Search Results (170)

The sustainable development of higher education exhibits a strong and measurable association with the level of regional innovation capacity. Drawing on panel data covering 31 provincial-level administrative regions in China from 2010 to 2022, we construct evaluation frameworks for both higher education and regional innovation capacity using the entropy weight method. These are complemented by kernel density estimation, spatial autocorrelation analysis, Dagum Gini coefficient decomposition, and the Obstacle Degree Model. Together, these tools enable a comprehensive investigation into the spatiotemporal evolution and driving mechanisms of coupling coordination dynamics between the two systems. The results indicate the following: (1) Both higher education and regional innovation capacity indices exhibit steady growth, accompanied by a clear temporal gradient differentiation. (2) The coupling coordination degree shows an overall upward trend, with significant inter-regional disparities, notably “higher in the east and low in the west”. (3) The spatial distribution of the coupling coordination degree reveals positive spatial autocorrelation, with provinces exhibiting similar levels tending to form spatial clusters, most commonly of the low–low or high–high type. (4) The spatial heterogeneity is pronounced, with inter-regional differences driving overall imbalance. (5) Key obstacles hindering regional innovation include inadequate R&D investment, limited trade openness, and weak technological development. In higher education sectors, limitations stem from insufficient social service benefits and efficiency of flow. This study recommends promoting the synchronized advancement of higher education and regional innovation through region-specific development strategies, strengthening institutional infrastructure, and accurately identifying and addressing key barriers. These efforts are essential to fostering high-quality, coordinated regional development. Full article

The inter-provincial border region in eastern China, encompassing the junction of Jiangsu, Anhui, Shandong, and Henan provinces, serves as a crucial zone that connects the important economic zones of Beijing–Tianjin–Hebei and the Yangtze River Delta. It is of great significance to study the temporal variation characteristics, spatial distribution patterns, and driving factors of PM_2.5 concentrations in this region. Based on the PM_2.5 concentration observation data, ground meteorological data, environmental data, and socio-economic data from 2022 to 2024, this study conducted in-depth and systematic research by using advanced methods, such as spatial autocorrelation analysis and geographical detectors. The research results show that the concentration of PM_2.5 rose from 2022 to 2023, but decreased from 2023 to 2024. From the perspective of seasonal variations, the concentration of PM_2.5 shows a distinct characteristic of being “high in winter and low in summer”. The monthly variation shows a “U”-shaped distribution pattern. In terms of spatial changes, the PM_2.5 concentration in the inter-provincial border region of eastern China (Jiangsu, Anhui, Shandong, Henan) forms a gradient difference of “higher in the west and lower in the east”. The high-concentration agglomeration areas are mainly concentrated in the Henan part of the study region, while the low-concentration agglomeration areas are distributed in the eastern coastal parts of the study region. The analysis of the driving factors of the PM_2.5 concentration based on geographical detectors reveals that the average temperature is the main factor affecting the PM_2.5 concentration. The interaction among the factors contributing to the spatial differentiation of the PM_2.5 concentration is very obvious. Temperature and population density (q = 0.92), temperature and precipitation (q = 0.95), slope and precipitation (q = 0.97), as well as DEM and population density (q = 0.96), are the main combinations of factors that have continuously affected the spatial differentiation of the PM_2.5 concentration for many years. The research results from this study provide a scientific basis and decision support for the prevention, control, and governance of PM_2.5 pollution. Full article

In the context of the new developmental philosophy, this study aimed to address the bottleneck of regional sustainable development; it constructs a three-system evaluation indicator system for Industrial Structure Optimization (ISO), Ecological Environment Management (EEM), and Socio-economic Development (SED), based on panel data from 20 cities in the Western Taiwan Straits Economic Zone between 2011 and 2023. To reveal how the synergistic development of the three subsystems in different domains can achieve sustainable development through their interactions and to analyze the dynamic patterns of the three subsystems, this study employed the panel vector autoregression (PVAR) model to examine the interactions between subsystems. Additionally, drawing on the framework of evolutionary economics, the study quantified the temporal evolution and spatial characteristics of the coupling coordination level among the three subsystems based on the results of the degree of coupling coordination model. The results indicate the following: (1) ISO shows a significant upward trend, EEM slightly declines, and SED experiences minor fluctuations before accelerating. (2) ISO, EEM, and SED exhibited self-reinforcing effects. (3) The degree of coupling, coordination, and coupling coordination all exhibit a trend of “fluctuating and increasing initially, followed by steady growth”. The spatial patterns of the degree of coupling, coordination, and coupling coordination have shifted from “decentralized” to “centralized”, with clear signs of synergistic development. (4) The difference in the degree of coupling coordination along the north–south direction remained the primary factor contributing to inter-regional disparities. Regions with the higher degrees of coupling coordination were concentrated in the southeastern coastal areas, while those with the lower degrees of coupling coordination appeared in the northeastern mountainous areas and southwestern coastal areas. (5) The spatial connection in the strength of the degree of coupling coordination has gradually increased, with notable intra-provincial connections and weakened inter-city connections across the province. The study’s results provided decision-making references for the construction of a sustainable development community. Full article

