Search Results (943)

Dendroctonus valens LeConte represents a major invasive pest species in China. Both larvae and adults primarily feed on the phloem of the tree trunk base and roots, disrupting nutrient transport and leading to host tree mortality, which poses a severe threat to forest ecosystems and the forestry economy. Juvenile hormone acid methyltransferase (JHAMT) is a key enzyme in insect juvenile hormone (JH) biosynthesis. In this study, we identified a JHAMT-encoding gene, DvJHAMT, in D. valens via bioinformatic analysis. RT-qPCR analysis revealed that DvJHAMT is predominantly expressed during the egg and larval stages. In the fourth-instar larvae, the highest expression levels were observed in the head and epidermis, suggesting a central regulatory role during this critical developmental period. To investigate its function via RNA interference (RNAi), a nanomaterial, star polycation (SPc), was employed for the transdermal delivery of dsRNA into the fourth-instar larvae. The results demonstrated that DvJHAMT knockdown significantly downregulated mRNA levels, resulting in marked decreases in larval survival, pupation, and eclosion rates. Notably, treatment with 0.7 µg dsDvJHAMT-SPc resulted in a 96.67% mortality rate and a reduced pupation rate of 41.67% at 34 days post-treatment. Furthermore, RNAi led to developmental deformities and significant weight loss in larvae. ELISA assays confirmed that DvJHAMT silencing led to reduced JHAMT enzyme activity and JH III titers in a dose-dependent manner. In conclusion, our findings demonstrate that DvJHAMT plays a vital role in JH biosynthesis and that its suppression exhibits potent lethal effects, suggesting that DvJHAMT is a promising candidate for RNAi-based management of D. valens. Full article

The Huang–Huai–Hai Plain supports one of China’s most important grain production systems, but crop production there is persistently constrained by limited water availability and recurrent drought. Common regional drought indicators are useful for monitoring dry conditions, yet they do not explicitly represent crop water demand and irrigation input, which reduces their suitability for agricultural risk assessment. In this study, a crop-oriented framework was developed for winter wheat and summer maize by linking crop water requirement, effective rainfall, irrigation supply, drought-event detection, and productivity-risk estimation. A standardized crop water deficit index (SCWDI) was developed from crop water balance and integrated with run theory, monthly correlation analysis, and a Copula–Bayesian framework to detect drought events, identify crop-sensitive periods, and quantify the probability and triggering threshold of gross primary productivity (GPP) loss. During 2001–2022, the Huang–Huai–Hai Plain experienced an average of 1.15 drought events per year, with pronounced spatial differences. The main sensitive period was June for summer maize and March–April for winter wheat. Summer maize showed a stronger drought response, with a mean triggering threshold of −1.54, whereas winter wheat required more severe stress to trigger concentrated productivity loss (−2.54). Under extreme drought, the probability of summer-maize GPP loss exceeded 80% in both the Beijing–Tianjin–Hebei region and Henan. These results provide a basis for growth-stage-oriented irrigation prioritization and spatially differentiated drought management under agricultural water scarcity. Full article

Water scarcity and water quality degradation in river basins are critical issues addressed by water resources management authorities. Grey relational analysis is adopted to rank key factors affecting water resources in the Beijing-Tianjin-Hebei region. Bankruptcy theory is combined with an improved Nash bargaining game model, and spatiotemporal constraints of cross-regional water resources are incorporated to analyze water allocation under multiple water supply scenarios. Results indicate that the GM (1,1) model achieves Level II (good) prediction accuracy, with relative errors below 6% in most years. The cooperative game model (CGM) yields the highest correlation coefficient of 0.996, indicating the optimal allocation performance. The water demand satisfaction rate in Beijing is the highest among the three regions. An economic compensation range indicator (e) is established for water resource trading games. As the trading water volume increases from 0.01 to 20 billion m³, the feasible compensation range expands from 463.57 to 1,757,045.78 ten thousand yuan. These results provide a scientific basis for rational, stable, and sustainable water resources allocation in the Beijing-Tianjin-Hebei region. Full article

