Search Results (97)

Water rights trading policies play a crucial role in optimizing water resource allocation, improving agricultural water use efficiency, and promoting the sustainability of both agriculture and the environment, while also providing strong support for achieving the ‘dual-carbon’ goals. Utilizing data from 291 prefecture-level cities between 2009 and 2023, this research applies the PSM-DID model to examine how the water rights trading policy affects the net carbon sink intensity in the planting sector. The findings are as follows: First, the water rights trading policy can significantly enhance the net carbon sink intensity of the planting industry, with an average increase of 1.110 tons per hectare. Second, the mediating effect model is employed to test the underlying mechanism. The results show that the water rights trading policy can play a role through two paths: reducing the proportion of food crop planting and reducing the use of fertilizer. Third, heterogeneity analysis is conducted using subgroup regression. The heterogeneity analysis reveals that the policy’s impact is more pronounced in cities characterized by abundant water resources, higher farmer incomes, and those situated in Eastern China. Fourth, a spatial-effect analysis is performed with the spatial Durbin model. The results further reveal that the policy not only directly enhances the net carbon sink intensity in the planting industry but also generates significant spatial spillover effects. In the future, efforts should focus on enhancing the market structure for water rights trading and reinforcing region-specific implementation strategies, guiding the green optimization of the planting structure, preventing the rebound effect of water conservation, and emphasizing the role of spatial linkage to create a new model of regionally coordinated low-carbon development in agriculture. Full article

Innovation in the new energy industry serves not only as a key accelerator for the global green and low-carbon energy transition but also as a core driving force of the ongoing energy revolution. This study utilizes data on publications, patents, and the spatial distribution of representative innovation enterprises in the new energy industry of the Yangtze River Delta urban agglomeration from 2009 to 2023 to construct a multilayer science–technology–industry innovation network. Social network analysis is employed to examine its evolutionary dynamics and structural characteristics, and the Quadratic Assignment Procedure (QAP) is used to investigate the factors shaping intercity innovation linkages. The results reveal that the multilayer innovation network has continuously expanded in scale, gradually forming a multi-core radiative structure with Shanghai, Nanjing, and Hangzhou at the center. At the cohesive subgroup level, the scientific and technological layers exhibit clear hierarchical differentiation, where core cities tend to engage in strong mutual collaborations, while the industrial layer shows a hub-and-spoke pattern combining large, medium, and small cities. In terms of layer relationships, the centrality of the scientific layer increasingly surpasses that of the technological and industrial layers. Inter-layer degree correlations and overlaps also display a strengthening trend. Furthermore, differences in regional higher education scale, urban economic density, and geographic proximity are found to exert significant influences on scientific, technological, and industrial innovation linkages among cities. In response, this study recommends enhancing the leadership role of core cities, leveraging the bridging and intermediary functions of peripheral cities, and promoting application-driven cross-regional innovation collaboration, thereby building efficient science–technology–industry networks and enhancing intercity innovation linkages and the flow of innovation resources, and ultimately promoting the high-quality development of the regional new energy industry. Full article

This paper examines the historical evolution and pathways of rural transformation (RT) at the regional level in four Asian countries—Bangladesh, China, Indonesia, and Pakistan. We conduct a comparative spatial analysis of regional level changes in high-value agricultural production (HVAP) and non-farm rural employment (NFRE). Using long-run data and bivariate mapping, we trace how rural economies have evolved over the past four decades and identify multiple transformation pathways. The results reveal both common upward trends and stark regional contrasts. China demonstrates the most rapid and synergic rise, integrating agricultural upgrading with widespread non-farm rural expansion. Bangladesh and Indonesia show more diverse trajectories, shaped by migration, urbanization, and agro-industrial linkages. Pakistan’s transformation is slower and more fragmented, marked by strong progress in some regions but persistent lags in others. The findings underscore that RT is not linear and can follow diverse pathways—synergic, HVAP-driven, NFRE-driven, remittance-based, or stagnant—depending on geography, natural endowments, policy, and local resource endowments. Our research highlights the need for regionally tailored strategies that link agricultural upgrading with rural labor diversification, strengthen rural–urban connectivity, and ensure that lagging regions are not left further behind. Full article