Facility agriculture can increase production efficiency and alleviate resource constraints. Its developmental level has become one of the most important indicators of the level of agricultural modernization worldwide. The Chinese government has attached great importance to the development of facility agriculture in recent years. Since 2020, the “No. 1 Document” has continuously emphasized and deployed the development of facility agriculture. Global climate change has greatly impacted the traditional agricultural production that is vulnerable to weather changes, while the development of facility agriculture can to some extent alleviate the limitations of climate conditions on agricultural production. However, it is unclear whether facility agriculture can help alleviate the adverse effects of global climate change, i.e., reducing greenhouse gas emissions. In view of this, in this research, based on the data from the latest National Compilation of Cost and Benefit Data on Agricultural Products in 2022, the greenhouse gas emissions and carbon emission indicators of open-field and greenhouse cucumber productions in China were measured using the life cycle assessment method (the full cycle of agricultural ecosystems). The results show that the average total greenhouse gas emissions (4572.67 kgCE·hm⁻²) from China’s facility cucumber production system are significantly higher than those from traditional open-field production methods (8712.86 kgCE·hm⁻²), with net greenhouse gas emissions from facility cucumber cultivation being on average 98.78% higher than those from open fields. Combining indicators such as land carbon intensity, carbon productivity, and carbon economic efficiency, it can be concluded that the sustainability of facility cucumber cultivation is lower than that of open-field cucumber cultivation. Additionally, considering the comprehensive differences in economic development, resource endowments, planting methods, and technological inputs across different regions, there are significant inter-provincial variations in the greenhouse gas composition, carbon sequestration, carbon ecological efficiency, carbon productivity, and carbon economic efficiency of both open-field and facility cucumbers. However, overall, carbon productivity shows a certain geographical proximity effect, with an increasing trend from south to north for open-field cucumbers. The above research findings provide direct evidence for the development of facility agriculture in China. Based on these measurement results and analytical conclusions, this paper further explores how to reduce carbon emissions and promote emission reduction in facility agriculture, providing reliable empirical support for policy implementation by relevant authorities and academic research. Full article

The Yellow River Basin (YRB) is a significant economic development region in China; however, it faces the challenge of underdeveloped economic levels, which impacts the sustainable development of the national economy. This study constructs an index system for high-quality economic development (HQED) based on five development concepts. The CRITIC method was utilized to comprehensively evaluate 78 prefecture-level cities in the YRB from 2000 to 2022. Techniques such as the Dagum Gini coefficient, exploratory spatial data analysis, Markov chain analysis, and the obstacle degree model were employed to investigate the temporal and spatial evolution of HQED levels and their associated obstacles in the YRB. The findings indicate a positive temporal trend in the HQED index, with increasing intra-group differences and overlapping issues among regions, while inter-group differences are decreasing. Nevertheless, the primary contradiction in the YRB continues to arise from inter-group disparities. Spatially, the development regions are predominantly centered around provincial capitals, exhibiting a pronounced “fault line” phenomenon and characteristic “spatial proximity”. In terms of evolutionary trends, the likelihood of each region maintaining its current state is relatively high; however, regions with higher-quality neighborhoods demonstrate a lower probability of stability and a greater likelihood of upward mobility. The positive impacts of high-quality neighborhoods outweigh the negative effects associated with low-quality areas. In terms of obstacles, factors such as sharing and coordination hinder progress in HQED in the YRB, with challenges related to coordination, innovation, and openness intensifying in recent years. Full article

