Search Results (300)

This study examined the spatial carbon emission effects of new quality productive forces (NQPs) using provincial panel data from China during 2012–2021. A dynamic spatial Durbin model with instrumental variable generalized method of moments estimation was used to address endogeneity in assessing direct and spillover effects on carbon emission intensity. Results show that the direct effect (0.0072) and spatial spillover ($-0.0100$) are statistically insignificant, with no identifiable emission reduction during the sample period. Technology diffusion exhibits a J-curve left-sided feature with a short-term total effect of 0.0553, as general technology diffusion accompanies energy-intensive capacity expansion without crossing the turning point. The spatial environmental Kuznets curve reveals a positive intensification effect: neighboring per-capita gross domestic product increases local carbon emission intensity, with marginal effects rising from 0.084 to 0.168. Heterogeneity analysis shows that green-technology-oriented NQPs exhibit the most promising emission-reduction potential, while digital infrastructure generates carbon rebound. These findings challenge the presumptions that local income growth automatically reduces carbon and that technology diffusion naturally leads to reduced emissions. Cross-regional carbon compensation mechanisms, green technology market standards, and extended technology transformation evaluation periods are recommended. Full article

Background: Synergistic development of the coupled and coordinated relationship of medical service capacity, residents’ health level, and regional economic development (MRR) is crucial for realizing the “Healthy China 2030” strategy. This study aims to analyze the spatiotemporal features of the coupling coordination degree (CCD) of MRR. Methods: Based on panel data from 2012 to 2022, we constructed the MRR evaluation system. The entropy method was adopted to calculate the comprehensive index of each subsystem, and the coupling coordination degree model (CCDM) was used to evaluate the CCD of MRR during the study period. Furthermore, we applied exploratory spatial data analysis, the Dagum Gini coefficient decomposition, extreme gradient boosting (XGBoost) and Shapley Additive Explanations (SHAP) to explore spatiotemporal dynamic characteristics and factors associated with CCD. Results: (1) Throughout the study period, the overall value of the MRR composite system increased from 0.3798 to 0.4097, with an average annual growth rate of 0.54%. (2) CCD remained generally low, dominated by the basic coordination type. Both global and local spatial autocorrelation analyses revealed significant differentiated spatial clusters of high and low CCD, with the overall spatial distribution fitting a “high in the east, low in the west” pattern. Inter-regional gaps are the main reason for the overall differences. (3) In the full sample, Population density (PD)was the dominant external predictive contributor, with a mean absolute SHAP value of 0.028, followed by Internet broadband access ports (IBAP)and Government health expenditure (GHE). The key predictive factors differed among regions. Conclusions: This study clarifies spatiotemporal evolution and predictive contributors of CCD. These findings provide valuable insights for decision-makers to promote coordinated MRR development. Full article

Improving green land use efficiency is an important approach to reconciling urban development with resource and environmental constraints. Using panel data from 280 cities at the prefecture level and above in China from 2011 to 2024, this study employs a dynamic spatial Durbin model to examine the effects of the digital economy on green land use efficiency, focusing on temporal dynamics, spatial spillover effects, distance-decay boundaries, moderating mechanisms, and urban heterogeneity. The results show that the digital economy significantly improves local green land use efficiency. Its spatial externalities exhibit a pronounced dynamic transition from the spatial siphoning effect in the short term to the green spillover effect in the long term. The short-term spatial siphoning effect is mainly concentrated within approximately 200 km, whereas the long-term green spillover effect extends to approximately 250 km, indicating a clear distance-decay pattern. Green technological innovation and industrial upgrading mitigate short-term spatial siphoning and strengthen the long-term green spillover effect, whereas factor misallocation intensifies short-term spatial siphoning and weakens the long-term green spillover effect. The green-enabling effect of the digital economy is stronger in cities in eastern China, resource-based cities, high-tier cities, and cities with stricter environmental regulation. These findings underscore the importance of coordinating digital economy development with cross-regional green land governance, while strengthening regional absorptive capacity and improving factor allocation efficiency. Full article

