuminate the intrinsic mechanisms linking the digital economy (DE) to urban carbon emission performance (CEP), this study develops a novel two-sector theoretical framework. Leveraging panel data from 278 Chinese prefecture-level cities (2011–2023), we employ a comprehensive evaluation method to gauge DE development and utilize calibrated nighttime light data with downscaling inversion techniques to estimate city-level CEP. Our empirical analysis integrates static panel fixed effects, panel threshold, and moderating effects models. Key findings reveal that the digital economy demonstrably enhances urban carbon emission performance, although this positive effect exhibits a threshold characteristic linked to the maturity of digital infrastructure; beyond a specific developmental stage, the marginal benefits diminish. Crucially, this enhancement operates primarily through the twin engines of fostering technological innovation and driving industrial structure upgrading, with the former playing a dominant role. The impact of DE on CEP displays significant heterogeneity, proving stronger in northern cities, resource-dependent cities, and those characterized by higher levels of inclusive finance or lower fiscal expenditure intensities. Furthermore, the effectiveness of DE in reducing carbon emissions is dynamically moderated by policy environments: flexible economic growth targets amplify its carbon reduction efficacy, while environmental target constraints, particularly direct binding mandates, exert a more pronounced moderating influence. This research provides crucial theoretical insights and actionable policy pathways for harmonizing the “Dual Carbon” goals with the overarching Digital China strategy. Full article

The structural responsiveness of urban energy systems has emerged as a central challenge in the governance of shrinking cities. Urban shrinkage entails more than a redistribution of resources—it reflects deep tensions embedded in population spatial configuration, functional redundancy, and institutional inertia. To investigate the evolutionary trajectory and driving mechanisms of urban energy consumption (UEC) under the context of urban shrinkage, this study focuses on China, a country undergoing rapid internal regional transformation. Drawing on panel data from 281 cities between 2008 and 2021, the study integrates two-way fixed effects (TWFE) models, mediation analysis, and spatial econometric models to ensure the scientific rigor and robustness of the quantitative analysis. Contrary to the intuitive assumption that declining population leads to reduced energy loads, the results reveal a non-linear and asymmetric trajectory wherein per capita energy consumption increases alongside continued demographic decline. Mechanism decomposition further shows that declines in population density and the share of secondary industry suppress UEC through spatial dispersal and the retreat of energy-intensive sectors, respectively. In contrast, fiscal contraction and institutional path dependency collectively elevate the share of traditional energy consumption, reinforcing the structural inertia of UEC. This study illuminates the non-linear dynamics of energy system evolution under urban shrinkage and argues for a shift away from linear and target-driven governance paradigms toward governance frameworks that emphasize structural adaptation, distributive equity, and systemic resilience—thereby offering a theoretical and empirical foundation for multi-objective sustainable urban transitions. Full article

As an intensive eco-agricultural model, the rice–crayfish co-culture (RCC) system has been widely adopted in recent years due to its remarkable advantages in resource use, efficiency, and economic benefits. However, the long-term mechanisms by which this system affects the quantity and stability of soil aggregate, as well as the vertical distribution of soil organic carbon (SOC) within aggregate across soil profiles, remain unclear. This study investigated the effects of varying duration (4 and 8 years) of RCC in Qianjiang City, Hubei Province. Soil samples were collected from six depth layers (0–10 cm, 10–20 cm, 20–30 cm, 30–40 cm, 40–80 cm, and 80–120 cm) to analyze the distribution characteristics of soil aggregate and SOC. The results demonstrated that, compared to the field which used RCC for a duration of 4 years, the field which used RCC for a duration of 8 years significantly reduced bulk density (BD) by 16.3% in the 40–80 cm layer. However, prolonged flooding has led to a 9.6% increase in the BD of the plow pan layer (10–20 cm) due to hydrostatic pressure and mechanical disturbances. Furthermore, the use of RCC for a duration of 8 years significantly enhanced the mass fractions of water-stable aggregates > 2 mm in the 0–80 cm soil layer at 0–10 cm (25.9%), 10–20 cm (30.2%), 20–30 cm (141.8%), 30–40 cm (172.4%), and 40–80 cm (112.9%), and improved aggregate stability throughout the entire soil profile. In terms of SOC distribution, the SOC concentration increased significantly with prolonged RCC usage across all soil layers, particularly in the 0–20 cm layer. The SOC was primarily derived from >2 mm (Large aggregate). Notably, although < 0.053 mm (Silt and clay) constituted a small proportion of the 0–20 cm layer, their SOC concentration reached 15.3–20.55 g kg⁻¹. Overall, extended RCC duration reduced BD in nearly all soil layers, promoted the formation of macro-aggregate, enhanced aggregate stability, and increased the SOC concentration within macro-aggregate, while strengthening the SOC stocks capacity of the 80–120 cm soil layer from 2.58 kg C m⁻² to 4.35 kg C m⁻², an increase of 68.6%. Full article