The evolution of groundwater in the Puhe River Basin is closely related to the ecological security of the Beijing–Tianjin–Hebei water source conservation zone. Based on 122 groundwater samples, this study systematically investigated the hydrochemical characteristics, evolution mechanisms, and water quality of shallow groundwater using mathematical statistics, Piper diagrams, ionic ratio analysis, and a variable fuzzy pattern recognition model. The results showed that shallow groundwater in the middle and upper reaches is generally weakly alkaline, fresh to hard water, with HCO₃–Ca and HCO₃·SO₄–Ca as the dominant hydrochemical facies. Groundwater hydrochemistry is primarily controlled by rock weathering, and the dissolution of silicate and carbonate rocks is the main source of major ions. Calcite and dolomite are in dynamic equilibrium between dissolution and precipitation, whereas gypsum and halite remain undersaturated. Overall, groundwater quality is generally good; however, anthropogenic activities in cultivated and construction lands have altered local hydrochemical composition and caused water quality deterioration in some areas. These findings improved the understanding of groundwater hydrochemical evolution in typical small watersheds of the northern Hebei hilly region and provided a scientific basis for the sustainable management and protection of groundwater resources in the Beijing–Tianjin–Hebei water source conservation area. Full article

How AI can contribute to green sustainable development (GSD) in China is a critical yet underexplored question. Leveraging the staggered implementation of the National New Generation Artificial Intelligence Innovation and Development Pilot Zone (AIPZ) as a quasi-natural experiment, this study employs a difference-in-differences approach with panel data from 285 prefecture-level cities (2017–2022). The main findings are threefold. First, AI directly promotes GSD and, more importantly, indirectly enhances GSD by upgrading new-quality productivity (NQP)—a novel mechanism that distinguishes this study from conventional environmental policy evaluations. Second, the facilitating effect is not uniform: significant positive effects are detected in the western, eastern, and central regions, but not in the northeastern region; among major urban agglomerations, the Pearl River Delta, Chengdu-Chongqing, and Yangtze River Deltaexhibit significant effects, whereas the Middle Reaches of the Yangtze River and Beijing-Tianjin-Hebei region does not. Third, spatial spillover analysis reveals that AI’s favorable effect on GSD spreads primarily through intercity similarity in economic development level. These findings provide actionable insights for policymakers aiming to harness AI for sustainable development, highlighting the importance of fostering NQP and designing regionally differentiated strategies. Full article

Understanding how sustainable urban competitiveness evolves within megaregions has become a central concern in urban and regional studies, particularly under the pressures of carbon neutrality, spatial inequality, and network-driven urbanization. This study develops a multidimensional framework to assess the sustainable competitiveness of cities in the Beijing–Tianjin–Hebei “2 + 36” urban agglomeration and examines its spatio-temporal evolution and relational structure. Using a 30-indicator system grounded in factor foundations, economic performance, innovation capacity, openness, and environmental livability, we construct a composite competitiveness index through principal component analysis (PCA). Kernel density estimation reveals a pattern of overall improvement accompanied by widening disparities, characterized by selective agglomeration and the emergence of a pronounced high-value tail. Spatial autocorrelation consistently indicates significant spatial dependence, while LISA analysis identifies persistent low–low clusters and limited spillover absorption around core cities. A modified gravity model further uncovers a transition from a linear, corridor-based linkage structure to a more polycentric and networked competitiveness system, albeit with enduring peripheral weak nodes. The study contributes theoretically by conceptualizing sustainable urban competitiveness as a multidimensional nexus shaped jointly by territorial attributes and relational network structures. It demonstrates that competitiveness dynamics in megaregions emerge from the interplay of hierarchical consolidation, spatial divergence, and network reconfiguration—challenging the traditional assumption of simple core-to-periphery diffusion. The findings offer broader global implications, showing that the Beijing–Tianjin–Hebei case mirrors worldwide megaregional patterns, where proximity alone is insufficient to ensure functional integration, and where coordinated governance, network embeddedness and sustainability transitions increasingly determine regional competitiveness. This research provides a comprehensive analytical foundation for understanding and governing megaregional competitiveness in the era of sustainable development. Full article

