Search Results (332)

This study is based on the data from co-authored papers, collaborative patents, and jointly authored varieties involving Chinese agricultural enterprises, universities, and research institutions from 2011 to 2023. We construct a three-dimensional dynamic equation system to model the agricultural industry–university–research (I-U-R) collaborative innovation network operation mechanism. Inspired by the Belousov–Zhabotinsky (B-Z) reaction, we model a three-variable oscillator with the state variables (network structure embeddedness, partner heterogeneity, and collaborative innovation output) to represent three primary substances in the chemical oscillators. This study investigates the network’s operational patterns and its determinants. Findings reveal that the patent network operates more efficiently than the paper and variety networks. Dependence on external government support increases with innovation complexity, coordination difficulty, and social value. Although a “structural optimization–resource agglomeration–output explosion” state is theoretically attainable under threshold conditions, the observed reality reflects “marginal structural optimization–continuous resource depletion–zero output growth”. Among the entities, eighteen are active leaders, forty-two constitute a stable but low-dynamism backbone, and ninety are general participants with limited innovation capacity. Significant structural contradictions highlight the need for targeted policy interventions to guide the network toward a more advanced and orderly state. Full article

Climate volatility and market uncertainty pose significant challenges to agricultural stability. We assess whether and how agricultural industrial agglomeration shapes China’s agricultural economic resilience using province-level panel data for 2003–2023 and a transparent, entropy-weighted index spanning resistance, recovery, and adaptability. Four results stand out. First, in a two-way fixed-effects model, agglomeration is associated with higher resilience on average, and this finding remains robust across multiple robustness tests and after addressing endogeneity concerns. Second, regional subgroup analyses reveal pronounced heterogeneity, providing evidence for geographically targeted policy design. Third, mechanism analysis reveals that the agricultural research intensity serves as a partial mediator between agglomeration and resilience. Fourth, the agglomeration-resilience relationship is nonlinear—N-shaped in the aggregate, while panel quantile regressions reveal an inverted-U among low-resilience provinces and an N-shaped pattern at the median and upper end of the distribution. In an extension, global Moran’s I statistics for three alternative resilience indices reveal significant positive spatial autocorrelation, indicating that agricultural economic resilience tends to cluster geographically and that spatial spillovers are likely to be present. In conclusion, agglomeration is a net enhancer of agricultural economic resilience, but its payoffs are agglomeration- and distribution-dependent: gains taper or reverse around the mid-range for low-resilience provinces, while the median and upper segments benefit again as specialization deepens, in a setting where resilience itself is spatially clustered. Reinforcing the research channel and tailoring actions to local resilience levels are therefore pivotal. Full article

Against the backdrop of the rapid development of digital technologies, such as mobile internet, big data, and cloud computing, the geographical agglomeration of industries is gradually shifting toward virtual agglomeration. In this paper, we examine the effect of both geographical and virtual agglomeration of the agricultural industry on farmers’ agricultural income, and we focus on the transmission mechanism of technological innovation in this process. In the empirical section, using the citrus industry as an example, we employed a moderated mediation effect model for verification and derived the following conclusions: (1) Both geographical and virtual agglomeration of the agricultural industry promote an increase in farmers’ agricultural income by enhancing technological innovation, respectively. (2) Virtual agglomeration of the agricultural industry has a negative moderating effect on the relationship between geographical agglomeration and farmers’ agricultural income, that is, virtual agglomeration alleviates the “crowding effect” and to some extent substitutes for geographical agglomeration. (3) In the mechanism where geographical agglomeration in the agricultural industry increases farmers’ agricultural income through technological innovation, virtual agglomeration has a positive moderating effect. This paper is important for enabling farmers to share the benefits of the digital economy and achieve continuous growth in agricultural income. It is also important for the sustainable development goals adopted by the United Nations, such as eliminating poverty (SDG1), eliminating hunger (SDG2), promoting sustainable economic growth and full employment (SDG8), and promoting innovation (SDG9). Full article