The digital economy (DE) serves as a crucial engine for breaking through technological stagnation at the low end and achieving carbon neutrality. However, existing studies predominantly explore the impact of the DE on local carbon reduction based on “attribute data”, with less focus on regional carbon collaborative reduction. This study employs a directed-weighted complex network analysis, using provincial panel data from China spanning 2012 to 2022, to characterize the evolutionary features of China’s Inter-regional Collaborative Carbon Reduction Governance Network (ICCGN). Using the Exponential Random Graph Model (ERGM) as an empirical test, the study explores how the DE facilitates collaborative carbon reduction. The results indicate the following: (1) The ICCGN demonstrates transitive triadic linkages, accompanied by increasingly blurred governance boundaries. The Eastern coastal areas have the highest network centrality, and the network core areas, including Guangdong, Chongqing, Gansu, and Qinghai, are gradually expanding, leading to further weakening of governance boundaries. The network’s spatial clustering structure presents four distinct blocks, with network spillover relationships concentrated in the first, third, and fourth blocks. The Eastern coastal areas play a “hub” role in undertaking carbon collaborative reduction, radiating and driving the central and western provinces. (2) From the perspective of the induced effect, the DE enables carbon collaborative reduction, exhibiting isotropic characteristics. (3) Heterogeneity tests show that regions with well-developed digital infrastructure and those with free trade zone constructions promote better effects, with a positive feedback effect in network status: betweenness centrality > degree centrality > closeness centrality. (4) Regarding the enabling mechanism, the DE drives carbon collaborative governance by enhancing technological innovation, promoting industrial structure upgrades, nurturing scientific talents, and reducing educational disparities. Full article

In the context of China’s “dual carbon” strategy, carbon productivity serves as a central in dicator for coordinating economic development with carbon emissions. While the digital economy reshapes spatial economic configurations and affects regional carbon productivity, its spatial interdependence and spillover effects remain insufficiently explored. Our study constructs composite indicators to measure both digital economy development and carbon productivity, examining 30 Chinese provinces from 2011 to 2022 using the super-efficiency SBM model and exploratory spatial data analysis. Spatial regression is applied to assess the spatial influences of the digital economy and the moderating role of industrial structure transforming. Results reveal that: (1) China’s carbon productivity has improved overall but with notable regional disparities; (2) a U-shaped linkage between digital development and carbon productivity is confirmed, with early-stage suppression and later environmental benefits; (3) industrial rationalization and upgrading significantly enhance this relationship, though structural frictions remain obstacles. Full article

The Yellow River Basin (YRB) is a vital water source and an essential ecological barrier in northern China. Currently, it faces pressing challenges related to water resource security and displays pronounced disparities in regional economic development. In recent years, with the elevation of Ecological Protection and High-Quality Development to a national strategy, examining the interaction between industrial growth and water environmental quality within the basin has become a priority. This study focuses on the mainstem of the YRB. By compiling relevant data from 2000 to 2021 and collecting water samples from 20 mainstem sites, and by integrating spatial distribution information of key industrial sectors with water quality records (including representative heavy metals and anions), we found that the basin’s economic output expanded significantly over the past two decades, approximately 11.7 times. The industrial structure evolved across provinces within the basin, exhibiting an overall upward trend in industrial upgrading; nevertheless, substantial differences in industrial composition and transformation persist between the upper and lower reaches. Spatial variations in different industries are closely associated with pollutant concentrations. In particular, major industries in the middle–lower reaches, notably concentrated in regions such as Shandong, possess high total asset values. Output from certain sectors (e.g., petroleum extraction, coal mining and processing, non-metallic mineral mining and processing) is strongly correlated with pollution changes, with marked spatial linkages between their geographic distribution and concentrations of critical heavy metals (Cu, Se, Mo, Mn, Ni). Moreover, spatial analysis of the industry–pollution nexus reveals an apparent paradox in the middle–lower YRB: high industrial output coupled with relatively low levels of heavy metal contamination. This finding highlights the pivotal role of an advanced industrial structure and elevated regional development quality in mediating the balance between economic expansion and environmental pressure. In conclusion, as a globally significant large river basin, the YRB demonstrates a tight coupling between water quality and industrial structure. The results provide spatially explicit scientific evidence and policy guidance for the coordinated advancement of industrial green transformation and water quality improvement in the YRB, offering broader insights into industrial structure patterns and pollution control strategies applicable to major river basins worldwide. Full article