Despite substantial improvement in air quality in China, winter PM_2.5 concentrations particularly in January show limited decline, especially in the central region. This study used statistical analysis and WRF-CMAQ to examine how typical meteorological years affect transport and pollution processes in Henan. The mean effect difference ranged from −22 to 33%. In January 2020, weak winds and a low planetary boundary layer increased PM_2.5 by 3–33%, whereas in January 2023, stronger northerly winds and a higher boundary layer reduced PM_2.5 by 12–22%. These differences altered transport pathways, leading to a shift in dominant source regions from Beijing–Tianjin–Hebei and Shandong to Anhui and Hubei, with primary PM_2.5 showing high sensitivity to transport pathways, whereas secondary PM_2.5 remained relatively stable due to its dependence on regional chemical formation. Typical meteorological years in Henan exhibit two distinct pollution regimes: The local accumulation regime (2020) showed faster growth (20–30 μg m⁻³ d⁻¹), a higher peak (107 μg m⁻³), longer persistence, and slower dissipation and was dominated by near-range transport. In contrast, the regional transport regime (2023) exhibited slower growth (<20 μg m⁻³ d⁻¹), a lower peak (99 μg m⁻³), shorter persistence, and more rapid dissipation and was sustained by multi-regional input from Anhui, Shandong, and Hubei. In both episodes, primary PM_2.5 dominated during the growth and peak stages, whereas secondary PM_2.5 played a more prominent role during dissipation. Full article

With the digital economy emerging as a new driver of high-quality development, unlocking the value of data factors and stimulating innovation momentum has become a key component of national strategy. This study treats the establishment of government open data platforms as an exogenous policy shock reflecting the degree of public data openness. Based on a multidimensional dataset constructed from China’s full patent database covering the period 2003–2022, we empirically examine how public data openness affects green technological innovation. The results indicate that public data openness exerts a significant positive effect on green technological innovation. These conclusions remain robust and consistent after a battery of rigorous robustness checks. In terms of heterogeneity, the impact displays prominent regional disparities: it is more pronounced in the Beijing–Tianjin–Hebei region, the Yangtze River Delta, the urban agglomerations in the middle reaches of the Yangtze River, as well as in non-traditional industrial bases and transport hub cities. Mechanism analysis suggests that public data openness fosters green technological innovation by attracting innovative talents, boosting entrepreneurial dynamism, and advancing governance transparency. These conclusions offer new implications for governments to optimize the provision of public services in the digital era and advance high-quality economic growth. Full article

Digital transformation and transparency in the seed supply chain are cornerstones of national food security and sustainable agricultural development. Existing agricultural traceability systems suffer from elevated storage overhead and performance degradation with massive seed data processing and fail to iterate quality supervision standards without disrupting continuous business operation. To address these problems, this study proposes a dual-optimization architecture-based traceability system for seed supply chains. An edge-assisted Merkle-tree dimension-reduction aggregation protocol is introduced to compress seed logistics scanning data before blockchain submission. Instead of storing each circulation record as an independent on-chain state update, the proposed scheme anchors one fixed-size Merkle root for each aggregated batch, reducing the per-batch on-chain payload to a constant size and lowering the overall on-chain anchoring burden from record-level growth to batch-level growth. Furthermore, it adopts a decoupled regulatory architecture based on the Strategy Pattern for the separation of traceability state storage and compliance inspection logic, enabling uninterrupted rule switching under the tested upgrade scenario via on-chain hash pointer adjustment. Rigorous statistical evaluation of the experimental results indicates that the system stably processes seed circulation records at a peak effective throughput of 1952.4 transactions per second. Under high-frequency concurrency, the 95th percentile (P95) latency remains controlled under 0.28 s. The average physical on-chain storage for 100,000 circulation records was reduced to 0.52 MB, and deploying a new quality inspection rule takes an average of only 2.2 s, with limited computational resource overhead. Full article

