Search Results (1,213)

Amid global population growth and the pressures of climate change, traditional factors in driving grain production are increasingly inadequate. In this context, this study utilizes panel data from 31 provinces in China (2001–2022) to examine the impact of digitalization (DG), technological innovation (TI), and financial innovation (FI) on grain production (GP). Specifically, the study constructs a comprehensive evaluation framework where DG is measured by mobile communication penetration, TI by agricultural R&D expenditure, and FI by the loan-to-GDP ratio of financial institutions. Employing a fixed effects model, the empirical results demonstrate that DG, TI, and FI yield significant positive returns on GP, with elasticity coefficients of 0.262, 10.675 and 6.589, respectively. Furthermore, synergistic effects are observed, where the interaction between DG and TI (coefficient 0.0402 × 10⁻³) and between DG and FI (coefficient 0.221 × 10⁻²) significantly amplify production capacity. Channel analysis reveals that DG and TI promote GP by fostering agricultural industrial agglomeration, TI and FI by advancing agricultural mechanization, and DG and FI by expanding the agricultural insurance scale. Heterogeneity analysis indicates that these factors significantly boost GP in major grain-producing regions but are insignificant in grain production–marketing balanced regions. In major grain-consuming regions, DG has an adverse effect, TI has no significant impact, and FI has a positive effect. Additionally, in non-humid regions, the positive impacts of DG, TI, and FI on GP are greater. Full article

A major obstacle to sustainable land management in ecologically sensitive areas is our limited understanding of the complex nonlinear mechanisms and threshold effects that dictate trade-offs between land use functions (LUFs). This study takes the Funiu Mountain area, a typical ecologically sensitive area in China, as a case study. At the township scale, the spatiotemporal patterns of LUFs from 2000 to 2020 were assessed based on the “production-living-ecological” function framework. The root mean square error (RMSE) model was introduced to quantify inter-functional trade-off intensity. Furthermore, the optimal parameters geographical detector (OPGD) and generalized additive model (GAM) were innovatively coupled to systematically analyze their driving mechanisms and nonlinear threshold effects. The results indicate that: (1) LUFs show clear functional complementarity and spatial game characteristics. The production function (PF) exhibits a heterogeneous pattern of “locally high, overall low”; the living function (LF) shows a local central agglomeration feature; and the ecological function (EF) displays a continuous gradient distribution of “high in the northwest, low in the southeast”. (2) The trade-off intensities between PF&EF and LF&EF are relatively strong, with high-value areas mainly distributed in the high-altitude central regions; while the trade-off intensity of PF&LF is weaker, with high-value areas mostly appearing in the central urban areas of each county. (3) The spatial heterogeneity of the trade-off relationship of LUFs is a comprehensive manifestation of the combined effects of the natural environment, socio-economic factors, and landscape patterns. The driving mechanisms of trade-off intensity among different functions show significant heterogeneity. (4) Key driving factors have significant nonlinear threshold effects. POP shows a complex dynamic regulatory effect with multiple thresholds and strong nonlinearity, while SLOPE, PET, and NDVI continuously play a fundamental constraining role in the trade-offs related to ecological functions. The key thresholds identified in this study can provide a direct scientific basis for regional differentiated territorial space governance. Full article

