Search Results (942)

In river-connected lake regions, both land use and hydrological regime changes may affect the ecosystem services; however, few studies have attempted to elucidate their complex influences. In this study, the spatiotemporal dynamics of eight ecosystem services (crop production, aquatic production, water yield, soil retention, flood regulation, water purification, net primary productivity, and habitat quality) were investigated through remote-sensing images and the InVEST model in the Dongting Lake Region during 2000–2020. Results revealed that crop and aquatic production increased significantly from 2000 to 2020, particularly in the northwestern and central regions, while soil retention and net primary productivity also improved. However, flood regulation, water purification, and habitat quality decreased, with the fastest decline in habitat quality occurring at the periphery of the Dongting Lake. Land-use types accounted for 63.3%, 53.8%, and 40.3% of spatial heterogeneity in habitat quality, flood regulation, and water purification, respectively. Land-use changes, particularly the expansion of construction land and the conversion of water bodies to cropland, led to a sharp decline in soil retention, flood regulation, water purification, net primary productivity, and habitat quality. In addition, crop production and aquatic production were higher in cultivated land and residential land, while the accompanying degradation of flood regulation, water purification, and habitat quality formed a “production-pollution-degradation” spatial coupling pattern. Furthermore, hydrological fluctuations further complicated these dynamics; wet years amplified agricultural outputs but intensified ecological degradation through spatial spillover effects. These findings underscore the need for integrated land-use and hydrological management strategies that balance human livelihoods with ecosystem resilience. Full article

This study examines whether regional infrastructure can predict economic resilience in European regions, focusing on resistance, recovery, and reorientation during the COVID-19 crisis. While infrastructure is widely recognized as a key factor influencing regional resilience, its explicit role has been underexplored in the European context. Using a comprehensive literature review and spatial econometric models applied to NUTS-2 level data from 2017 to 2024, we investigate the direct and spatial spillover effects of various infrastructure types—transportation, healthcare, tourism, education, and digital access—on regional resilience outcomes. We apply OLS and four spatial models (SEM, SLX, SDEM, SDM) under 29 spatial weighting matrices to account for spatial autocorrelation. Results show that motorway density, early school leaving, and healthcare infrastructure in neighbouring regions significantly affect resistance. For recovery, railway density and GDP per capita emerge as key predictors, with notable spatial spillovers. Reorientation is shaped by population structure, railway density, and tourism infrastructure, with both positive and negative spatial dynamics observed. The findings underscore the importance of infrastructure not only in isolation but also within regional systems, revealing complex interdependencies. We conclude that policymakers must consider spatial externalities and coordinate infrastructure investments to enhance regional economic resilience across interconnected Europe. Full article

China’s economy is shifting from an era of rapid expansion to one focused on high-quality development, making it imperative to tackle environmental degradation linked to energy use. Understanding how New Quality Productive Forces (NQPF) interact with energy efficiency, along with the mechanisms driving this relationship, is essential for economic transformation and long-term sustainability. This study establishes an evaluation framework for NQPF, integrating technological, green, and digital dimensions. We apply fixed-effects models, the spatial Durbin model (SDM), a moderation model, and a threshold model to analyze the influence of NQPF on Green Total Factor Energy Efficiency (GTFEE) and its spatial implications. This underscores the necessity of distinguishing it from traditional productivity frameworks and adopting a new analytical perspective. Furthermore, by considering dimensions such as input, application, innovation capability, and market efficiency, we reveal the moderating role and heterogeneous effects of artificial intelligence (AI). The findings are as follows: The development of NQPF significantly enhances GTFEE, and the conclusion remains robust after tail reduction and endogeneity tests. NQPF has a positive spatial spillover effect on GTFEE; that is, while improving the local GTFEE, it also improves neighboring regions GTFEE. The advancement of AI significantly strengthens the positive impact of NQPF on GTFEE. AI exhibits a significant U-shaped threshold effect: as AI levels increase, its moderating effect transitions from suppression to facilitation, with marginal benefits gradually increasing over time. Full article