Quantifying anthropogenic CO₂ increments is vital for assessing emission reductions. Using a seamless XCO₂ dataset over China reconstructed from OCO-2/3 satellite retrievals and machine learning, combined with EOF decomposition and LISA analysis, this study investigates XCO₂ anomalies and local anthropogenic increments (dXCO₂) at national and urban agglomeration scales. Nationally, XCO₂ anomalies exhibit a “southeast positive, northwest negative” spatial pattern aligning with human activities and a “winter high, summer low” seasonal cycle. EOF analysis reveals four dominant modes: anthropogenic–natural trade-offs, East Asian summer monsoon modulation, local emissions, and baseline context. At the regional scale, multi-year mean dXCO₂ (2015–2019) in Beijing–Tianjin–Hebei (BTH), Yangtze River Delta (YRD), and Pearl River Delta (PRD) are 3.46 ± 0.45 ppm, 1.30 ± 0.36 ppm, and 0.08 ± 0.14 ppm, respectively, showing higher values in northern heavy industrial zones. During the 2020–2022 pandemic, dXCO₂ decreased in BTH (2.28 ± 0.73 ppm) and YRD (1.16 ± 0.43 ppm) but increased in PRD (0.28 ± 0.27 ppm). Compared to pre-pandemic levels, lockdowns saw dXCO₂ decrease slightly in YRD while increasing in BTH and PRD, reflecting differential responses of regional industrial structures. This study demonstrates the potential of seamless XCO₂ data for monitoring anthropogenic enhancement signals, and the proposed LISA-based method offers new support for regionally differentiated emission reduction assessments. Full article

This study investigates the spatiotemporal evolution and migration path coupling of the “water–land–energy–carbon” nexus system in the Beijing–Tianjin–Hebei region from 2002 to 2023 using multi-source data. The Coefficient of Variation and Shannon entropy were employed to assess the stability of elements, while Dynamic Time Warping (DTW) was applied to couple their migration paths. The results reveal the following: (1) Terrestrial water and groundwater exhibited similar evolution patterns, though groundwater showed greater volatility. Land use remained stable, with primary conversion being cropland to impervious. Nighttime light intensity increased significantly in urban areas, reflecting growth in energy consumption. Carbon emissions increased in most areas but decreased in some urban centers. (2) Element centroids displayed differentiated migration: water resources and cropland shifted southwest, and ecological land expanded northwest, while impervious, carbon emissions, and nighttime light concentrated in the southeast and northeast. (3) Two strongly coupled paths were identified: “terrestrial water–groundwater–cropland,” reflecting agricultural dependence on water resources, and “impervious –nighttime light–carbon emissions,” revealing the linkage between urban expansion, energy consumption, and carbon emissions. This study reveals the migration patterns of factors driven by both natural factors and human activities, providing quantitative support for resource optimization and low-carbon development policies in the Beijing–Tianjin–Hebei region. Full article

The Beijing–Tianjin–Hebei (BTH) coordinated-development strategy provides a county-level setting for examining how transport-led regional restructuring reshaped the relationship between human activity and land–environment conditions. Using a balanced panel of 200 county-level units from 2010 to 2020, we work with two linked subsystems: the human-activity subsystem (H), which combines transport integration and economic upgrading, and the land–environment subsystem (L), which combines land-use transition and ecological response. Pooled entropy weighting, a coupling-coordination index, spatial autocorrelation analysis, and fixed-effects differential-response models are used to trace temporal change, spatial clustering, and post-2014 heterogeneity within BTH. Mean coupling coordination (D) rose from 0.5430 to 0.6012, but the increase came mainly from the rise of H, while L changed only slightly. Positive spatial autocorrelation persisted throughout the period. Counties in the Beijing–Tianjin ring kept higher absolute coordination levels, yet after 2014, they improved more slowly than non-ring counties because land–environment adjustment lagged behind changes within H. Relative to key ecological function zones, agricultural counties—and to a lesser extent urbanized counties—posted faster gains in D, again mainly through H. The results show that in BTH, regional integration did not move the two subsystems in lockstep: transport reorganization and economic upgrading advanced faster than land–environment adjustment, so durable county coordination still depended on land governance, ecological regulation, and policies matched to territorial functions. Full article

