Search Results (1,137)

Achieving carbon reduction is essential in advancing China’s dual carbon goals and promoting a green transformation in the transportation sector. Changes in energy structure and intensity constitute key drivers for sustainable and low-carbon development in this field. To explore the spatial spillover effects of the energy structure and intensity on the green transition of transportation, this study constructs a panel dataset of 30 Chinese provinces from 2007 to 2020. It employs a super-efficiency SBM model, non-parametric kernel density estimation, and a spatial Markov chain to verify and quantify the spatial spillover effects of green total factor productivity (GTFP) in the transportation sector. A dynamic spatial Durbin model is then used for empirical estimation. The main findings are as follows: (1) GTFP in China’s transportation sector exhibits a distinct spatial pattern of “high in the east, low in the west”, with an evident path dependence and structural divergence in its evolution; (2) GTFP displays spatial clustering characteristics, with “high–high” and “low–low” agglomeration patterns, and the spatial Markov chain confirms that the GTFP levels of neighboring regions significantly influence local transitions; (3) the optimization of the energy structure significantly promotes both local and neighboring GTFP in the short term, although the effect weakens over the long term; (4) a reduction in energy intensity also exerts a significant positive effect on GTFP, but with clear regional heterogeneity: the effects are more pronounced in the eastern and central regions, whereas the western and northeastern regions face risks of negative spillovers. Drawing on the empirical findings, several policy recommendations are proposed, including implementing regionally differentiated strategies for energy structure adjustment, enhancing transportation’s energy efficiency, strengthening cross-regional policy coordination, and establishing green development incentive mechanisms, with the aim of supporting the green and low-carbon transformation of the transportation sector both theoretically and practically. 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

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

With the advancement of global climate governance, public attention—an emerging form of social capital—has played an increasingly important role in the carbon emission effects of green technological innovation. Based on panel data from 267 prefecture-level cities in China from 2012 to 2022, this study employed a two-way fixed-effects model to identify the nonlinear relationship between green innovation and carbon emissions, incorporated interaction terms to examine the moderating effect of public attention, and applied a spatial Durbin model to analyze the spatial spillover effects of green innovation. The results reveal an inverted U-shaped relationship between green innovation and carbon emissions, with the inflection point corresponding to 8.58 authorized green patents per 10,000 people—a threshold that most cities have yet to reach. Public attention significantly altered the shape of the carbon effect curve by making it steeper; in cities with a higher share of secondary industry, it delayed the inflection point, whereas in cities dominated by the tertiary industry, the turning point appeared earlier. In addition, green innovation had significant spatial spillover effects, and its impact on carbon emissions in neighboring cities displayed a U-shaped pattern. This paper proposes an analytical framework of “socially empowered innovation” to reveal the nonlinear moderating mechanism through which public attention influences the carbon effects of green innovation. The findings offer important policy implications: efforts should focus on long-term innovation, promote regional coordination, guide rational public participation, and avoid short-sighted and unsustainable mitigation practices. Full article

This study develops an integrated analytical framework to examine the interplay of urbanization, energy consumption, and CO₂ emissions at the city level in China. Utilizing the Entropy-TOPSIS method for multidimensional urbanization measurement, the GM_Combo model for spatial spillover analysis, and Random Forest for identifying emission drivers, we analyze data from 282 Chinese cities from 2006 to 2020. Results reveal significant hierarchical differences in urbanization, with K-means clustering identifying high, medium, and low urbanization groups reflecting diverse regional development pathways. Energy consumption increasingly drives emissions, while urbanization’s influence declines, indicating partial decoupling. Strong spatial spillovers highlight the need for regional coordination. Ecological assets provide moderate mitigation effects. These findings contribute to the literature by introducing a multidimensional urbanization index, uncovering nonlinear energy–emissions dynamics, and quantifying intercity spillovers, offering empirical support for tailored low-carbon policies and sustainable urban governance. Full article