The security and stability of energy are vital to the national economy and people’s well-being. At present, the global energy industry is undergoing a profound historical transformation. Exploring effective strategies to bolster the resilience of the energy industry supply chain and ensure its sustainable development represents a pivotal approach to achieving energy security and stability. Based on panel data from 30 provinces in China from 2013 to 2023, this study constructs an indicator system for new quality productivity forces and the resilience of the energy industry supply chain, applies the entropy weight method for indicator weighting, and employs an improved E–G index algorithm to measure the industrial agglomeration index. The influence of new quality productivity forces on the resilience of the energy industry supply chain is examined through a two-way fixed-effects model. The research findings demonstrate that new quality productivity significantly enhances the resilience of the energy industry supply chain. The level of energy supply exhibits a moderating effect, positively facilitating the enhancement of supply chain resilience through new quality productivity. The levels of urbanization, development, and industrial collaborative agglomeration demonstrate a threshold effect, leading to a nonlinear impact of new quality productivity on the resilience of the energy industry supply chain. Our heterogeneity tests reveal that in central r–ions and regions with higher levels of informatization, the promoting effect of new quality productivity on the resilience of the energy industry supply chain is more pronounced. This study further clarifies the mechanism through which new quality productivity influences the resilience of the energy industry supply chain, enriches and expands the understanding of the role of new quality productivity in the energy industry, and provides crucial support for governments and enterprises in making decisions aimed at enhancing the resilience of the energy industry supply chain. Full article

The high brand premium of geographical indication (GI) tea has not been efficiently converted into widespread economic benefits through its supply chain. The current performance evaluation system is confronted with a dual predicament: first, the strong external environment (such as policy support and industrial agglomeration) interference is hard to isolate, making it impossible to distinguish between “environmental advantages” and “true management levels”; second, the general agricultural indicators fail to capture the output essence of GIs centered on “brand value”. Therefore, this study constructs an evaluation framework integrating methodological and indicator innovations. Methodologically, a three-stage DEA model is adopted to eliminate the influence of exogenous environments and random noises, precisely measuring the “pure management efficiency” of the supply chain. Indicatively, common variables are abandoned, and a customized system is established with logistics facilities, production area, and regional digital investment as inputs, and brand reputation, value, and income as outputs. Based on the panel data of twelve representative tea GIs from 2021 to 2024, the study finds that the following: (1) The “pure management efficiency” of the supply chain is the key factor influencing performance evaluation. (2) “Diseconomies of scale” are the main structural bottleneck restricting performance improvement rather than technological backwardness. (3) Solving the above-mentioned management efficiency problems, especially resolving “diseconomies of scale”, is the micro foundation for achieving sustainable industrial development. This research not only provides methodological support and empirical evidence for the refined management and sustainable development of the geographical indication agricultural product supply chain, but also has significant practical significance for promoting the quality and efficiency improvement of the tea industry and facilitating the sustainable development of related agriculture. Full article

This paper proposes a valorization approach for solid lavender residue, a by-product of the essential oil industry. The biomass residue was carbonized at atmospheric pressure and two temperatures (450 °C and 650 °C), followed by solvothermal modification with zinc ions (Zn²⁺, 3 and 5 mmol). The effects of temperature and Zn²⁺ incorporation on the elemental composition and morphology of the resulting biochar were examined using X-ray Fluorescence (XRF), Fourier Transform Infrared (FTIR) spectroscopy, and Scanning Electron Microscopy/Energy-Dispersive X-ray Spectroscopy (SEM/EDS) analyses. The applied Zn²⁺ modification was effective at both concentrations for the biochar obtained at both carbonization temperatures. However, a more uniform metal ion distribution was observed at 3 mmol, while at 5 mmol, a partial particle agglomeration occurred. Progressive degradation of the O–H, C=O, and C–O groups with increasing temperature and the presence of Zn–O-related interactions was observed. The results demonstrated consistent and reproducible trends, suggesting that controlled carbonization combined with Zn²⁺ incorporation can convert lavender residues into modified carbonaceous materials. Full article