This study explores how China’s National Circular Economy Demonstration City (NCEDC) policy affects the green total factor productivity of urban land (UL-GTFP), using the program as an exogenous policy intervention. Based on panel data for 278 cities from 2003 to 2023 and verified through multiple robustness checks, the results show that the NCEDC policy significantly promotes UL-GTFP, with its positive effects gradually emerging and remaining stable over time. The policy improves land-use efficiency mainly by enhancing resource allocation, driving industrial upgrading, and advancing market-oriented reforms. The effects are more evident in cities with larger land areas, stronger digital infrastructure, and vary across eastern, central, and western regions. Moreover, positive spatial spillovers indicate that pilot cities can boost UL-GTFP in surrounding areas through technology diffusion and industrial linkages. Overall, the findings highlight that circular economy policies can optimize land use and spatial structure, offering practical guidance for regionally tailored strategies to advance sustainable urban transformation. Full article

In many newly industrialized countries, the booming industrial parks have played a crucial role in propelling urban growth, promoting socioeconomic growth, and causing environmental deterioration. This study investigated land use/land cover (LULC) transformation and thermal effects of the “104 Industrial Blocks” in Shanghai, which have been the key industrial development zones since 1995. A total of 64 industrial clusters were identified by merging industrial parks with close spatial linkages. Subsequently, using a data-driven framework that contains data generated from Landsat series C2L2 images and auxiliary datasets, we analyzed land development patterns and associated anomalous thermal response across three scales: macro-level pattern, meso-level ring, and local scale. The results indicate that industrial growth in the downtown shifted from incremental expansion to stock renewal. Suburban areas became the main destinations for industrial relocation. Consequently, the thermal environment underwent a remarkable reconfiguration. Urban heat island (UHI) intensity declined in the downtown, while industrial clusters on the urban periphery emerged as newly emerging heat sources. Around 75% of suburban industrial parks have shifted from low- to medium/high-density patterns, creating new industrial heat islands. In contrast, only 20.31% of suburban industrial parks have shifted from low- to medium-density development without resulting in new urban heat islands. Full article

Against the backdrop of global economic digital transformation and the rapid flow of creative factors, innovation spaces, as the key carriers of inventive activities, drive high-quality development in urban agglomerations. This study develops a three-dimensional framework of “Spatial Structure–Factor Synergy–Institutional Drivers” to uncover the evolution of innovation spaces and industrial shifts in the Beijing–Tianjin–Hebei urban agglomeration, China. Methodologically, spatial econometric techniques were applied to capture both the overall concentration and spatial disparities of innovation. Spatial Gini and variation coefficients measured innovation clustering, while standard deviation ellipses and location entropy identified spatial linkages among high-tech innovation clusters. Geographically weighted regression models explored spatial heterogeneity in influencing factors, and a policy intensity index was constructed to assess the effectiveness of differentiated policy interventions in optimizing innovation resources. Key findings include the following: (1) Innovation spaces are spatially polarized in a “core–periphery” pattern, yet require cross-regional collaboration. Concurrently, high-tech industries demonstrate a gradient structure: central cities leading in R&D, sub-central cities driving industrial applications, and node cities achieving specialized development through industrial transfer. (2) The driving mechanisms exhibit significant spatial heterogeneity: economic density shows diminishing returns in core areas, whereas R&D investment and ecological quality demonstrate increasingly positive effects, with foreign investment’s role evolving positively post-institutional reforms. (3) Regional innovation synergy has formed a preliminary framework, but strengthening sustainable policy mechanisms remains pivotal to advancing market-driven coordination and dismantling administrative barriers. These findings underscore the importance of integrated policy reforms for achieving balanced and high-quality innovation development in administratively coordinated urban agglomerations like BTH. Full article