The ongoing advancement of urbanization has significantly amplified its impacts on the water environment. Understanding the coupling relationships between urbanization and the water environment (UAWE) is crucial for Chinese policymakers aiming to promote sustainable urban development. In this study, a comprehensive UAWE evaluation model was developed to examine the development trajectories in Neijiang City from 2012 to 2022. Methodologically, a comprehensive evaluation approach was applied to assess urbanization and water resource trends over this period, followed by the development of a Coupling Coordination Degree Model (CCDM) to quantify their synergistic relationship. The results showed that the coupling between the comprehensive urbanization index and the water environment system evolved over time, as reflected in the following key findings: (1) Neijiang underwent three distinct stages from 2012 to 2022 in terms of coupling and coordination between urbanization and the water environment: Basic Coordination (2012–2015), Good Coordination (2016–2020), and Excellent Coordination (2020–2022). (2) Urbanization exerted varying impacts on subsystems of the water environment, with the pressure-response subsystems exhibiting marked volatility from 2012 to 2022. The impact intensity followed the order spatial urbanization > economic urbanization > social urbanization > population urbanization. These findings offer valuable theoretical and practical insights for aligning urban sustainability goals with effective water environment protection measures. This study provides essential guidance for policymakers in Neijiang and similar regions, enabling the development of tailored strategies for sustainable urbanization and enhanced water management. Full article

Understanding the spatio-temporal evolution of farmland carbon emissions, disentangling their underlying driving forces, and exploring the decoupling relationship between these emissions and economic development are pivotal to advancing low-carbon and high-quality agricultural development in Shandong Province, China. Using the Logarithmic Mean Divisia Index (LMDI) and Tapio decoupling model, this study conducted a comprehensive analysis of panel data from 16 cities in Shandong Province spanning 2004–2023. This research reveals that the total farmland carbon emissions in Shandong Province followed a trajectory of “initial fluctuating increase and subsequent steady decline” during the study period. The emissions peaked at 29.4 million tons in 2007 and then declined to 20.2 million tons in 2023, representing a 26.0% reduction compared to the 2004 level. Farmland carbon emission intensity in Shandong Province showed an overall downward trend over the period 2004–2023, with the 2023 intensity registering a 68.9% decline compared to 2004. The carbon emission intensity, agricultural structure, and labor effects acted as inhibiting factors on farmland carbon emissions in Shandong Province, while the economic development effect exerted a positive driving impact on the growth of such emissions. Over the 20-year period, these four factors cumulatively contributed to a reduction of 2.1 × 10⁵ tons in farmland carbon emissions. During 2004–2013, the farmland carbon emissions in Zaozhuang, Yantai, Jining, Linyi, Dezhou, Liaocheng, and Heze showed a weak decoupling state, while in 2014–2023, the farmland carbon emissions and economic development in all cities of Shandong Province showed a strong decoupling state. In the future, it is feasible to reduce farmland carbon emissions in Shandong Province by improving agricultural resource utilization efficiency through technological progress, adopting advanced low-carbon technologies, and promoting the transformation of agricultural industrial structures towards “high-value and low-carbon” designs. Full article