Gross Domestic Product (GDP) serves as a core indicator for measuring the sustainable economic development of countries and regions. Accurate understanding of its spatio-temporal distribution is crucial for achieving the United Nations Sustainable Development Goals (SDGs). However, current grid-based GDP data for China’s regions predominantly consists of data from specific years, making it difficult to capture fine-grained changes in economic development. To address this, this study proposes a spatial GDP framework integrating cross-scale feature extraction (CSFs) with stacked ensemble learning. Based on China’s county-level GDP statistics and multi-source auxiliary data, it first generates a density-weighted estimation layer. This is then processed through dasymetric mapping to produce China’s Annual High-Resolution Gridded GDP Dataset (CA_GDP) from 2000 to 2021. Evaluation demonstrates the framework’s superior performance in density weight estimation, achieving an R² of 0.82 against statistical data. Compared to traditional single models like Random Forests (RF), it improves R² by 13–54%, reduces mean absolute error (MAE) by 2–26%, and lowers root mean square error (RMSE) by 19–39%, with these advantages remaining stable across time series. The dasymetric mapping of the CA_GDP dataset clearly depicts the economic development patterns and urban agglomeration effects in the southeastern coastal regions, as well as the relatively lagging economic development in western areas. Compared to existing public datasets, CA_GDP offers significant advantages in reflecting the fine-grained economic spatial structure within county-level units, providing a more reliable data foundation for identifying regional economic disparities, policy formulation and evaluation, and related research. Full article

In response to the requirements for groundwater pollution risk identification and zoning-based management in typical coastal industrial agglomeration areas, this study takes the coastal industrial zone of the Jidong Plain as the research area and. It develops an integrated evaluation framework for groundwater pollution prevention zoning. The framework is quantitatively centered on pollution source load assessment and groundwater vulnerability analysis, and applies the Analytic Hierarchy Process (AHP) solely as an interpretative and decision-support tool. In this study, the Linear Weighted Function (LWF) method and the DRASTIC model are employed to quantitatively characterize pollution source load intensity (PI) and groundwater system vulnerability (DI), respectively. By constructing a prevention and control index (R) in the form of the product of pollution source load and groundwater vulnerability, the framework achieves an integrated representation of pollution input intensity and the carrying capacity of the groundwater system. The AHP is not directly involved in indicator weighting or zoning calculations; instead, it is applied as a post hoc analytical approach to identify the relative importance of different evaluation factors in groundwater pollution prevention zoning, thereby supporting the interpretation of the zoning results and management priority setting. The results indicate that the overall pollution source load in the study area is relatively low, with low-to-moderately low load zones accounting for 68.7% of the area. In comparison, high-load zones account for only 1.43% and are mainly concentrated in the southeastern coastal industrial belt. Shallow groundwater generally exhibits high vulnerability, with highly vulnerable zones covering 86.56% of the area and predominantly distributed in the northeastern Quaternary unconsolidated sedimentary regions. Based on the prevention and control index (R), the study area is classified into prevention zones and remediation zones. Prevention zones account for 94.47% of the total area, whereas remediation zones account for 5.53%. High-risk areas are mainly concentrated in coastal industrial belts and highly vulnerable cultivated areas. The results demonstrate that the proposed integrated evaluation framework effectively couples pollution source load and groundwater vulnerability, and, on the basis of the finalized zoning results, enhances the interpretability and management specificity of the zoning outcomes through post hoc decision-support analysis, thereby providing a scientific basis and methodological reference for groundwater pollution prevention zoning and differentiated management in coastal industrial regions. Full article