Drawing on the longitudinal dataset from 262 cities at the provincial tier and higher across China between 2011 and 2022, this research employs the production model to formulate the China Urban Industrial Land Mismatch Index, quantifying the extent of industrial land misalignment across China. It also analyzes its spatiotemporal evolution characteristics and regional differentiation characteristics, and explores the influence of China’s urban industrial land discordance on the advancement of urban ecological modernization. The key insights are outlined below. Firstly, across the entire spectrum of Chinese urban centers, cities from the eastern, central, and western zones, as well as those situated along the Yangtze River and the Yellow River basins, exhibit comparable patterns in industrial land misalignment. The extent of industrial land discordance has diminished, regional disparities have lessened to some degree, and there is an absence of polarization or the Matthew effect. Secondly, the variation in industrial land discordance within cities in the eastern region is the most pronounced, followed by the central region, with the western region showing the least disparity. The greatest contrast in the urban industrial land mismatch is found between the eastern and central regions. The primary driver of the discrepancy in industrial land misalignment across the eastern, central, and western regions is predominantly the ultra-variable density, followed by intra-regional disparities, with inter-regional differences contributing the least. Furthermore, the variation in the industrial land mismatch within cities in the Yangtze River Basin surpasses that within cities in the Yellow River Basin. The disparity in industrial land misalignment between the two follows a pattern of initially increasing, then decreasing, and subsequently rising again. The primary origin of this discrepancy lies within regional variations, followed by ultra-variable density, with inter-regional differences contributing the least. Thirdly, the regression analysis reveals that the discordance in industrial land use across Chinese cities exerts a substantial negative influence on urban ecological evolution. This effect operates through technological innovation and the employment levels in the secondary sector. Fourthly, industrial land discordance significantly hampers urban ecological advancement in the eastern region, shows a negative but statistically insignificant impact in the central region, and has a positive yet inconsequential effect in the western region. Moreover, the misalignment of industrial land exerts a notable suppressive influence on the ecological modernization of cities within the Yangtze River Basin, while it plays a significant role in fostering the ecological modernization of cities in the Yellow River Basin. Fifth, the mismatch of urban industrial land has produced significant negative spatial spillover effects on urban ecological modernization. Full article

Autochthonous microorganisms play critical roles in shaping the quality of Chinese sausages and may be influenced by local climate and/or processing conditions. The present study aimed to reveal the interprovincial differences in microbial community between Sichuan and Guizhou sausages, as well as driving factors based on high-throughput sequencing and bioinformatic analysis. The results indicated that Cobetia, Debaryomycetaceae, Kurtzmaniella, and Candida zeylanoides served as biomarkers for Sichuan sausages. In contrast, Enterococcus, unclassified Cyanobacteriales, Lactobacillales, Aspergillus vitricola, Mortierella, Fusarium, and Penicillium were identified as biomarkers for Guizhou sausages. Furthermore, salt content and moisture level showed positive correlations with Cobetia, Staphylococcus, Debaryomyces, and Kurtzmaniella, mainly found in Sichuan sausages. Conversely, pH and water activity (Aw) were positively associated with potential pathogenic bacteria (e.g., Vibrio, Cyanobacteria, Enterococcus, and Aeromonas) and fungi (e.g., Aspergillus, Fusarium, and Penicillium), which were mainly distributed in Guizhou sausages. Notably, microbial composition discrepancies between Sichuan and Guizhou sausages were primarily driven by processing conditions rather than regional climate factors. Collectively, these findings provide valuable insight for developing novel specific starters. Full article

It is important to study the difference, distribution dynamics and convergence of China’s renewable energy development level to stimulate its potential. Based on China’s provincial panel data from 2006 to 2021, this paper analyzes the regional characteristics of China’s renewable energy development using the Dagum Gini coefficient, kernel density estimation, σ convergence and spatial β convergence, and draws the following conclusions: Firstly, renewable energy in the country and the four major regions have achieved stable growth. Secondly, the intra-group differences in China and the four major regions are gradually decreasing, and the contribution rate of inter-group differences to the overall differences is gradually increasing, which is the main source of the overall differences. Thirdly, the national renewable energy development has a positive spatial correlation. Fourthly, there are σ convergence and spatial β convergence in the whole country and the four major regions; the σ convergence coefficient gradually decreases, and the β convergence regression coefficient is significantly negative. Therefore, this paper proposes the following recommendations: formulate government policies according to local conditions, strengthen technical exchanges and cooperation among regions, and encourage investment in renewable energy development; thus, we can promote a more efficient realization of the “dual carbon” goal. Full article

The role of the digital business environment (DBE) in the sustainable development of enterprises (SDE) has received extensive attention. This study aims to discover what factors of DBE affect SDE. The empirical results based on China’s inter-provincial panel data from 2011 to 2021 show that DBE has a dual impact on the quantity and quality of enterprises from five dimensions, digital infrastructure, digital industrial environment, digital R&D support, digital talent supply, and digital market demand, among which the digital industrial environment, digital R&D support, and digital talent supply are more conducive to enterprise sustainability. The digital industry environment, digital R&D support and digital talent supply are more conducive to improving enterprise development quality. The results of the heterogeneity analysis further show that there is a significant difference in the regional effect of DBE on SDE. Enterprises in eastern, central, and western China show a tendency to differentiate the demand for different factor conditions, such as technology, industry, and talent, in the process of development. The research in this study provides new theoretical perspectives and empirical evidence for optimising the business environment and achieving SDE. Full article