This research explores the effects of milling on fecal sludge (FS) biochar with an emphasis on milling time (5, 10, and 15 min) and ball-to-powder ratio (BPR) (4.533 g/g, 9.067 g/g, and 10.5 g/g). FS biochar was prepared through slow co-pyrolysis of a 50:50 mixture (by weight) of fecal sludge and rice husk powder at 550 °C. The resultant FS biochar with good qualities was subjected to methylene blue (MB) dye adsorption at varying FS biochar weights (0.05 g, 0.1 g, and 0.15 g) and adsorption durations. The BSA peaked at 50 m²/g for a BPR of 10.5 g/g and a milling duration of 10 min. Prolonged milling (15 min) led to structural degradation and reduced BET surface area (BSA). The pore volume peaked at a BPR of 9.067 g/g for shorter milling times and 10.5 g/g for extended milling. The SEM revealed that a milling time of 10 min at a BPR of 9.067 g/g provided the best balance between particle size reduction and uniform morphology, minimizing agglomeration. MB adsorption revealed that FS biochar milled for 10 min and 9.067 g/g BPR demonstrated the best properties. These findings highlight the potential of FS biochar for applications in environmental remediation and agricultural fields, contributing to resource recovery from FS. Full article

The growing demand for sustainable materials has intensified research on biodegradable polymers, particularly poly(ε-caprolactone) (PCL), poly(lactic acid) (PLA), and their blends. PLA and PCL offer biocompatibility and biodegradability, making them attractive for biomedical, packaging, and agricultural applications; however, their practical utility remains limited owing to intrinsic drawbacks. PLA has low impact strength and poor thermal resistance, while PCL suffers from low tensile strength and slow degradation kinetics. Blending PLA with PCL can complement their properties, providing a tunable balance of stiffness and flexibility. Further improvements can be achieved through the incorporation of micro- and nanocellulose (NC), which act as reinforcements, nucleating agents, as well as compatibilizers. We critically examine fabrication strategies for NC-reinforced PLA, PCL, and their blends, highlighting NC extraction, surface modification, processing strategies, and dispersion techniques that prevent agglomeration and facilitate uniform distribution. Comparative insights into composite and nanocomposite systems reveal that NC incorporation significantly enhances mechanical properties, thermal resistance, crystallization, and biodegradation kinetics, particularly at low filler loadings, owing to its high surface area, specific strength, and hydrophilicity. The review underscores the potential of PLA/PCL-based nanocomposites as eco-friendly biomaterials with tunable properties tailored for diverse sustainable applications. Full article

Spatial mismatches between ecosystem services and human demands pose critical challenges for sustainable land use in ecologically fragile regions. Rapid urbanization intensifies land-use conflicts in ecologically fragile regions, threatening ecosystem services and habitat sustainability. This study addresses this challenge by quantifying spatial mismatches between landscape resource functions (LRFs: natural, traditional, and humanistic) and service demands (LSFs, e.g., catering and public facilities) in Xinxian County, in China’s Dabie Mountains, using multi-source data (DEM, POI big data, and remote sensing) and spatial analysis (nearest neighbor indices, kernel density, and multi-ring buffers). The results reveal that concentrated natural LRFs in high-elevation single-core clusters exhibit low dispersion, thus increasing vulnerability to land conversion, while agglomerated LSFs in urban cores exacerbate ecosystem service inequalities. Crucially, service deficits beyond 3 km buffers and the fragmentation of traditional agricultural zones indicate potential erosion of regulating services, as inferred from spatial mismatches (e.g., soil retention and water regulation), and cultural resilience. These spatial mismatches act as proxies for habitat risks, in which humanistic landscape expansion competes with ecological corridors, amplifying fragmentation. To mitigate risks, we propose (1) enhancing connectivity for natural resource corridors to stabilize regulating services, (2) reallocating LSFs to peri-urban buffers to reduce pressure on critical habitats, and (3) integrating ecosystem service trade-offs into landscape planning. This framework provides an actionable pathway for balancing development and habitat conservation in mountainous regions undergoing land-use transitions. Full article

The land use dynamics of urban, agricultural, and ecological spaces are critical factors influencing land surface temperature (LST); however, the existing methods for describing the spatial carriers of land surface temperature evolution face issues such as granularity effects and projection sensitivity, which hinder effective comparisons across different regions and categories, thus limiting the progress of current research. This study introduces a quadtree-based spatial framework to achieve unified measurements of scale and fragmentation across Urban–Agricultural–Ecological spaces, with an empirical analysis of the Middle Yangtze River Region. Results show that between 2000 and 2020, urban and agricultural spaces expanded while ecological spaces declined, with all three types becoming increasingly fragmented. Urban agglomeration and expansion significantly elevated LST; agricultural spaces exerted relatively limited effects; and ecological fragmentation generated localized cooling but weakened core regulatory functions, ultimately leading to warming within ecological spaces themselves. This study proposes a robust method for spatial identification and fragmentation quantification, revealing the dual role of scale and morphology in regulating regional thermal environments and underscoring the importance of balanced Urban–Agricultural–Ecological configurations for climate-adaptive land use planning. Full article