Rapid urbanization presents a fundamental challenge to global sustainable development, as urban expansion increasingly conflicts with resource constraints, ecological carrying capacity, and carbon emission mandates. Serving as a highly spatially heterogeneous laboratory, China offers a critical context for embedding green development into urban efficiency assessments. This study reconceptualizes new urbanization efficiency (NUE) through a multidimensional framework encompassing resource inputs, coordinated development processes, and sustainable outcomes. Using a panel of 281 prefecture-level cities, we evaluated NUE via a remote-sensing-constrained Super-SBM model, utilizing LISA time paths and an interpretable spatial machine learning framework (GWR-XGBoost-SHAP) to unpack its spatiotemporal dynamics. Key findings indicate: (1) China’s NUE exhibited a fluctuating upward trajectory, transitioning from an east-high/west-low to a south-high/north-low spatial pattern. (2) Spatiotemporal analysis revealed strong spatial inertia and profound path dependency in North China, characterizing it as a persistent low-value basin, whereas southeastern coastal cities demonstrated dynamic, path-breaking trajectories. (3) While green development intensity, industrial upgrading, and technological innovation emerged as primary drivers, they operate through complex nonlinear mechanisms. Specifically, green development and innovation exhibit threshold-triggered synergies, population agglomeration acts as a nonlinear amplifier, and external openness presents context-dependent negative interactions. These findings refine NUE measurement methodologies and provide a transferable analytical framework to inform differentiated, place-based urbanization policies for regions navigating the friction between urban growth and ecological limits. Full article

Decoupling economic growth from carbon emissions is central to the sustainable development of rapidly urbanizing economies, and urban agglomerations are the pivotal spatial units for delivering this transition under China’s dual-carbon goals, yet systematic cross-agglomeration comparisons that could inform differentiated sustainability policy remain scarce. Using panel data for 107 prefecture-level cities in five agglomerations—the Yangtze River Delta (YRD), Beijing–Tianjin–Hebei (BTH), Pearl River Delta (PRD), Chengdu–Chongqing (CY), and the middle reaches of the Yangtze River (MRYR)—across five benchmark years spanning 2005–2023, we combined a two-way fixed-effects environmental Kuznets curve (EKC) model, the Tapio decoupling model, and cross-sectional quadrant analysis to examine the growth–emission relationship in shape, decoupling dynamics, and spatial structure. All five agglomerations traced an inverted-U trajectory, with turning-point per capita gross domestic product (GDP) rising in the order CY < PRD < BTH < MRYR < YRD. Once fixed effects and structural controls were added, most quadratic terms became insignificant and reversed sign after the secondary-industry share and carbon intensity entered; only the PRD and BTH retained a significant nonlinear form. The net income effect is therefore largely monotonic, with the inverted U carried by industrial upgrading and energy-efficiency gains. Tapio decoupling followed a non-monotonic “improve-then-regress” path, with expansive negative decoupling re-emerging across all agglomerations during 2020–2023. Spatially, high-value clustering persisted in the YRD, weakened in the BTH after 2020, and concentrated on single cores in Chengdu and Wuhan. We accordingly propose sustainability-oriented low-carbon pathways differentiated jointly by agglomeration and quadrant. By showing that decoupling is stage-dependent and reversible rather than an automatic by-product of income growth, our findings indicate that durable progress toward regional sustainability hinges on structural transformation and coordinated governance tailored to each agglomeration’s stage of development. Full article

In this study, a high-order Galerkin–Numerov approach is presented to solve the transient vibration problem of anisotropic Kirchhoff plates supported by a uniform Vlasov foundation. A discretization of the governing fourth-order plate equation is derived based on a mixed boundary value problem and a hybrid Hermite–sine Galerkin formulation, which maintains the C1-continuity properties of classical plate theory. The resulting reduced-order modal system is integrated in time with the Numerov scheme, which is fourth-order accurate, and has a small numerical dispersion and good phase-preserving properties for oscillatory dynamics. The proposed methodology is evaluated using stability and convergence tests and parametric investigations. The fourth-order temporal convergence and rapid spectral-like spatial convergence of the numerical results are validated, and the long-time accuracy and robustness of the formulation is confirmed by the negligible phase error and bounded energy drift. The results from the parametric study indicate that the thickness of the plates and the stiffness of the Winkler foundation are the two most important mechanisms for vibration suppression, while the orthotropic coupling and the Vlasov shear interaction have substantial effects on the modal redistribution and transient deformation properties. The proposed method is compared with the conventional lower-order integration schemes, and it is observed that the method gives better phase fidelity and computational efficiency, and it is possible to predict the vibration amplitude and vibration timing accurately. In addition to the numerical benefits, the framework also provided physical insights on the coupled effect of anisotropy, foundation interaction and boundary restraint. The suggested model is directly applicable for composite floor systems, aerospace panels, foundation supported slabs, biomechanical plate analogs, etc., and smart vibration control platforms. This work thus lays the groundwork for future studies of nonlinear behavior, adaptive foundations and digital twin simulation of structural systems and presents a strong and scalable computational tool for the study of plate–foundation dynamics. Full article

