The study aimed to investigate the spatial correlation network of carbon emissions from cultivated land use in the Yellow River Basin(YRB) and its driving factors, which is conducive to promoting collaborative carbon emission reduction in cultivated land use across the region. The study utilized the carbon emission coefficient method to calculate carbon emissions from cultivated land use in the YRB between 2008 and 2022. A modified gravity model and social network analysis method were then employed to analyze the characteristics of the spatial correlation network of carbon emissions from cultivated land use in the YRB. Additionally, the Quadratic Assignment Procedure (QAP) method was utilized to identify driving factors. The research findings indicate that: (1) Between 2008 and 2022, the overall carbon emissions from cultivated land use in the YRB increased by 27.6%. The proportion of carbon emissions from different sources, from largest to smallest, was as follows: straw burning (over 60%), agricultural inputs (over 20%), and crop cultivation (around 13%). (2) According to the overall network characteristics, the spatial correlation network underwent an evolution from dispersion to concentration and then to adjustment. The network connectivity was good, efficiency fluctuated and rose to stability, centrality showed an inverted "U" shaped change, with Shandong and Henan remaining at the core of the network throughout. (3)Based on individual network characteristics, the network structure showed a core-periphery hierarchy, with Gansu and Inner Mongolia identified as the core provinces. (4) QAP analysis indicated that factors such as geographical proximity, urbanization levels, and agricultural machinery input intensity positively influenced the spatial correlation network, while factors like agricultural economic levels, farmer income levels, and environmental regulations had negative effects. Based on the findings of this study, feasible pathways are proposed from aspects including the three sources of carbon emissions, regional cooperation within the YRB, and policy optimization.

In the context of increasingly frequent and severe natural disasters, scientifically measuring and analyzing the efficiency of natural disaster emergency management in China is of great practical significance for enhancing the performance of the emergency management system and promoting its systematic and high-quality development. This study first applies a super-efficiency SBM-DEA model with undesirable outputs to systematically measure the efficiency of China’s natural disaster emergency management system during the period 2019–2023. Subsequently, the Dagum Gini coefficient and Kernel Density estimation are employed to examine regional disparities and dynamic evolution across eastern, central, western, and northeastern China. Finally, the coefficient of variation and spatial econometric models are applied to test the spatial convergence characteristics of emergency management efficiency. The results indicate that: (1) China’s overall disaster emergency management efficiency remains at a relatively low level and exhibits a fluctuating trend characterized by an initial increase followed by a decline. The regional distribution pattern of emergency efficiency is ranked as “Northeast > Central > West > East”. (2) The average annual contributions of intra-regional disparities, inter-regional disparities, and transvariation density to the overall variation in national emergency management efficiency are 27.58%, 39.90%, and 32.53%, respectively, indicating that inter-regional disparities and transvariation density are the dominant sources of systemic differences among regional subsystems. (3) The national distribution of emergency management efficiency displays a bimodal pattern, indicating polarization; however, the secondary peak is relatively flat, suggesting a weakening trend of provincial-level polarization and a gradual narrowing gap with high-efficiency regions. (4) σ-divergence is observed at the national level and in the central region, while both absolute and conditional β-convergence exist to varying degrees at the national level and across all four regions. Nevertheless, the enhancement of natural disaster emergency management efficiency has not yet realized a system-level transition from convergence in growth rates to convergence in efficiency gaps. In addition, economic development, technological progress, urbanization, and industrial structure exert significantly heterogeneous effects on disaster emergency management efficiency across different regions.

Improving environmentally adjusted water use efficiency in the planting industry (EAWUE) is important for balancing agricultural production, water conservation, and water environmental protection. Using panel data for 101 prefecture-level cities in the Yangtze River Economic Belt during 2011–2023, this study integrates a Super-SBM model with undesirable outputs, a modified gravity model, social network analysis, and a temporal exponential random graph model (TERGM) to examine EAWUE dynamics, spatial association networks, and formation mechanisms. The results show that EAWUE improved overall, although spatial disparities remained evident. The spatial association network became denser and more connected, with inter-city linkages expanding from local associations to broader cross-regional and multi-node interactions. The Yangtze River Delta maintained a prominent core position, cities in the middle reaches played stronger bridging roles, and cities in the upper reaches showed increasing participation, forming four functional block types. Network tie formation was statistically associated with endogenous network structures, node attributes, spatial constraints, and temporal dependence. Reciprocity, transitive structures, and network persistence showed positive associations with tie formation, whereas geographic distance showed a negative association. Resource endowment, rural human capital, and industrial structure upgrading generally showed positive associations, while economic development and government support exhibited heterogeneous associations with sending and receiving roles. Sensitivity and robustness tests generally supported the main structural findings. These findings highlight the need for differentiated prefecture-level governance, stronger agricultural water conservation and non-point source pollution control, improved cross-regional coordination, and fuller use of core nodes and functional blocks to support sustainable agricultural water management.