In order to study the differential characteristics of heavy metal contamination levels and their sources in soils under various land use types and anthropogenic activities at a regional scale, this study focused on the Beijing–Tianjin–Hebei (BTH) urban agglomeration in North China. We analyzed heavy metal content in three land use types (urban green spaces, croplands, and vegetable fields/orchards) through field sampling and laboratory analysis, with content determined by inductively coupled plasma mass spectrometry (ICP-MS). The sources of heavy metals were quantitatively apportioned their sources using the absolute principal component score–multiple linear regression (APCS-MLR) method. Results of this study are as follows: (1) Heavy metal content varied among different soil types, with vegetable fields/orchards soils showing relatively higher content. Urban green spaces and cropland soils exhibited comparable heavy metal levels, though urban green spaces displayed higher spatial heterogeneity, while cropland soils showed more homogeneous distributions. (2) The APCS-MLR model identified five pollution sources: mixed traffic–coal combustion sources, industrial sources, agricultural sources, natural sources, and unknown sources. Natural sources were consistently the dominant contributors of arsenic (As), chromium (Cr), and nickel (Ni) across all three land use types, with contribution rates of 32.62–70.26%. Traffic and coal combustion emissions were the primary sources of lead (Pb) and copper (Cu) in urban green spaces, accounting for 40.28–66.26%, while industrial activities showed the highest contributions to zinc (Zn) and cadmium (Cd) in urban green spaces, at 45.88–65.25%. Agricultural activities contributed similarly to Cd accumulation in both cropland and vegetable fields/orchards soils (41.68–51.32%), but their contributions to Cu and Zn in vegetable fields/orchards soils (46.62–55.58%) were significantly higher than those in cropland (9.21–13.40%). Notably, unexplained sources accounted for 18.64–42.59% of heavy metals in vegetable fields/orchards soils, suggesting particularly complex sources in these systems. This study provides a scientific basis for sustainable soil management strategies and promoting coordinated pollution control in urban agglomeration regions. 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

This study reports on green-synthesized zinc oxide nanoparticles (ZnONPs), focusing on their physicochemical characterization, photocatalytic properties, and agricultural applications. Dynamic light scattering (DLS) analysis revealed a mean hydrodynamic diameter of 337.3 nm and a polydispersity index (PDI) of 0.400, indicating moderate polydispersity and nanoparticle aggregation, typical of biologically synthesized systems. High-resolution transmission electron microscopy (HR-TEM) showed predominantly spherical particles with an average diameter of ~28 nm, exhibiting slight agglomeration. Energy-dispersive X-ray spectroscopy (EDX) confirmed the elemental composition of zinc and oxygen, while X-ray diffraction (XRD) analysis identified a hexagonal wurtzite crystal structure with a dominant (002) plane and an average crystallite size of ~29 nm. Photoluminescence (PL) spectroscopy displayed a distinct near-band-edge emission at ~462 nm and a broad blue–green emission band (430–600 nm) with relatively low intensity. The ultraviolet–visible spectroscopy (UV–Vis) absorption spectrum of the synthesized ZnONPs exhibited a strong absorption peak at 372 nm, and the optical band gap was calculated as 2.67 eV using the Tauc method. Fourier-transform infrared spectroscopy (FTIR) analysis revealed both similarities and distinct differences to the pigeon extract, confirming the successful formation of nanoparticles. A prominent absorption band observed at 455 cm⁻¹ was assigned to Zn–O stretching vibrations. X-ray photoelectron spectroscopy (XPS) analysis showed that raw pigeon droppings contained no Zn signals, while their extract provided organic biomolecules for reduction and stabilization, and it confirmed Zn²⁺ species and Zn–O bonding in the synthesized ZnONPs. Photocatalytic degradation assays demonstrated the efficient removal of pollutants from sewage water, leading to significant reductions in total dissolved solids (TDS), chemical oxygen demand (COD), and total suspended solids (TSS). These results are consistent with reported values for ZnO-based photocatalytic systems, which achieve biochemical oxygen demand (BOD) levels below 2 mg/L and COD values around 11.8 mg/L. Subsequent reuse of treated water for irrigation yielded promising agronomic outcomes. Wheat and barley seeds exhibited 100% germination rates with ZnO NP-treated water, which were markedly higher than those obtained using chlorine-treated effluent (65–68%) and even the control (89–91%). After 21 days, root and shoot lengths under ZnO NP irrigation exceeded those of the control group by 30–50%, indicating enhanced seedling vigor. These findings demonstrate that biosynthesized ZnONPs represent a sustainable and multifunctional solution for wastewater remediation and agricultural enhancement, positioning them as a promising candidate for integration into green technologies that support sustainable urban development. Full article