Achieving coordinated development between higher education and regional economies is central to sustainable urban growth. This study examines the spatiotemporal coupling coordination between higher education and economic development across 90 cities within seven major coastal urban agglomerations in China over the period 2008–2021. An evaluation index system was constructed across seven dimensions, and three analytical methods were integrated: the entropy weight method for composite index calculation, the coupling coordination degree model for assessing synergistic development, and the panel vector autoregression (PVAR) model for dynamic interaction analysis. A fixed-effects regression model was further applied to identify key driving factors. The results indicate that: (1) higher education levels showed a steady upward trend across all agglomerations, while widening absolute disparities persisted among cities; (2) although a bidirectional Granger-causal relationship exists between higher education and economic development, the interaction is asymmetric along two distinct dimensions: higher education exerts a more statistically robust predictive influence on the economy, while unforecast economic shocks transmit more strongly to higher education than the reverse; this asymmetry manifests in specific urban agglomerations—most notably the Pearl River Delta—as a structural mismatch between economic strength and higher education development; (3) economic development level, government fiscal support, urbanization, and higher education scale are significantly associated with the coupling coordination between the two systems. These findings highlight the structural misalignment between higher education supply and regional economic demand and underscore the need for differentiated, spatially targeted policy interventions to promote sustainable regional development. Policy recommendations are proposed for optimizing higher-education resource allocation, reforming talent cultivation, and strengthening intra-agglomeration coordination mechanisms. Full article

Sustainable air-quality governance requires not only local emission reduction but also a shift from single-pollutant control to coordinated PM_2.5–O₃ control, and from city-bounded management to regional governance under spatial spillovers. Based on balanced annual city-level panel data for the “2 + 26” urban agglomeration in the Beijing–Tianjin–Hebei region and surrounding areas from 2013 to 2020, this paper uses the dynamic Spatial Durbin Model (SDM) to analyze the spatial spillover effect of PM_2.5 and O₃ pollution and the effect of regional governance policies. The results show that both PM_2.5 and O₃ exhibit significant spatial autocorrelation and cross-city dependence, indicating that isolated local control measures are insufficient for sustainable air pollution prevention and that city-bounded governance cannot fully address regionally connected pollution risks. Economic output and secondary-industry employment remain important structural factors of pollution. The policy-text analysis shows that measures centered on coal-related control and industrial governance were more directly aligned with PM_2.5 reduction, whereas O₃-related governance lagged, suggesting that single-pollutant-oriented control may generate a sustainability trade-off when PM_2.5 reduction is not accompanied by coordinated O₃ control. These findings highlight two sustainability challenges in China’s regional air-quality governance: first, single-pollutant control can improve particulate pollution but may not ensure sustainable air-quality improvement when O₃ and its precursors are insufficiently addressed; second, isolated city-level governance may be insufficient when pollution outcomes exhibit significant spatial dependence across administrative boundaries. The study provides empirical evidence for sustainable air-quality governance by emphasizing differentiated PM_2.5 and O₃ responses, coordinated PM_2.5–O₃ control, regional governance beyond individual city boundaries, and the integration of spatial spillover assessment into regional environmental policy design. Full article

Industrial land bias is a persistent outcome of China’s land allocation system, but why its efficiency penalty differs across cities remains insufficiently explained. This study examines this unevenness by linking land allocation, population density, and city type heterogeneity within a unified framework. Using panel data for 281 prefecture-level and above cities in China from 2010 to 2022, we combine two-way fixed effects estimation with robustness checks, dynamic panel analysis, transmission channel tests, subsample comparison, and interaction models. Results show that industrial land bias significantly reduces urban land economic efficiency, with the strongest penalty after a one-year lag. Population density is an important spatial transmission channel: industrial land bias lowers density mainly by expanding built-up land faster than population concentration. The penalty is the largest in border cities, smaller in coastal cities, and statistically insignificant in general cities. The negative effect weakens as the secondary industry share increases, suggesting that local production capacity helps absorb industrial land expansion. The contribution of this study is to explain why the same industrial land bias generates uneven efficiency penalties across coastal, general, and border cities, providing evidence for place-sensitive land supply policies. Full article