Amid global economic transformation, a persistent productivity gap exists between developed and developing nations in agriculture sector, shaped by technological advancements and shifting resource allocation patterns. Agricultural socialized services (ASS), defined as organized systems providing technical support, mechanization assistance, information services, market linkages, and resource optimization to farmers, have emerged as critical mechanisms for agricultural development. In developing economies, these services catalyze gains in agricultural labor productivity through the integration of advanced technologies and the mechanization of farming practices. Using panel data from 30 Chinese provinces during 2011 to 2022, this study investigates the relationship between ASS and ALP, focusing on regional heterogeneity, threshold effects, and spatial spillovers. The combination of spatial econometric methods and threshold analysis was selected for its unique capacity to capture both the geographic interdependencies and nonlinear relationships that characterize agricultural development processes. These thresholds at 5.254 and 8.478 represent critical points where the impact of ASS on ALP significantly changes in magnitude, revealing a nonlinear relationship that evolves across different stages of agricultural development. The study highlights notable regional disparities in the impact of ASS. Specifically, ASS is more effective on ALP in eastern, central and key food-producing regions, while its impact is relatively weak in western and non-food-producing regions. Spatial spillover analysis indicates that advancements in ASS create positive externalities, extending beyond their immediate implementation zones and facilitating inter-provincial agricultural cooperation and development. These findings provide crucial guidance for policymakers and agricultural service providers to optimize resource allocation and service delivery strategies. By identifying critical development thresholds and regional variations, this research offers evidence-based support for government officials designing targeted agricultural policies and enterprises developing region-specific service models to foster sustainable agricultural growth across diverse regional landscapes. Full article

Land use supports production and living activities and provides ecosystem services for people. With the flow of capital, goods, and services among regions, trade leads to the transfer of carbon emissions from importing regions to exporting regions, and this is telecoupled with land systems in different regions. Although significant progress has been made in quantifying embodied carbon emissions induced by interprovincial and international trade, the telecoupling relationship between carbon emissions and land systems has not been sufficiently investigated. Here we followed the telecoupling theoretical framework and used the multi-region input–output (MRIO) model to examine the spatial pattern of embodied carbon emissions by land use in China due to interprovincial trade. The results show that the spatial patterns of embodied carbon emissions from the production end and from the consumption end are different based on land use type. The provinces with rich energy resources and favorable conditions such as Inner Mongolia, Xinjiang, and Heilongjiang undertake carbon emissions from the agricultural and industrial land use of other provinces. In contrast, the provinces with large economies but scarce resources such as Zhejiang and Guangdong export larger portions of their carbon emissions to the land use of other provinces. Across China, developed regions generally exported more carbon emissions from land use than they undertake from other developing regions. The carbon transfer in agricultural land was prominent between the eastern and western regions. The carbon emissions of industrial land were generally transferred from southern regions to northern and western areas. Our research reveals different patterns of embodied carbon emissions for different land use types, and these findings could provide more detailed information for policy-making processes to achieve fair carbon emissions and sustainable land use. Full article

Water resource tax can regulate water consumption through economic leveraging, enhance water conservation awareness among enterprises and society, and optimize the industrial structure, thus promoting rational water resource use and sustainable development. However, the current water resource tax reform in China is still in the pilot exploration stage, and it is unclear if it will actually increase agricultural water use efficiency. We built a multi-period double-difference model and a mediation effect model based on 2011–2022 inter-provincial panel data in order to investigate the water resource tax reform’s impact on agricultural water conservation and its trajectory. The findings demonstrate that agricultural water use efficiency has been greatly increased by the water resource tax reform, and this conclusion remains strong even after parallel trend and placebo testing. The tax reform has primarily increased agricultural water use efficiency through crop cultivation structural adjustments and water-saving technologies’ advancement. When examining inter-provincial disparities, we found a more evident policy impact in economically developed and water-scarce regions. Further results show that the water resource tax reform has significantly reduced the groundwater portion of the regional water use structure, which indicates that it has synergistically curbed groundwater exploitation and promoted regional ecological restoration. Moreover, this paper demonstrates that the policy has realized water conservation in agriculture while avoiding a negative effect on agricultural economic growth. Full article