Refuse-derived fuel (RDF) presents a viable strategy to concurrently address the challenges of municipal solid waste management and the need for alternative energy. In this context, the present review systematically synthesizes recent advances in RDF preparation, combustion behavior, and efficient utilization technologies. The study examines the full chain of RDF production—including waste selection, mechanical/optical/magnetic sorting, granulation, briquetting, and chemical modification—highlighting how pretreatment technologies influence fuel homogeneity, calorific value, and emissions. The thermochemical conversion characteristics of RDF are systematically analyzed, covering the mechanism differences among slow pyrolysis, fast pyrolysis, flash pyrolysis, pyrolysis mechanisms, catalytic pyrolysis, fragmentation behavior, volatile release patterns, and kinetic modeling using Arrhenius and model-free isoconversional methods (e.g., FWO). Special attention is given to co-firing and high-efficiency combustion technologies, including ultra-supercritical boilers, circulating fluidized beds, and rotary kilns, where fuel quality, ash fusion behavior, slagging, bed agglomeration, and particulate emissions determine operational compatibility. Integrating recent findings, this review identifies the key technical bottlenecks—feedstock variability, chlorine/sulfur release, heavy-metal contaminants, ash-related issues, and the need for standardized RDF quality control. Emerging solutions such as AI-assisted sorting, catalytic upgrading, optimized co-firing strategies, and advanced thermal conversion systems (oxy-fuel, chemical looping, supercritical steam cycles) are discussed within the broader context of carbon reduction and circular economy transitions. Overall, RDF represents a scalable, flexible, and high-value waste-to-energy pathway, and the review provides insights into future research directions, system optimization, and policy frameworks required to support its industrial deployment. Full article

Urban agglomerations are concentrated production areas of new-quality productivity (NQP), and developing NQP is an inevitable requirement and obligation to promote the high-quality development of urban agglomerations. It is of great concern whether green finance (GF) can serve as a catalyst in promoting the formation and development of NQP in urban agglomerations. This study selects panel data from 41 cities in the Yangtze River Delta urban agglomeration spanning 2011–2023 to construct a comprehensive indicator system for NQP based on the composition, quality, and function of productive factors in the urban agglomeration, and explores the impact effects, mechanisms of action, spatial spillover effects, and heterogeneity of GF on the development of NQP using a two-way fixed-effects model, an intermediary effect model, and a spatial Durbin model (SDM). The empirical results indicate the following: (1) GF can significantly promote the development of NQP in the Yangtze River Delta urban agglomeration, and there is a significant positive spatial spillover effect. The above conclusions remain valid after a series of robustness tests and endogeneity treatments. (2) The mechanism tests find that industrial structure upgrading and environmental regulation play positive mediating roles in GF’s promotion of NQP development in urban agglomerations. (3) The impact of GF on NQP exhibits significant heterogeneity. In regions with higher levels of economic and financial development, as well as a higher degree of marketization, the promotional effect of GF on NQP is more pronounced. In terms of city size and geographical location, the empowering effect and spatial spillover effect of GF on NQP are more evident in prefecture-level cities and the northern plain area of the Yangtze River Delta. Therefore, it is recommended to implement differentiated GF policies to promote the development of NQP in the Yangtze River Delta urban agglomeration through regional cooperation, green technology innovation, industrial transformation and upgrading, and environmental regulation. Full article

In response to growing interest in green additives derived from natural raw materials or post-production waste of natural origin, epoxy compositions containing the additive in the form of waste wood flour and microcellulose were prepared. The research involved the chemical modification of the additive through a two-stage silanization process using 3-aminopropyltriethoxysilane. Followed by filler’s characterization using Fourier Transformed Infrared Spectroscopy (FT-IR) to analyze the modification in chemical structure, Wide Angle X-Ray Diffraction (WAXD) to detect differences in crystal structure, and Scanning Electron Microscopy (SEM) to observe morphological changes. Next, waste oak flour (WF) and microcrystalline cellulose (MCC) were used in unmodified and silanized form (sil-WF and sil-MCC, respectively) to prepare epoxy composites, followed by testing their influence on the mechanical (hardness, tensile strength, flexural strength, compressive strength, and impact strength), thermal, and morphological characteristics of epoxy composites based on Epidian 6. Comparing the effect of modification on the properties of the analyzed additives, it was found that silanization had a larger impact on increasing the interaction of the waste wood flour with the epoxy matrix than silanization of MCC due to a lesser tendency of the sil-WF than the sil-MCC to agglomerate. An enhanced interaction of sil-WF with the polymer resulted in improved mechanical properties. Composite EP/sil-WF (cured epoxy composite based on low-molecular-weight epoxy resin Epidian 6 filled with 5 wt.% of silanized wood flour) was characterized by improved flexural (61.97 MPa) and compressive properties (69.1 MPa) compared to both EP/WF (cured epoxy composite based on low-molecular-weight epoxy resin Epidian 6 filled with 5 wt.% of unmodified wood flour) (42.39 MPa and 61.0 MPa) and the unfilled reference composition (54.55 MPa and 67.4 MPa, respectively). Moreover, compositions containing a cellulosic additive were characterized by better impact properties than the reference composition. Full article

