Climate change and increasingly severe weather pose dual pressures on agriculture: to reduce carbon emissions and to manage climate risk. These pressures challenge the transition to green, low-carbon development. On the basis of panel data from 31 provinces in China from 2003 to 2023—a period selected for data continuity and to capture the implementation of major national agricultural and environmental policies—in this study, an evaluation index system for agricultural green and low-carbon development (GAC) was established. This study aims to analyze the impact of climate change risks (CPRI) on GAC, focusing on the moderating role of agricultural insurance (INS) and spatial spillover effects. Specifically, it seeks to answer the following questions: (1) What is the direction and magnitude of CPRI’s effect on GAC? (2) Can INS mitigate this effect? (3) Does CPRI exhibit spatial spillover effects on GAC? Using data from the NOAA and Chinese statistical yearbooks, by employing a model with two-way fixed effects, moderating effect analysis, and the spatial Durbin model, the mechanisms underlying the spatial spillover effects of CPRI and regional heterogeneity were examined, as well as the moderating function of INS. CPRI was found to significantly inhibit GAC, as extreme weather events triggered short-term decision-making among farmers and constrained investment in green technologies. These events reduced the capacity of the soil to sequester carbon. This inhibitory effect was greater in nonmajor grain-producing regions and in eastern China. INS helped reduce negative impacts by providing effective risk transfer mechanisms. Furthermore, CPRI was found to exert harmful spillover effects across different regions, with greater indirect effects than direct effects. In conclusion, CPRI significantly hinders agricultural green transition, a process moderated by insurance and characterized by spatial spillovers. On the basis of these observations, we recommend several policies, including the development of regionally tailored adaptation strategies, the achievement of innovation in agricultural insurance products, and the establishment of collaborative governance frameworks that span regions to address these challenges.

The combined implementation of land consolidation and smart agriculture is crucial for food security and agricultural carbon neutrality. Using 2010–2024 panel data from 279 Chinese prefecture-level cities, this study constructs an integrated assessment system and examines impact mechanisms and spatial effects using dual machine learning, mediation analysis, and dynamic spatial models. Results show that the interaction between land consolidation and smart agriculture significantly enhances food security at the 10% significance level and promotes agricultural carbon neutrality. Mechanism analysis indicates that agricultural industrial agglomeration positively contributes to both outcomes, while technological innovation significantly promotes carbon neutrality but temporarily suppresses food security. Spatial analysis reveals limited direct effects on local food security but positive indirect and total effects on neighboring regions, with carbon neutrality showing positive direct, indirect, and total effects. After controlling for city fixed effects and quadratic terms, the synergy remains significant, indicating robustness. The study suggests strengthening coordinated governance and innovation-driven regional development to jointly advance food security and agricultural carbon neutrality.