Achieving synergies between government-led and market-based policy instruments is critical to advancing Energy–Environmental Productivity and Sustainable Urban Development. This study investigates the effects of China’s dual-pilot energy policies (New Energy Demonstration Cities (NEDCs) and Energy Consumption Permit Trading (ECPT)) on urban environmental productivity (UEP) across 279 prefecture-level cities from 2006 to 2023. Utilizing a Non-Radial Directional Distance Function (NDDF) approach, combined with Difference-in-Differences (DID) estimation and spatial econometric models, the analysis reveals that these synergistic policies significantly enhance both comprehensive and net measures of UEP. Mechanism analysis highlights the roles of industrial restructuring, technological innovation, and energy transition in driving these improvements, while heterogeneity analysis indicates varying effects across different city types. Spatial spillover analysis further demonstrates that policy impacts extend beyond targeted cities, contributing to broader regional gains in UEP. These findings offer important insights for the design of integrated energy and environmental policies and support progress toward key Sustainable Development Goals (SDG 7, SDG 11, and SDG 12). Full article

Promoting the sustainable development of virtual water trade is of great significance to safeguarding China’s water resource security and balanced regional economic growth. This study analyzes the virtual water trade network among 31 Chinese provinces based on multi-regional input–output tables from 2012, 2015, and 2017, using total trade decomposition, social network analysis, and exponential random graph models. The key findings are as follows: (1) The total virtual water trade volume remains stable, with Xinjiang, Jiangsu, and Guangdong as the core regions, while remote areas such as Shaanxi and Gansu have lower trade volumes. The primary industry dominates, and it is driven by simple value chains. (2) Provinces such as Xinjiang, Heilongjiang, and Jiangsu form the network’s core. Network density and symmetry increased from 2012 to 2015 but declined slightly in 2017, with efficiency peaking and then dropping, and the clustering coefficient decreased annually. Four economic sectors exhibit distinct interactions: frequent two-way flows in Sector 1, significant inflows in Sector 2, prominent net spillovers in Sector 3, and key brokers in Sector 4. (3) The network evolved from a core-periphery structure with weak ties to a stable, heterogeneous, and resilient system. (4) Influencing factors, such asper capita water resources, economic development, and population, significantly impact trade. Similarities in economic levels, population, and water endowments promote trade, while spatial distance has a limited effect, with geographic proximity showing a significant negative impact on long-distance trade. Full article

As the climate problem is getting more and more serious and the “low-carbon revolution” of globalization is emerging, the logistics industry, as a high-end service industry, must also take the road of low-carbon development. Improving logistics carbon emission efficiency (LCEE) is gradually becoming an inevitable choice to maintain sustainable social development. The study uses the Super-SBM (Super-Slack-Based Measure) model to evaluate the urban LCEE from 2013 to 2022, explores the contribution of efficiency changes and technological progress to LCEE through the decomposition of the GML (Global Malmquist–Luenberger) index, and reveals the influence of digital transformation and energy consumption structure on LCEE by using the Spatial Durbin Model, concluding as follows: (1) LCEE declines from east to west, with large regional differences. (2) LCEE has steadily increased over the past decade, with slower growth from east to west. It fell in 2020 due to COVID-19 but has since recovered. (3) LCEE shows a catching-up effect among the three major regions, with technological progress being a key driver of improvement. (4) LCEE has significant spatial dependence. Energy consumption structure has a short-term negative spillover effect, while digital transformation has a positive spillover effect. Full article

As an important direction in industrial evolution, the synergistic agglomeration of manufacturing and productive service industries has become a key path to promote the green transformation of the economy. Based on China’s provincial panel data, this study utilizes a variety of econometric methods to explore in depth the mechanisms, spatial effects and regional differences in the impact of the synergistic agglomeration of manufacturing and productive service industries on the green, low-carbon and recycling development of the economy. The empirical results show that the synergistic agglomeration of manufacturing and productive services not only directly promotes the green, low-carbon and recycling development of the economy, but also generates an indirect impact through the intermediary channel and exhibits significant spillover characteristics in the spatial dimension. This conclusion holds firm after a series of robustness tests. In addition, environmental regulations and the level of regional industrialization play a moderating role on the impact of industrial synergistic agglomeration and green, low-carbon and recycling development of the economy, and the effect of the role varies across regions and levels of economic development. This paper provides a decision-making reference for further optimizing the regional layout of China’s industries and enhancing the green, low-carbon and recycling development of the economy in each province. Full article