As extreme weather events increasingly threaten global food systems, accurately assessing climate risks and predicting regional crop yields remains a critical challenge. Conventional prediction models often rely on direct weather-to-yield relationships, bypassing continuous crop physiological responses and limiting their capacity to capture fine-grained temporal impacts of meteorological anomalies. To address this, we propose a novel two-stage spatiotemporal functional framework that integrates high-resolution daily weather trajectories with satellite-derived indicators, utilizing the Enhanced Vegetation Index (EVI) and Land Surface Water Index (LSWI) to represent canopy structural vigor and hydraulic status, respectively. In the first stage, a Historical Functional Linear Model (HFLM) dynamically maps daily meteorological trajectories (temperature, precipitation, and solar radiation) onto continuous physiological curves under strict temporal causality constraints. This generates bivariate coefficient surfaces that reveal dynamic windows of vulnerability and capture divergent, lagged physiological responses to climate stress. In the second stage, a spatially heterogeneous functional additive model integrates these weather-shaped physiological trajectories alongside raw meteorological dynamics as joint predictors for county-level yields. By extracting functional principal components and modeling flexible non-linear biological responses while accounting for continuous spatial heterogeneity, this dual-channel frameworkcaptures key aspects of both chronic physiological stress and acute meteorological shocks. Validated across a 25-year (2000–2024) U.S. Corn Belt panel, the proposed DC-FAM achieves a mean weighted mean squared prediction error (WMSPE) of 242.33 (bu/acre)² and a median out-of-sample $R_{\mathrm{cv}}^2$ of 0.422, outperforming all benchmarks including a random forest. Attribution of the 2012 flash drought further demonstrates the framework’s capacity to mechanistically trace the complete disaster propagation chain from anomalous spring warming to mid-summer hydraulic failure. The proposed framework provides a transparent, biophysically grounded tool for decoding dynamic climate stress trajectories and disaster propagation chains, offering potential implications for adaptive farm management and precision agricultural insurance. Full article

Against the backdrop of China’s strategic goals of achieving carbon peaking and carbon neutrality, a key question is whether renewable electricity generation (REG) is associated with lower carbon emission intensity (CEI). To address this issue, this study employs panel data from 30 Chinese provinces from 2005 to 2024 and combines the Tapio decoupling model, Moran’s I test, and the spatial Durbin model (SDM), with the ordinary least squares (OLS) used as a benchmark to analyze the decoupling evolution, spatial spillover associations, and potential transmission channels between REG and CEI. The findings show that: (1) the relationship between REG and CEI evolves from weak decoupling to strong decoupling, suggesting a potentially nonlinear relationship; (2) CEI exhibits significant spatial autocorrelation and regional clustering; (3) REG is significantly associated with lower CEI, with both local and spatial spillover associations; (4) the local mitigation association is stronger in eastern and higher-CEI provinces, while spillover effects are more pronounced in western, northeastern, and resource-based provinces; and (5) the REG-CEI association may operate through energy structure (ES) optimization and energy intensity (EI) reduction, while environmental regulation (ER) may strengthen this association. The endogeneity tests provide supplementary evidence consistent with these findings, although they should not be interpreted as definitive causal proof. Overall, this study contributes to the sustainability literature by showing that the REG-CEI relationship is not merely a static local association, but a dynamic and spatially differentiated pattern shaped by regional coordination and energy-system adjustment. These findings provide evidence relevant to sustainability-oriented energy policy by suggesting that renewable electricity development should be assessed not only by generation scale, but also by its association with carbon-intensity reduction, spatial coordination, and energy-system efficiency. Full article