Agricultural green development cannot be achieved without effective financial support. Based on panel data from 30 provinces in China from 2014 to 2023, this paper uses a coupling coordination model to measure and analyse the degree of coordination between digital inclusive finance and green finance; this further constructs a comprehensive evaluation system for agricultural green development, and on this basis uses a fixed-effect model and a threshold regression model to systematically examine the impact of the coordination between the two on agricultural green development. The findings are as follows: first, the coordination between digital inclusive finance and green finance shows an upward trend over time, shifting spatially from a high trend in the east to a low trend in the west to regional convergence; second, the coordination between the two has a substantial and favourable impact on green agricultural development, which is a conclusion that persists after robustness tests; third, the effect is heterogeneous, with more pronounced promotion effects in non-grain-producing regions, regions with high agricultural technology levels, and low levels of financial exclusion; fourth, the effect exhibits nonlinear characteristics, with coordination and agricultural industrial agglomeration each forming a single-threshold effect. This research lays down a foundational framework for financial coordination in supporting agricultural green development. It suggests promoting a dual-wheel coordination mechanism to effectively empower agricultural green development by strengthening technological empowerment, regional linkage, and designing differentiated policies. Full article

The digital economy, as an advanced economic form, exerts a profound yet unclear influence on water environmental quality within large-scale watersheds. Focusing on the Yellow River Basin (YRB), the second-largest river in China, this study investigates this complex relationship. We developed a novel dual-engine coupling model integrating Support Vector Machines (SVM) and Light Gradient Boosting Machines (LightGBM) to establish comprehensive multi-input, multi-output linkages between digital economy indicators and water quality parameters. Results show that (1) There are notable spatial disparities and synergies in the basin, regions with more developed digital economy generally have better water environmental quality. (2) The SVM model effectively captures the complex spatial relationship between digital economy inputs and water quality outputs, with an average training accuracy above 0.80 and average validation accuracy above 0.70, indicating that digital economy variables are sensitive to water quality changes. (3) The LightGBM model identifies key driving factors and contributions, revealing that digital industrialization has a more significant impact on water quality improvement than industrial digitization. Thus, digital industrialization is a crucial pathway for green transformation in large—scale catchments. Full article

The sustainable transformation of areas associated with mining is an essential contemporary challenge. In the course of such transformations, economic benefits are confronted with community criticism of heavy industry. In this context, the study examines spatial solutions implemented in the revitalisation of areas adjacent to active industrial sites. The article aims to characterise solutions applied in locations that elude a straightforward division into industrial and post-industrial. The motivations of the entities involved in the construction and the effects of implementing such projects are investigated. To achieve this aim, compositional and visual linkages in four locations (in Germany and Poland) were analysed, along with the intentions of designers and investors and the opinions of users. The study revealed the influence of political decisions on spatial solutions, an aspect not previously analysed, which has led to a limited understanding of the role they play in the transformation. It was indicated that drawing users’ attention to the aesthetic values of active industrial areas coincides with diverting attention from their nuisances. The discreet cooperation between local authorities, designers, and industry (as expressed in architectural solutions) was emphasised. The research opens a field for discussion on managing community perceptions through spatial solutions. Full article

The emergency industry refers to a comprehensive industrial system of products, technologies, and services aimed at preventing, responding to, and mitigating emergencies. The emergency industry is primarily oriented toward disaster prevention and mitigation, providing direct support to enhance societal resilience. Given the frequent occurrence of natural disasters and the strategic layout of global emergency technologies, it is of great practical significance to study how the science and technology systems of disaster-prone countries respond. Based on the theories of disaster economics and innovation geography, this paper constructs a mediation effect model to investigate how China improves the key technological capabilities of its emergency industry through three response pathways—demand stimulation, technological advancement, and educational enhancement—following natural disasters. The stepwise testing approach, which integrates the mediation effect model with the spatial Durbin model, consists of three stages. The first stage tests the total effect model to assess how disasters impact local key technologies and their spatial spillover on adjacent regions. The second stage examines the direct influence of disasters on the three pathways and their spatial spillover using the mediator equation. The third stage uses the outcome equation with the mediator to evaluate how the pathways affect local key technologies and neighboring regions after controlling for disaster impacts. We offer both theoretical insights and empirical evidence to support specialized research on technological diffusion induced by disasters. The result shows that although the direct negative impact of disasters is inevitable, the institutional advantages of China’s emergency rescue and innovative collaborative efforts have played a significant role in promoting key technologies. Under the new national system, China is progressively establishing a spatial framework wherein emergency products are allocated across regions, key technologies are synergistically integrated, and the development of emergency-related disciplines is promoted through regional collaboration in response to the frequent occurrence of natural disasters. This demonstrates that the advancement of key technologies in China’s emergency industry is significantly supported by inter-regional cooperation and linkage mechanisms. Full article