The implementation of the Carbon Border Adjustment Mechanism (CBAM) carries profound implications for China’s export trade with the EU. However, a comprehensive analysis of CBAM’s impact on provincial export trade, particularly one grounded in industrial linkages and incorporating diverse policy scenarios, remains limited. To address this gap, this study develops a mechanistic framework based on industrial linkage theory and dynamically integrates key factors such as the scope of industries covered by CBAM, carbon emission accounting boundaries, and carbon pricing into a multi-scenario quantitative model. Leveraging a refined multi-region input–output (MRIO) model, we quantitatively assess the effects of CBAM on China’s provincial exports to the EU under various scenarios. The findings show that CBAM significantly raises export costs, leading to a pronounced decline in the competitiveness of five highly vulnerable industries. As CBAM expands to include sectors covered by the EU Emissions Trading System (EU ETS), the total levies on affected industries increase considerably, ranging from USD 0.07 billion to USD 2.25 billion depending on the scenario. Conversely, seven provincial industries, such as the chemical industry in Shanxi, experience only limited impacts due to their low direct carbon intensity and minimal overall increases in carbon tariffs. Then, the study underscores the pivotal role of China’s domestic carbon pricing mechanism in mitigating the effects of CBAM. Higher domestic carbon prices enhance China’s capacity to respond effectively, thereby reducing the overall impact of the mechanism. By adopting an inter-industry linkage perspective, this study provides new insights into assessing the multidimensional impacts of CBAM on China’s exports to the EU across provinces under different policy design scenarios, providing lessons for different categories of provinces on how to cope with CBAM. Full article

In the context of sustainable development, breaking free from resource endowment constraints and promoting energy transformation are long-term goals of concern. The digital economy empowers the development of the energy industry and provides a feasible path for improving energy efficiency. This article selects interprovincial panel data from China to analyze the direct and indirect impacts of China’s digital economy on green total factor energy efficiency (GTFEE), as well as spatial spillover effects. Based on the calculation of green total factor energy efficiency, static and dynamic panel models are used to analyze the direct impact of the digital economy on green total factor energy efficiency through index decomposition and threshold models, as well as the indirect impact of digital economy technology effects on it. The research results indicate that the direct impact of the digital economy on GTFEE exhibits a positive U-shaped effect. Indirect impact analysis shows that technological innovation has a significant dual threshold effect on the variables of green total factor energy technology efficiency index and green total factor energy technology progress index. Further analysis using the spatial Durbin model shows that the digital economy has nonlinear spatial spillover effects on GTFEE, with regional heterogeneity and resource endowment differences. Studying the impact of digital economy development on green all-factor energy efficiency is of great practical significance in order to propose suggestions for promoting green and sustainable development. Full article

The semi-humid evergreen broadleaved forest (SEBF) is the zonal vegetation type of western subtropical regions in China. Under human and natural disturbance, the area of SEBFs is severely shrinking, with remaining fragments scattered across mountains of the Central Yunnan Plateau. To explore the mechanisms of community assembly and species maintenance in the severely fragmented SEBFs, we selected three sites—Jinguangsi Provincial Nature Reserve, Huafoshan Scenic Area, and Qiongzhusi Forest Park—across the range of this vegetation type, and sampled a total of 42 plots of forest dominated by Castanopsis orthacantha Franch., the most widely distributed community type of SEBFs. We compared the species richness and composition of the communities of different age classes, employed the net relatedness index to characterize the phylogenetic structure of communities, and used Mantel tests and partial Mantel tests to quantify the impacts of spatial distance, age class, and habitat factors (including climate, topography, and soil) on species turnover across different spatial scales (i.e., intra- and inter-site) for trees, shrubs, and herbs, respectively. The results indicated the following: (1) In the young stage, the C. orthacantha communities exhibited a species richness statistically lower than those in middle-aged and mature communities. Notably, the difference in species richness among age classes was merely significant for shrub and herb species. Moreover, the phylogenetic structure changed towards over-dispersion with increasing community age. (2) The age class of the community played a pivotal role in determining taxonomic β diversity in the tree layer, while climate and soil factors significantly influenced β diversity in the shrub and herb layers of the communities. (3) Environmental filtering emerged as the predominant force shaping community assembly at the intra-site scale, whereas spatial distance was the primary determinant at the inter-site scale. Meanwhile, dispersal limitation versus biological interaction seemed to dominate the community dynamics of the C. orthacantha communities in the early versus middle and old ages, respectively. Our results highlight the variability in community assembly processes across different spatial and temporal scales, providing insights into the priority of the conservation and restoration of severely degraded zonal SEBFs. Expanding research to broader scales and other SEBF types, as well as considering the impacts of climate change and human activities, would provide further insights into understanding the mechanisms of community assembly and effective conservation strategies. Full article