China is the world’s leading producer of offshore mariculture, contributing more than 60 percent of global output. Yet the provincial distribution of mariculture space and its economic concentration are still not well described at a comparable national scale. This study draws on a publicly available nation-scale GIS dataset extracted from Landsat 8 imagery from 2018 to map offshore mariculture across nine coastal provinces and to quantify spatial inequality and specialization. The mapped offshore mariculture footprint totals 733,840 ha. The distribution is sharply uneven. Fujian alone reaches 183,025 ha, nearly thirty times the area of Hainan. The Gini coefficient is 0.412, and concentration ratios show that the top three provinces account for 64.0 percent of the total area, and the top five account for 84.5 percent. Location quotient results indicate strong specialization in Fujian, Jiangsu, and Hebei, while Hainan and Guangxi remain marginal. Cluster analysis further identifies three development modes: large-scale expansion, medium-scale and relatively balanced growth, and small-scale dispersed production. Overall, the pattern is consistent with resource endowment, agglomeration effects, and path dependence. The findings point to the need for improved coastal spatial planning, stronger interprovincial technology diffusion, and differentiated governance that balances efficiency with equity and environmental sustainability. Full article

Against the backdrop of rapid modernization and tightening agricultural resource constraints, coordinating urbanization and grain production is a key challenge for China. Using panel data from 30 Chinese provinces from 2004 to 2023, this study applies the coupling coordination degree (CCD) model and a panel vector autoregression model to examine the spatiotemporal coupling characteristics and interaction mechanisms among new-type urbanization (NTU), cultivated land use efficiency (CLUE), and food security (FS). The results show that these three systems have gradually evolved toward coordinated development, with major grain-producing regions consistently leading and entering a moderate coordination stage earlier than other regions. Spatially, CCD exhibits significant positive spatial autocorrelation, characterized by stable “High–High” agglomeration in Northeast China and “Low–Low” agglomeration in southern provinces. Dynamic analysis indicates that system fluctuations are mainly driven by internal inertia, while inter-system interactions are also significant; NTU promotes CLUE, and CLUE and FS exhibit bidirectional causality with complex feedback effects. This study argues for promoting urban–rural factor mobility, advancing green and technology-enabled land use, implementing region-specific development strategies, and establishing a “human–land–grain” early-warning mechanism to safeguard food security during urban expansion. Full article

Green total factor productivity (GTFP), as an important indicator considering both economic development and environmental protection, has prompted countries around the world to actively explore ways to improve it in the context of the global transition to a green economy. The Low-Carbon City Policy (LCCP) implemented by the Chinese government, along with the National Big Data Comprehensive Pilot Zone Policy (NBDCPZ), which serve as key carriers of green regulation and digital innovation, respectively, play an important role in improving green total factor productivity (GTFP) and achieving high-quality economic development. This study aims to deeply explore whether there is a collaborative enabling effect of the Low-Carbon City Policy (LCCP) and the National Big Data Comprehensive Pilot Zone Policy (NBDCPZ) on green total factor productivity (GTFP) and to reveal the internal mechanism by which they improve GTFP through green technological innovation and industrial agglomeration. Specifically, based on the panel data of 269 prefecture-level cities in China from 2006 to 2022, a “dual-pilot” policy is constructed through LCCP and NBDCPZ, and a multi-period difference-in-differences model (DID) is used to evaluate the collaborative effect of the “dual-pilot” policy on GTFP. The results show that the “dual-pilot” policy has a significant collaborative effect on green total factor productivity (GTFP), and its enabling effect is more obvious than that of the “single-pilot” policy. These conclusions still hold after a series of endogeneity and robustness tests. Mechanism analysis shows that the “dual-pilot” policy can also improve green total factor productivity (GTFP) through green technological innovation and industrial agglomeration. Heterogeneity analysis reveals that the collaborative enabling effect of the “dual-pilot” policy is influenced by geographical location and population density. Specifically, the “dual-pilot” policy significantly promotes green total factor productivity (GTFP) in coastal cities and those with high population density. These research results provide a scientific basis for formulating green development policies in China and other countries, as well as a direction for subsequent research on the collaborative enabling effect of multiple policies. Full article