Flood control infrastructure is essential for the development of cities and the population’s well-being. The goal is to protect human and economic resources by reducing the inundation area and controlling the flood level and peak discharges. Detention basins can do this by storing a large volume of water to be released after the peak discharge. By doing this, a large amount of energy is stored, which can be recovered via micro-hydropower. In addition, as the release flow is controlled and almost constant, Pumps as Turbines (PAT) could be a feasible and economic option in these cases. Thus, this study investigates the feasibility of micro-hydropower (MHP) in urban detention basins, using the Santa Lúcia detention basin in Belo Horizonte as a case study. The methodology involved hydrological modeling, hydraulic analysis, and economic and environmental assessment. The results demonstrated that PAT selection has a crucial role in the feasibility of the MHP, and exploiting rainfall with lower intensities but higher frequencies is more attractive. Using multiple PATs with different operating points also showed promising results in improving energy production. In addition to the economic benefits, the MHP in the detention basin produces minimal environmental impact and, as it exploits a wasted energy source, it also reduces the carbon footprint in the urban water cycle. Full article

Climate change, resource scarcity, and ecological degradation have become critical bottlenecks constraining socio-economic development. Basin cities serve as key nodes in China’s ecological security pattern, playing indispensable roles in ecological civilization construction. This study established an evaluation index system spanning five dimensions to assess the effectiveness of ecological civilization construction. This study employs the entropy-weighted Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) and Back-Propagation (BP) neural network methods to evaluate the level of ecological civilization construction in the Yellow River Basin from 2010 to 2022, to analyze its indicator weights, and to explore the spatio-temporal evolution characteristics of each city. The results demonstrate the following: (1) Although the ecological civilization construction level of cities in the Yellow River Basin shows a steady improvement, significant regional development disparities persist. (2) The upper reaches are primarily constrained by ecological fragility and economic underdevelopment. The middle reaches exhibit significant internal divergence, with provincial capitals leading yet demonstrating limited spillover effects on neighboring areas. The lower reaches face intense anthropogenic pressures, necessitating greater economic–ecological coordination. (3) Among the dimensions considered, Territorial Space and Eco-environmental Protection emerged as the two most influential dimensions contributing to performance differences. According to the ecological civilization construction performance and changing characteristics of the 48 cities, this study proposes differentiated optimization measures and coordinated development pathways to advance the implementation of the national strategy for ecological protection and high-quality development in the Yellow River Basin. Full article

In response to the escalating global energy demands, the optimization of energy efficiency has emerged as a linchpin for sustainable development. This study considers the potential of energy conservation and emission reduction in one of the most economically vibrant and resource-intensive regions in China, the Yangtze River Economic Belt, encompassing 11 provinces and cities. The SBM-Undesirable model is used to measure the energy efficiency and analyze the temporal-spatial distribution. Moran’s I is employed to analyze the overall spatial pattern and local regional differences in energy efficiency. The systematic analysis shows that the temporal fluctuation exists in the development of energy efficiency, and the average of the Yangtze River Economic Belt exhibits a development pattern of “downstream > midstream > upstream” from the spatial perspective. The upstream region would require way more effort than others to decarbonize and improve efficiency. At the municipal level, the overall energy efficiency of 11 provinces and cities fails to reach an efficient state, and potential for improvement exists. Moreover, the potential model of energy conservation and emission reduction is constructed. We further explore the pathways of energy efficiency improvement for each region in the Yangtze River Economic Belt, including pathways of “High-Efficiency Type”, “High Emission Reduction Potential”, and “Extensive Development Type”. Full article