Against the backdrop of widening regional disparities and the rapid expansion of digital connectivity, understanding the relationship between new quality productive forces (NQPF) and urban–rural integration requires a systemic and network-based perspective. This study approaches urban–rural integration from a complex adaptive system perspective embedded in dynamic interregional networks. Using panel data from 31 Chinese provinces from 2014 to 2024, we construct composite indices for NQPF and urban–rural integration and combine two-way fixed-effects models, static Spatial Durbin Models (SDM), and dynamic-network two-way fixed-effects spatial-lag specifications. This framework helps examine local associations, network-based spillover patterns, and heterogeneous system responses. The results show that: (1) urban–rural integration exhibits significant spatial clustering, with Moran’s I becoming positive and statistically significant after 2016, reflecting persistent structural imbalances within the regional system; (2) the static SDM results show that NQPF is positively associated with urban–rural integration both locally and through spatial indirect linkages; (3) compared with conventional static geographic matrices, the dynamic network-based spatial weights provide additional information on evolving interregional linkages shaped by economic proximity, digital capability similarity, and factor mobility; and (4) under the dynamic network-based specification, NQPF remains positively associated with network exposure in connected provinces, with heterogeneous patterns across regions. More stable local associations are observed in high-connectivity and eastern regions, while the low-connectivity group and central–western regions appear to benefit more from network-based linkages. These findings suggest that the relationship between NQPF and urban–rural integration is embedded in a spatially connected and network-conditioned regional system. By integrating spatial econometrics with a complex systems perspective, this study provides a complementary framework for understanding regional transformation in the digital era. Full article

Extreme climate events have emerged as a critical threat to the economic resilience and environmental sustainability of urban systems. As a central pillar of the low-carbon transition, improvements in carbon emission efficiency (CEE) are increasingly recognized as a potential pathway to mitigate the occurrence and intensity of such events. Drawing on a balanced panel dataset of 163 cities from 2006 to 2022, this study integrates an Extreme Gradient Boosting (XGBoost) model augmented with SHAP (Shapley Additive Explanations) analysis and a Geographically and Temporally Weighted Regression (GTWR) framework to examine the nonlinear and spatially heterogeneous effects of CEE on the Climate Physical Risk Index (CPRI). The results reveal a distinct two-stage dynamic pattern, in which CEE initially exacerbates and subsequently mitigates climate risk, indicating a nonlinear transition from short-term intensification to long-term alleviation. This relationship shows clear differences across city levels and climate types. The strongest effects appear in peripheral cities and in areas with extreme rainfall dominance (ERD). Spatial analysis based on GTWR also shows a clear north–south pattern. The effect of CEE in reducing risk becomes stronger from the south to the north. Based on these results, the study suggests different land-use policy strategies for different city types and climate conditions. The results give actionable insights for designing targeted carbon governance policies. These policies aim to deal with the growing challenges caused by extreme climate events under ongoing climate change. Full article

The article presents the results of an empirical study of the localisation processes of the Sustainable Development Goals (SDGs) in 102 regions of Russia and Kazakhstan for the period 2015–2024. Based on the author’s methodology for constructing the SDG Localisation Index (SDGLI) using the method of the main components, a quantitative assessment of regional progress was carried out according to 14 SDGs. Cluster analysis has identified four sustainable types of regions that differ in the structure and dynamics of sustainable development. Using eco-metric tools (panel regressions with fixed effects, spatial models, difference-in-differences method), key factors of interregional differentiation were identified, including economic, social, institutional and spatial determinants. Particular attention is paid to assessing the effect of adopting regional sustainable development strategies. A decomposition of interregional inequality was carried out, which made it possible to quantify the contribution of various groups of factors. The results of the study contribute to the theory of regional economics and can be used to improve regional policies in the field of sustainable development. Full article

In this study, the influence of thermal loading in a supersonic flight environment on the mechanical stiffness of elastic structures and the corresponding aeroelastic stability limits is investigated analytically. Recognizing that elevated temperatures inherently alter constituent elastic properties, a temperature-dependent continuous elasticity framework is incorporated directly into the governing differential operators of the structural domain. The macro-mechanical behavior of representative panel- and wing-type elements is modeled utilizing the Euler–Bernoulli beam formulation, while high-speed supersonic aerodynamic effects are represented through linearized first-order piston theory. The continuous spatial displacement fields are discretized by means of a modal expansion, and the coupled aeroelastic system is subsequently transformed into a finite set of dynamic state-space equations using the Ritz–Galerkin truncation method. The numerical and analytical outputs demonstrate that aerothermal softening not only induces continuous erosion in the material stiffness but also directly modulates the aeroelastic pole trajectories, thereby prematurely contracting the safe supersonic flight envelope. The primary novelty of the proposed framework lies in the derivation of explicit analytical expressions that directly map temperature-dependent stiffness variations onto supersonic aeroelastic instability boundaries. Because this approach is formulated in a generalized analytical form, it can be applied across diverse material systems, geometric profiles, and thermal conditions with reduced computational overhead compared to full fluid–structure interaction solvers, thereby providing a theoretical basis for preliminary stability assessment of supersonic aerospace configurations operating under high-temperature conditions. Full article