Global water scarcity has emerged as a critical barrier to sustainable socio-economic development, stimulating water rights trading to serve as a policy instrument designed to enhance water use efficiency. This study systematically evaluates the impact of water rights trading (WRT) on agricultural water use efficiency (AWE) using panel data from 30 provinces (2011–2022) and a difference-in-difference (DID) model, while thoroughly investigating the underlying mechanisms and spatial spillover effects. The following are primary conclusions: (1) WRT significantly improves efficiency, reducing water consumption per unit of agricultural output by 4.5% in pilot regions, with robustness checks confirming reliability; (2) the policy’s effects on agricultural water use efficiency vary across regions; (3) mechanism analysis suggests that efficiency improvements are primarily driven by optimized crop planting patterns, adoption of water-saving irrigation technologies, advancements in agricultural mechanization, and strengthened environmental regulations; and (4) the policy exhibits notable spatial spillover effects. These findings contribute to the evaluation of WRT policy and offer practical insights for market-based water allocation reforms, suggesting further expansion of WRT with an emphasis on regional coordination and cross-regional cooperation mechanisms. Full article

The digital economy is a vital driver of industrial transformation and green development in China. This study aims to investigate how formal and informal environmental regulations affected the growth of the digital economy across Chinese prefecture-level cities between 2010 and 2020. Utilizing panel data from official statistical yearbooks and local bulletins, the research employs entropy weighting and ratio analysis to measure regulatory intensity and effectiveness. Spatial econometric models are applied to assess the direct and spillover effects of environmental regulation on digital economy development. Results indicate a nationwide strengthening of both formal and informal regulations, with formal mechanisms exerting a more pronounced influence on digital growth. Regional disparities are evident, with cities under stricter environmental oversight showing faster digital advancement. Spatial spillover effects exist but diminish with distance, likely due to institutional fragmentation. These findings underscore the need for integrated multi-level regulatory approaches, promoting synergy between formal and informal regulations and embedding environmental goals within land-use planning and digital infrastructure investment. The study offers new insights into the interplay between environmental governance and urban digital transformation, providing lessons relevant to China and other developing countries pursuing sustainable transitions. Full article

This study builds an evaluation index system for the modernization of harmonious coexistence between man and nature from 2014 to 2024, including three criteria for ecological environmental protection, green economic transformation, and enhancement of people’s livelihood, to help Nanping City’s sustainable development and build a “Pilot Demonstration Zone for the Modernization of Harmonious Coexistence between Humans and Nature”. Despite the 2020 coronavirus pandemic, the study area’s modern development of harmonious coexistence between humans and nature increased from 2014 to 2024, narrowing the development gap between counties. The coupling coordination degree of the criterion layer is “high in the middle, low in the east and west, high in the south and low in the north”. Under the spatial spillover effect, counties with higher development stages radiate driving force on surrounding counties with lower development stages. In 2014, 2019, and 2024, resource agglomeration, social civilization progress, economic development, and government policy regulation drove harmonious coexistence between humans and nature in Nanping City. Full article

Improving agricultural eco-efficiency (AEE) plays a critical role in fulfilling agriculture sustainable development goals (SDGs). China’s agriculture-led Rural Industrial Integration (RII) seeks to synergize rural industrialization with agricultural sustainability, yet its impact on AEE remains underexplored. Using a 2008–2022 panel of 285 prefecture-level cities in China, this study uses a series of econometric methods to empirically verify the impact of RII on AEE. The coefficient of RII under the fixed effect model is 0.366, indicating that it has a significant positive impact on AEE, which remains valid after robustness tests such as the instrumental variable method and the use of the “Rural Industrial Integration Development Demonstration County” pilot as a quasi-natural experiment. Mechanism tests show that rural labor transfer, agricultural technology innovation, and agricultural carbon emissions play an important role in mediating the impact of RII on AEE. RII has a negative spatial spillover effect on AEE, with a coefficient of −2.280. In addition, the impact of RII on AEE also varies under the heterogeneity of regions and development models. This study provides new evidence that China’s RII practices can promote sustainable agricultural development, deepens theoretical understanding of the impact of RII on AEE, and provides a reference for future policy implementation. Full article