Given that the increasing non-agricultural conversion of cultivated land (NACCL) endangers food security, studying the spatial and temporal variation characteristics and driving mechanisms of NACCL in Sichuan Province can offer a scientific foundation for developing local farmland preservation measures and controlling further conversion. Guided by the theoretical framework of land use transition, this study utilizes land use datasets spanning multiple periods between 2000 and 2023. Comprehensively considering population scale factors, natural geographical factors, and socioeconomic factors, the county-level annual NACCL rate is calculated. Following this, the dynamic evolution and underlying driving forces of NACCL across 183 counties in Sichuan Province are examined through temporal and spatial dimensions, utilizing analytical tools including Nonparametric Kernel Density Estimation (KDE) and the Geographical Detector model with Optimal Parameters (OPGD). The study finds that: (1) Overall, NACCL in Sichuan Province exhibits phased temporal fluctuations characterized by “expansion—contraction—re-expansion—strict control,” with cultivated land mainly being converted into urban land, and the differences among counties gradually narrowing. (2) In Sichuan Province, the spatial configuration of NACCL is characterized by the expansion of high-value agglomerations alongside the dispersed and stable distribution of low-value areas. (3) Analysis through the OPGD model indicates that urban construction land dominates the NACCL process in Sichuan Province, and the driving dimension evolves from single to synergistic. The findings of this study offer a systematic examination of the spatiotemporal evolution and underlying drivers of NACCL in Sichuan Province. This analysis provides a scientific basis for formulating region-specific farmland protection policies and supports the optimization of territorial spatial planning systems. The results hold significant practical relevance for promoting the sustainable use of cultivated land resources. Full article

A quantitative study on the spatial structure and spatiotemporal variation characteristics of net carbon sinks in regional farmland ecosystems is of significant importance for uncovering the multifunctional roles of farmland ecosystems and formulating region-specific agricultural policies and management strategies. Based on the measurement of net carbon sinks in county-level farmland ecosystems across Hunan Province from 2005 to 2020, this research employs methodologies, including the standard deviational ellipse (SDE), spatial autocorrelation, and exploratory spatiotemporal data analysis (ESTDA) to investigate the spatiotemporal evolution characteristics of net carbon sinks in Hunan’s county-level farmland ecosystems. The results show that the net carbon sinks of county-level farmland ecosystems in Hunan Province exhibits a “northeast–southwest” spatial distribution pattern, with a trend toward spatial agglomeration during contraction, and the center of gravity of net carbon sinks has generally shifted northwestward over time. A significant positive spatial correlation exists globally in the net carbon sinks of Hunan’s county-level farmland ecosystems, and the degree of spatial agglomeration has gradually intensified amid fluctuations. The dynamic evolution of local spatial patterns of net carbon sinks in county-level farmland ecosystems in Hunan Province varied significantly, showing strong stability in both local spatial structure and spatial dependence direction. In contrast, eastern and central Hunan exhibited more dynamic local spatial structures compared to southern and northern regions. The local spatial association patterns of the net carbon sinks in county-level farmland ecosystems remained relatively stable, with weak spatial synergy and a pronounced path-dependent locking effect in spatial agglomeration. Full article