The accelerating growth of the digital economy (DE) offers fresh momentum towards reaching carbon emissions’ peak and neutrality. Nevertheless, the impact mechanism of the DE on carbon emissions intensity (CEI) is insufficiently characterized. Our study first constructs an expanded comprehensive indicator system to evaluate DE development level from five dimensions containing 17 indicators. Panel data from 30 Chinese provincial regions (2013–2023) were analyzed using fixed effects, mediating effects, and spatial Durbin models to empirically examine the relationship and mechanisms between DE and CEI. Considering the existence of indirect effects of DE on CEs, the mechanism associated with the effect of the DE on CEs from the perspectives of economic growth, industrial structure upgrading, and scientific and technology innovation has been explored. The findings indicate notable regional disparities in the DE level across various provincial regions of China. China’s DE development significantly inhibits CEI. Furthermore, the DE’s development has successfully curtailed CE growth via three mediating mechanisms. And the DE exhibits a critical spatial spillover effect on CEI, and that effect also exhibits regional heterogeneity. Our findings can aid in regional DE development and the creation of policies to reduce CEs. 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

At a critical juncture in the global low-carbon transition, the role of artificial intelligence (AI) in facilitating low-carbon growth has become increasingly significant. To accelerate the integration of AI with socio-economic development, China has established National New Generation Artificial Intelligence Innovation and Development Pilot Zones (AIPZ). However, the specific impact of these zones on low-carbon development remains unclear. This study utilized panel data from 30 provinces in China from 2013 to 2022 and employed the multi-period difference-in-differences (DID) model and the spatial autoregressive difference-in-differences (SARDID) model to examine the carbon emissions reduction effects of the AIPZ policy and its spatial spillover effects. The findings revealed that the policy significantly reduced carbon emissions intensity (CEI) across provinces, with an average reduction effect of 6.9%. The analysis of the impact mechanism confirmed the key role of human, technological, and financial resources. Heterogeneity analysis indicated varying effects across regions, with more significant reductions in eastern and energy-rich areas. Further analysis using the SARDID model confirmed spatial spillover effects on CEI. This paper aims to enhance understanding of the relationship between AIPZ and CEI and provide empirical evidence for policymakers during the low-carbon transition. By exploring the potential of the AIPZ policy in emissions reduction, it proposes targeted strategies and implementation pathways for policymakers and industry participants to promote the sustainable development of China’s low-carbon economy. Full article

Agricultural new quality productive forces (ANQPFs) signify the progressive trajectory of modern agriculture. However, their development encounters significant challenges in many nations. The digital economy, characterized by its strong innovative capacity, offers continuous impetus for advancing agricultural new quality productive forces (ANQPFs). Based on panel data from 30 Chinese provinces (2014–2023), this study employs a two-way fixed-effects model, mediation and threshold effect analyses, and a spatial Durbin model to comprehensively assess the influence of the digital economy (DE) on agricultural new quality productive forces (ANQPFs). The findings reveal that (1) the digital economy (DE) significantly enhances the advancement of agricultural new quality productive forces (ANQPFs); (2) while its positive effect is pronounced in eastern, central, and western China, the impact is weaker in the northeastern region; (3) rural financial development (RFD) acts as a mediator in the relationship between digital economy (DE) growth and agricultural new quality productive forces (ANQPFs); (4) the digital economy (DE)’s contribution to agricultural new quality productive forces (ANQPFs) demonstrates non-linear trends; and (5) spatially, while the digital economy (DE) boosts the local agricultural new quality productive forces (ANQPFs), it exerts a negative spillover effect on neighboring areas. This research offers fresh empirical insights into the determinants of agricultural new quality productive forces (ANQPFs) and suggests policy measures to support agricultural modernization. Full article