Promoting the value realization of ecological products is a central issue in practicing the concept that “lucid waters and lush mountains are invaluable assets.” This is particularly urgent for alpine regions, which are vital ecological security barriers but face stringent developmental constraints. This study takes Golog Tibetan Autonomous Prefecture in Qinghai Province as a case study. It establishes a Gross Ecosystem Product (GEP) accounting framework tailored to the characteristics of alpine ecosystems and conducts continuous empirical accounting for the period 2020–2023. The findings reveal that: (i) The total GEP of Golog is immense (reaching 655.586 billion yuan in 2023) but exhibits significant dynamic non-stationarity driven by climatic fluctuations, with a coefficient of variation as high as 11.48%. (ii) The value structure of the GEP is highly unbalanced, with regulatory services contributing over 97.6%. Water conservation and biodiversity protection are the two pillars, highlighting its role as a supplier of public ecological products and the predicament of market failure. (iii) The spatial distribution of GEP is highly heterogeneous. Maduo County, comprising 34% of the prefecture’s land area, contributes 48% of its total GEP, with its value per unit area being 1.68 times that of Gande County, revealing the spatial agglomeration of key ecosystem services. To address the dynamic, structural, and spatial constraints identified by these quantitative features, this paper proposes synergistic realization pathways centered on “monetizing regulatory services,” “precision policy regulation,” and “capacity and institution building”. The aim is to overcome the systemic bottlenecks—“difficulties in measurement, trading, coarse compensation, and weak incentives”—in alpine ecological functional zones. This provides a systematic theoretical and practical solution for fostering a virtuous cycle between ecological conservation and regional sustainable development. Full article

Y-branched TiO₂ nanotubes (NTs) were produced by anodizing titanium plates derived from aerospace production leftovers and subsequently engineered to develop an enhanced TiO₂-based photocatalytic system. The NTs were electrochemically reduced to obtain reduced TiO₂ nanotubes (rTN) with a narrowed bandgap, followed by surface modification with polydopamine (PD) and silk fibroin-derived quantum dots (QDs) to promote enhanced UV and visible-light photocatalysis for wastewater treatment. The QDs were hydrothermally synthesized from Bombyx mori silk fibroin. Scanning Electron Microscopy (SEM) revealed spherical QD agglomerates encapsulated within the PD layer, while Energy Dispersive X-ray Spectroscopy (EDX) confirmed the presence of carbon and nitrogen originating from both PD and QD. The resulting rNT/PD/QD photocatalyst exhibited a significantly reduced bandgap (1.03 eV), increased Urbach energy (1.35 eV), and moderate hydrophilicity. A high double-layer capacitance (C_dl) indicated an enlarged electrochemically active surface due to the combination of treatments. Electrochemical characterization demonstrated reduced electrical resistance, higher charge density, and lower electron–hole recombination, leading to improved interfacial charge transfer efficiency and electrochemical stability during multi-cycle cyclic voltammetry measurements. Preliminary photocatalytic tests show that the rNT/PD/QD photocatalyst achieved a degradation efficiency of 79.26% for methyl orange (MO) and 35% for tetracycline (TC). Full article