Urban agglomerations underpin regional economic growth and sustainability transitions, yet the spatial heterogeneity and drivers of land use intensity (LUI) remain insufficiently resolved in inland settings. This study develops a high-resolution framework—combining a 1 km hexagonal grid with XGBoost-SHAP—to (i) map subsystem-specific LUI evolution, (ii) identify dominant drivers and nonlinear thresholds, and (iii) inform differentiated, sustainable land governance in the Guanzhong Plain Urban Agglomeration (GPUA) over 2000–2020. Composite LUI indices were constructed for human settlement (HS), cropland (CS), and forest (FS) subsystems; eleven natural, socioeconomic, urban–rural, and locational variables served as candidate drivers. The results show marked redistributions across subsystems. In HS, the share of low-intensity cells declined (86.54% to 83.18%) as that of medium- (12.10% to 14.26%) and high-intensity ones (1.22% to 2.56%) increased, forming a continuous high-intensity corridor between Xi’an and Xianyang by 2020. CS shifted toward medium-intensity (32.53% to 50.57%) with the contraction of high-intensity cells (26.62% to 14.53%), evidencing strong dynamism (55.1% net intensification; 38.5% net decline). FS transitioned to low-intensity dominance by 2020 (59.12%), with stability and delayed growth concentrated in conserved mountainous zones. Urban–rural gradients were distinct: HS rose by >20% (relative to 2000) in cores but remained low and stable in rural areas (mean < 0.20); CS peaked and stayed stable at fringes (mean ≈ 0.60); FS shifted from an inverse gradient (2000–2010) to core-area recovery by 2020. Explainable machine learning revealed inverted U-shaped relationships for HS (per capita GDP) and CS (population density) and a unimodal peak for FS with respect to distance to urban centers; model performance was strong (HS R² up to 0.82) with robust validation. Policy recommendations are subsystem-specific: enforce growth boundaries and prioritize infill/polycentric networks (HS); pair farmland redlines with precision agriculture (CS); and maintain ecological redlines with differentiated conservation and afforestation (FS). The framework offers transferable, data-driven evidence for calibrating thresholds and sequencing interventions to reconcile land use intensification with ecological integrity in rapidly urbanizing contexts. Full article

Accurate analysis of land use transformation (LUT) and its ecological and environmental effects, along with investigations into how ecological and environmental quality responds to both natural and human factors, is crucial for protecting regional ecosystems. This research concentrated on the Yangtze River Delta Urban Agglomeration (YRDUA), analyzing land use change patterns and their effects on ecological environment quality (EEQ) from the perspectives of production, living, and ecological spaces. Partial least squares structural equation modeling (PLS-SEM) was utilized to assess the immediate and mediated effects of environmental and socio-economic drivers. Additionally, this study examined how urban agglomeration integration affects LUT and EEQ. The findings suggest that: (1) Throughout 2000–2020, production land decreased, and living land expanded markedly, while ecological land remained largely stable. (2) Between 2000 and 2020, the overall environmental quality in the YRDUA declined, showing significant temporal and spatial disparities among regions. (3) Converting urban or rural residential land to agricultural land promotes ecological improvement, whereas the opposite conversion tends to result in environmental degradation. (4) Topography, climate, and greening directly improve environmental quality, whereas LUT, economic development and integration exert adverse impacts. Topography indirectly influences the ecological environment through its effects on climate, economy, regional integration, and LUT, whereas climate and the economy exert indirect effects via LUT, greening and integration. This research serves as a scientific foundation for ecological environment protection, sustainable growth and regional land space planning in urban agglomerations. Full article

Photocatalytic technology offers significant potential for pollutant remediation through efficient, cost-effective mineralization but faces inherent limitations, including catalyst agglomeration and rapid charge recombination. To address these challenges, we developed activated carbon-modified porous graphitic carbon nitride (APCN) synthesized through the co-polycondensation of dicyandiamide with NH₄Cl and fir-wood-derived activated carbon (AC). The incorporated AC effectively prevented the agglomeration of carbon nitride frameworks, thereby enhancing the specific surface area (S_BET) of APCN. This matrix was subsequently composited with hydrothermally prepared (1T/2H) mixed-phase MoS₂ through ultrasonication, forming a MoS₂/APCN heterostructure. Characterizations including Scanning electron microscopy (SEM), Transmission electron microscopy (TEM), and N₂ adsorption–desorption isotherms (BET) confirmed that MoS₂ was successfully loaded onto APCN via an ultrasonic synthesis method. The composite exhibited outstanding photocatalytic activity, degrading 95.5% RhB in 40 min (pH = 7) and 97.4% in 25 min (pH = 3.5), with 87.3% efficiency retention after four cycles (pH = 7). Crucially, AC enhanced visible-light absorption and functioned as an electron-mediating component. Photoelectrochemical analyses and radical-trapping experiments confirmed a direct Z-scheme charge transfer mechanism, wherein conductive AC accelerates electron transport and suppresses carrier recombination. This study establishes both an efficient RhB degradation photocatalyst and a sustainable strategy for valorizing agricultural waste in advanced material design. Full article