Green public procurement (GPP) is a pivotal policy instrument for advancing urban low-carbon transitions. Using panel data from 285 Chinese cities (2015–2023), this study employs a panel fixed-effects model, mediation analysis, and spatial Durbin model to assess the impact, influencing mechanisms, and spatial spillover effects of GPP on urban carbon emissions intensity. The key findings reveal the following: (1) a 1% increase in GPP implementation is associated with a 1.360% reduction in local urban carbon emissions intensity. (2) GPP reduces urban carbon emissions intensity through urban green innovation, corporate sustainability performance, and public ecological awareness. (3) GPP exhibits significant cross-boundary spillovers, where a 1% reduction in local carbon emissions intensity induced by GPP leads to a 14.510% decline in that in neighboring cities. These results provide robust empirical evidence for integrating GPP into the urban climate governance framework. Furthermore, our findings offer practical insights for optimizing the implementation of GPP policies and strengthen regional cooperation in carbon reduction. Full article

Highway accessibility plays a vital role in supporting local economic development, particularly in regions lacking access to sea or river ports. Recognizing the functional transformation of road infrastructure, the Chinese government has made substantial investments in its expansion. Nevertheless, a theoretical gap remains in justifying whether such investments yield significant economic returns. Drawing on the theory of economic externalities, this study investigates the causal relationship between highway development and regional economic growth, and assesses whether highway construction leads to an acceleration in growth rates. Utilizing panel data from 14 Chinese cities spanning 2000 to 2014, the synthetic control method (SCM) is employed to evaluate the economic externalities of highway investment. The results indicate a positive impact on surrounding industries. Furthermore, a growth rate forecasting analysis based on Back-Propagation Neural Networks (BPNNs) is conducted using industrial enterprise data from 2005 to 2014. The growth rate in the treated city is 1.144%, which is close to the real number 1.117%, higher than the number for the weighted control group, which is 1.000%. The findings suggest that the growth rate of total industrial output improved significantly, confirming the existence of positive spillover effects. This not only enriches the empirical literature on transport infrastructure but also provides targeted enlightenment for the sustainable development of urban economy in terms of policy guidance. Full article

The rapid development of the digital economy and the pursuit of green transformation are reshaping the innovation landscape of Chinese firms. However, limited attention has been paid to how digital industry agglomeration (DIA) influences corporate green innovation (CGI) at the firm level. Drawing on panel data from China’s A-share listed firms between 2017 and 2021, this study examines the differential effects of specialized agglomeration and diversified agglomeration of digital industry on CGI. The results indicate that DIA can promote CGI, with a 1% increase in DIA associated with a 1.503% increase in green innovation output. Further analysis reveals that specialized agglomeration exerts a significant positive effect, while diversified agglomeration has no evident impact. Our mechanism analysis indicates that knowledge spillovers serve as the key channel through which DIA fosters CGI. Moreover, heterogeneous effects analysis indicates that DIA exerts a stronger influence on non-high-tech enterprises and in regions where environmental regulation is less stringent. Drawing on these insights, fostering specialized digital clusters and strengthening knowledge-sharing mechanisms can help alleviate existing constraints on innovation diffusion, accelerating green innovation and supporting long-term sustainability. Full article

This study investigates the impact and mechanisms of digital inclusive finance (DIF) on high-quality economic development in China. Drawing on panel data from 281 prefecture-level cities between 2011 and 2021, we employ a Spatial Durbin Model (SDM) to analyze both the direct effects and spatial spillovers of DIF. The results indicate that (1) DIF has a significantly positive effect on high-quality development, which remains robust after conducting various stability and endogeneity tests; (2) DIF strongly contributes to economic upgrading in eastern regions, while its impact is weaker or even negative in central and western regions, revealing notable regional disparities exist; (3) a key finding is the identification of a double-threshold effect, suggesting that the positive influence of DIF only emerges when financial and industrial development surpass certain thresholds; (4) results from the two-regime SDM further show that spillover effects are more prominent in non-central cities than in central ones; and (5) mechanism analysis reveals that DIF facilitates high-quality growth primarily by promoting industrial structure upgrading. These findings underscore the importance of region-specific policy strategies to enhance the role of DIF and reduce spatial disparities in development across China. Full article