Smart cities use advanced infrastructure and technology to improve the quality of life for their citizens. Collaborative services in smart cities are making the smart city ecosystem more reliable. These services are required to enhance the operation of interoperable systems, such as smart transportation services that share their data with smart safety services to execute emergency response, surveillance, and criminal prevention measures. However, an important issue in this ecosystem is data security, which involves the protection of sensitive data exchange during the interoperability of heterogeneous smart services. Researchers have addressed these issues through blockchain integration and the implementation of smart contracts, where collaborative applications can enhance both the efficiency and security of the smart city ecosystem. Despite these facts, complexity is an issue in smart contracts since complex coding associated with their deployment might influence the performance and scalability of collaborative applications in interconnected systems. These challenges underscore the need to optimize smart contract code to ensure efficient and scalable solutions in the smart city ecosystem. In this article, we propose a new framework that integrates generative AI with blockchain in order to eliminate the limitations of smart contracts. We make use of models such as GPT-2, GPT-3, and GPT4, which natively can write and optimize code in an efficient manner and support multiple programming languages, including Python 3.12.x and Solidity. To validate our proposed framework, we integrate these models with already existing frameworks for collaborative smart services to optimize smart contract code, reducing resource-intensive processes while maintaining security and efficiency. Our findings demonstrate that GPT-4-based optimized smart contracts outperform other optimized and non-optimized approaches. This integration reduces smart contract execution overhead, enhances security, and improves scalability, paving the way for a more robust and efficient smart contract ecosystem in smart city applications. Full article

This study investigates the complex dynamics of new-type urbanization in resource-based county-level cities, using Wuan City in Hebei Province, China, as a representative case. As China pursues a high-quality development agenda, cities historically dependent on resource extraction face profound challenges in achieving sustainable and inclusive urban growth. This research employs a multi-method approach—including Theil index analysis, industrial shift-share analysis, a Cobb–Douglas production function model, and a composite urbanization index—to quantitatively diagnose the constraints on Wuan’s development and assess its transformation efforts. Our empirical results reveal a multifaceted situation: while the urban–rural income gap has narrowed, rural income streams remain fragile. The shift-share analysis indicates that although Wuan’s traditional industries have regained competitiveness, the city’s economic structure is still burdened by a persistent negative structural component, hindering diversification. Furthermore, the economy exhibits characteristics of a labor-intensive growth model with inefficient capital deployment. These underlying issues are reflected in a comprehensive urbanization index that, after a period of rapid growth, has recently stagnated, signaling the exhaustion of the city’s traditional development mode. In response, Wuan attempts an “industrial transformation-driven new-type urbanization” path. This study details the three core strategies being implemented: (1) incremental population urbanization through development at the urban fringe and in industrial zones; (2) in situ urbanization of the existing rural population; and (3) the cultivation of specialized “characteristic small towns” to create new, diversified economic nodes. The findings from Wuan offer critical, actionable lessons for other resource-dependent regions. The case demonstrates that successful urban transformation requires not only industrial upgrading but also integrated, spatially aware planning and robust institutional support. We conclude that while Wuan’s model provides a valuable reference, its strategies must be adapted to local contexts, emphasizing the universal importance of institutional innovation, human capital investment, and a people-centered approach to achieving resilient and high-quality urbanization. Full article

Under the impetus of the global urbanization, the synergistic relationship between smart city policies and green innovation capabilities has emerged as a critical agenda for achieving sustainable development goals. While existing studies have explored the techno-economic effects of smart cities, systematic evidence remains scarce regarding their pathways and heterogeneous impacts on green growth. This study investigates the influence of smart city pilot policies on urban green growth trajectories and their heterogeneous characteristics. Leveraging panel data from 293 Chinese prefecture-level cities, we employ a multi-period difference-in-differences (DID) model with two-way fixed effects to control for unobserved city-specific and time-specific factors, complemented by robustness checks including parallel trend tests, placebo tests, and alternative dependent variable specifications. Data sources encompass the China City Statistical Yearbook, CNRDS, and CSMAR databases, covering core metrics such as green patent applications and grants, industrial upgrading indices, and environmental regulation intensity, with missing values being addressed via mean imputation. The findings demonstrate that smart city pilot policies significantly enhance green innovation levels in treated cities, with effects exhibiting pronounced spatial and resource-based heterogeneity; there are notably stronger impacts in non-resource-dependent cities and eastern regions. Mechanism analysis shows that policies are driven by a dual effect of industrial upgrading and environmental regulation. The former is manifested by the high substitution elasticity of the digital economy for traditional manufacturing, while the latter is reflected in the rising compliance costs of polluting enterprises. This research advances a cross-nationally comparable theoretical framework for understanding green transition mechanisms in smart city development while providing empirical benchmarks for policy design in emerging economies. Full article