Harmonizing economic growth and carbon emissions is key to reaching the “dual carbon” targets. This research centers on the seven key urban agglomerations within the Yellow River Basin (YRB) and establishes an integrated research framework of decoupling effect quantification–spatial association recognition–driving factor analysis. By combining the Tapio decoupling model, a modified gravity model, social network analysis (SNA), and the Logarithmic Mean Divisia Index (LMDI) method, the study systematically evaluates the decoupling states, spatial association structure, and driving mechanisms between regional carbon emissions and economic growth from 2001 to 2020. The results show that: (1) All seven urban agglomerations exhibit a simultaneous upward trend in both carbon emissions and GDP, but significant regional disparities exist, with some agglomerations demonstrating a green growth pattern where economic growth outpaces carbon emissions. (2) Weak decoupling is the predominant type among urban agglomerations and their constituent cities in the YRB. Notably, some regions have regressed to growing connection or growing negative decoupling during 2016–2020. (3) The spatial network of carbon emission decoupling effects exhibits a core-periphery structure characterized by stronger eastern regions and weaker western regions, with the Shandong Peninsula and Guanzhong Plain urban agglomerations serving as core nodes for regional linkage. (4) Per capita GDP and technological level play a dominant role in promoting decoupling, while energy intensity and the population carrying intensity of the real economy are the primary inhibiting factors; the impact of industrial structure shows an unstable direction. Grounded in these findings, this study formulates differentiated carbon reduction pathways tailored to regional heterogeneity, providing theoretical insights and actionable guidance to facilitate the low-carbon transition and coordinated governance of urban agglomerations. Full article

With the impact of fossil energy on the climate environment and the development of energy technologies, new energy vehicles, represented by electric cars, have begun to receive increasing attention and emphasis. The rapid proliferation of public charging infrastructure for NEVs has concurrently influenced traditional petrol station networks, creating measurable disparities in their spatial distributions that warrant systematic investigation. This research examines Wenzhou City, China, as a representative case area, employing multi-source Point of Interest (POI) data and spatial analysis models to analyse differential characteristics in spatial layout accessibility, service equity, and underlying driving mechanisms between public electric vehicle charging stations (EV) and traditional gas stations (GS). The findings reveal that public electric vehicle charging stations exhibit a pronounced “single-centre concentration with weak multi-centre linkage” spatial configuration, heavily reliant on dual-core drivers of population density and economic activity. This results in marked service accessibility declines in peripheral areas, resembling a cliff-like drop, and a relatively low spatial equity index. In contrast, traditional gas stations demonstrate a “core-axis linkage” diffusion pattern with strong coupling to urban road networks, showing gradient attenuation in service coverage efficiency along transportation arteries, fewer suburban service gaps, and more gradual accessibility reductions. Location entropy analysis further indicates that charging station deployment shows significant capital-oriented tendencies, with certain areas exhibiting paradoxical “excess facilities” phenomena, while gas station distribution aligns more closely with road network topology and transportation demand dynamics. Furthermore, the layout characteristics of public charging stations feature a more complex and diverse range of land use types, while traditional gas stations have a strong dependence on industrial land. This research elucidates the spatial distribution patterns of emerging and legacy energy infrastructure in the survey regions, providing critical empirical evidence for optimising energy infrastructure allocation and facilitating coordinated transportation system transitions. The findings also offer practical insights for the construction of energy supply facilities in urban development frameworks, holding substantial reference value for achieving sustainable urban spatial governance. Full article