Intelligent manufacturing is the inevitable path for China to achieve its strategy of becoming a manufacturing power. Exploring how intelligent manufacturing policies can promote green innovation, which refers to promoting innovative technologies aimed at improving resource utilization efficiency, is of great significance for promoting the green transformation of enterprises. Based on the data of A-share listed enterprises from 2010 to 2023, this study regards the intelligent manufacturing demonstration project pilot as a quasi-natural experiment and explores its policy spillover effects and mechanism. The research findings indicate that the intelligent manufacturing policy can greatly improve firms’ green innovation, and non-state-owned and non-high-pollution enterprises are more sensitive to intelligent manufacturing policies. It has a significant spatial spillover effect in both the district and industry dimensions. In addition, the mechanism analysis indicates that alleviating enterprises’ financing constraints and environmental uncertainty are important ways to promote enterprises’ green innovation. This study empirically designs to fill the theoretical gap in the association between intelligent manufacturing policies and green innovation in the body of knowledge, and innovatively verifies the spatial spillover effect of intelligent manufacturing policies from both the district and industry dimensions. At the practical level, its conclusion provides an operational decision-making toolbox for multiple entities such as the government, enterprises, and financial institutions to jointly promote green transformation. Full article

The development of New Quality Productive Forces (NQPF), fueled by simultaneous progress of informatization, digitalization, and ecologization, creates a transformative sustainability framework that connects economic growth and environmental protection. People usually think that environmental regulation enhances regional ecologization, thereby boosting total NQPF. Does this hold true for China’s Yangtze River Basin? Utilizing panel data from 2015 to 2022, this study examines the impact of environmental regulation on NQPF across 86 prefecture-level cities in the basin. Our empirical results corroborate that environmental regulation exerts a statistically significant positive effect on digital NQPF development, which in turn contributes substantially to overall NQPF enhancement—This finding remains robust across alternative estimation methods. Our analysis further identifies three primary mechanisms driving this effect: industrial upgrading, technological innovation, and GDP growth. The effect is nonlinear and characterized by a threshold: in less developed areas, environmental regulation somewhat helps, whereas in more developed regions, reaching a certain strength significantly enhances both digital and overall productivity. Furthermore, environmental regulation demonstrates notable spillover effects: they enhance local outcomes while simultaneously improving digital and overall NQPF in neighboring regions. These findings offer strong evidence and valuable policy insights for advancing the digital transformation and high-quality sustainable development of the Yangtze River Basin. Full article

In recent years, the rapid progress of artificial intelligence (AI) technologies has significantly influenced urban green energy efficiency. Leveraging panel data from 271 cities in China spanning the period of 2010–2022, this paper conducts an empirical analysis of the impact of AI on urban green energy efficiency from multiple perspectives, including green finance, industrial chain resilience, and the intensity of environmental regulation. The key findings are as follows: ① AI has a substantial positive effect on urban green energy efficiency, a conclusion that is consistently confirmed through multiple robustness tests; ② Heterogeneity analysis shows that the influence of AI varies markedly across different regions, city sizes, and whether cities are central, coastal, or transportation hubs, yet it maintains an overall positive correlation. However, its impact is relatively weaker in the northeastern region and in megacities; ③ Mechanism tests reveal that AI enhances urban green energy efficiency by improving green finance, strengthening industrial chain resilience, and intensifying environmental regulation; ④ Spatial spillover analysis indicates that AI exerts a positive spatial spillover effect on local urban green energy efficiency. Based on these findings, this paper offers targeted policy recommendations to enhance urban green energy efficiency and advance sustainable development. Full article