Urban agglomerations have become the dominant spatial platform of urbanization, regional coordination, and economic transformation in China. Yet whether the expansion of agglomeration scale at the urban-agglomeration level alleviates or intensifies energy use remains insufficiently understood. Extending the scale of analysis from individual cities to integrated urban agglomerations, this study investigates 64 cities in four major Chinese urban agglomerations, including Beijing–Tianjin–Hebei, the Yangtze River Delta, the Pearl River Delta, and Chengdu–Chongqing, over the period 2006–2023. Using panel data models, this study examines the impact of the scale agglomeration within urban agglomeration on urban energy intensity. The results show that the overall agglomeration scale generated by urban agglomeration formation significantly suppresses energy intensity while indicating a robust energy-saving effect: every 10% increase in agglomeration scale is associated with a decline of approximately 0.0893 million tons of standard coal per CNY 100 million of GDP. This finding remains stable after addressing endogeneity concerns and performing a series of robustness checks. Mechanism analyses further suggest that this effect operates primarily through talent agglomeration, technological progress, and public transportation expansion. In addition, the energy-saving effect is more pronounced in smaller cities, cities with lower administrative rank, cities with weaker factor mobility, and cities characterized by poorer air quality but stronger public environmental attention. These findings contribute to the literature on urban agglomeration and green development by showing that the agglomeration scale within urban agglomerations can generate inclusive energy-efficiency gains, especially for relatively disadvantaged cities, thereby offering important implications for spatial governance and low-carbon transition in rapidly urbanizing economies. Full article

In the context of global climate change, the “dual carbon” goals, and land space planning, this study integrates the Patch-generating Land Use Simulation (PLUS) model, the Carnegie-Ames-Stanford Approach (CASA) model, and a soil respiration model (Heterotrophic Respiration, R_h) to simulate land use change and estimate Net Ecosystem Productivity (NEP) from 2002 to 2023. It projects the carbon sink pattern for 2030 using Hot Spot Analysis. The results show the following: (1) From 2020 to 2030, land use in the Beijing–Tianjin–Hebei region will be characterized by decreases in cropland and grassland and increases in impervious and forest, with cropland-to-impervious conversion dominating. (2) The spatial pattern of NEP exhibits a clear “high in mountainous areas and low in plains” distribution, where forest, grassland, and cropland function as carbon sinks, with forest having the strongest sequestration capacity. The carbon sink core areas cover approximately 59,479 km² and account for about 27.40% of the total area. (3) By 2030, the total carbon sink in the Beijing–Tianjin–Hebei region is projected to range from 31.81 to 32.39 Tg C under different scenarios, with forest contributing nearly 70%. The carbon sink core areas account for approximately 19.12–19.16 Tg C, representing about 60% of the total carbon sink. Full article

Railways constitute a core component of China’s national comprehensive transportation network, and their spatial organization and temporal accessibility jointly shape transport integration and system efficiency. Identifying their evolution from the dual perspectives of spatial expansion and time compression is therefore of both theoretical and practical significance. Drawing on fractal theory, this study examines the structural characteristics, evolutionary trends, and driving factors of railway networks in China’s five major urban systems from 2014 to 2024 from a “space–time” dual perspective. The results show that railway networks exhibit a staged pattern of “spatial filling preceding temporal correlation”, with a lag of approximately 1–8 years—about 1 year in the Guangdong–Hong Kong–Macao Greater Bay Area (GBA), 5 years in the Middle Yangtze River (MYR) region and Beijing–Tianjin–Hebei (BTH), and up to 8 years in the Chengdu–Chongqing (CC) region. In addition, clear regional differences are observed: the Yangtze River Delta (YRD) is polycentric, with the greatest potential, projected to continue rapid spatial growth until 2027 and to remain in a fast-growth phase of temporal correlation; GBA is highly coordinated; BTH is developed but characterized by dual-core agglomeration; CC grows rapidly with lagging functionality; and MYR is corridor-dependent with limited potential. These findings indicate that network functionality does not emerge synchronously with infrastructure expansion, but depends on subsequent improvements in operational organization and service capacity. Compared with single-scale-based indicators, the “spatial distribution–temporal correlation” framework more effectively captures network performance and provides quantitative support for transport optimization and coordinated regional development. Full article