Seeking to advance mutual clustering of the tourism economy and cultural industries while safeguarding cultural sustainability in tourism, this paper delves into the patterns of co-development and the contributing forces across spatial and temporal dimensions in the Yellow River Basin. Using a combined spatial and temporal analytical lens, along with spatial autocorrelation testing and a spatial Durbin model embedded in a synergetic systems approach, the present study analyzes the evolutionary characteristics of the spatiotemporal pattern of the collaborative agglomeration of the Yellow River Basin’s tourism and cultural industries in 2011 and 2021 and the internal mechanism of its influencing factors. We then propose countermeasures and suggestions to boost the quality–efficiency synergy agglomeration of the basin’s tourism and cultural industries. The results showed the following: ① From 2011 to 2021, a positive overall spatial autocorrelation was noted in the basin’s tourism and cultural industries. Temporally, it presented a variation trend of “rise–fall–rise”, and spatially, it presented a distribution characteristic of “higher in the central and eastern regions versus in its western parts”. ② From 2011 to 2021, the local spatial autocorrelation (LSA) of the basin’s tourism and cultural industries remained at a low level. Moreover, significant differences were noted in the LSA among different regions. In spatial terms, the clustering intensity of tourism and cultural industries was stronger in the central and eastern parts of the basin versus in its western parts. ③ Influencing variables for tourism–culture collaborative agglomeration across the basin involve both temporal superposition effects and spatial radiation driving effects. The industrial economy, policies, and innovation exert enduring effects on the development and cross-regional spillover outcomes of the two collaborative agglomerations. Serving as a theoretical reference and policy resource, this study addresses how to promote the quality–efficiency synergy in the Yellow River Basin’s tourism and cultural industries while enhancing cultural sustainability in the tourism industry. Moreover, it can also provide experiences and references for other similar regions. Full article

Physical activity plays a vital role in promoting public health. Among its various forms, outdoor exercise offers combined physical and mental health benefits. However, the spatial patterns and underlying drivers of outdoor exercise remain underexplored in rapidly urbanizing areas. Based on 15,880 app-tracked trajectories from 723 individuals, this study investigates running, walking, and cycling patterns across 130 communities in Southern Dongguan. Results reveal three key findings. First, different types of outdoor exercise show distinct spatial patterns: running is common in urban centers, walking is concentrated around natural landscapes, and cycling follows cross-regional networks. Second, natural and built environmental features shape outdoor exercise behavior. Waterfront continuity promotes participation, while residential areas support walking. In contrast, manufacturing zones inhibit participation due to environmental degradation. Socioeconomic factors also influence participation by enhancing the grassroots governance capacity. Third, spatial spillover effects significantly shape cycling patterns, and traditional models that ignore spatial dependence underestimate environmental impacts. These findings provide new insights into how the combined influence of artificial and natural environments shapes outdoor exercise in rapidly urbanizing cities. They also reveal the distinctive role of grassroots governance with state support in China, offering valuable lessons for other fast-growing urban regions worldwide. Full article

Land is a critical factor of production that contributes significantly to economic growth. However, conventional land use pattern in China has resulted in serious environmental pollution. Now enhancing green land use efficiency (GLUE) has emerged as an effective strategy for improving environmental quality. The development of the digital economy (DE), characterized by low cost and high efficiency, has demonstrated considerable potential in reducing environmental pollutants and enhancing resource allocation. This study employs an extensive analytical framework to analyze the impact of DE development on GLUE across 267 cities in China from 2011 to 2019. The results show that DE exerts a significant effect on improving GLUE, which remains valid after the execution of endogeneity and robustness tests. The research on mechanisms indicates that this promotional effect is primarily achieved through the innovation in green technology and the optimization of industrial structure. Extended empirical tests indicate there is a nonlinear trend, wherein the positive effect increasingly intensifies after green industry innovation and industrial structure optimization exceeds threshold values. There is also a significant short term spillover effect of DE on GLUE, supplemented by long term effects. These findings substantially improve our comprehension of the connection of DE and land use, while providing practical policy recommendations for promoting environmentally sustainable development and land green utilization. Full article