Agricultural production contributes to the increase in global carbon emissions. It is crucial to improve output and reduce carbon emissions in the context of agricultural modernization, for which improved carbon emission efficiency is key. However, the role of agricultural modernization in promoting agricultural carbon emission efficiency is not clear. Hence, the aim of this article is to analyze the spatiotemporal evolution of agricultural modernization and agricultural carbon emission efficiency in China from 2000 to 2019 and to reveal the relationship between agricultural modernization and agricultural carbon emission efficiency. The results showed that (1) in China, the overall level of agricultural modernization has been steadily increasing, and the regional differences are widening, showing a spatial pattern characterized by a gradual decline from the eastern and central regions to the western region. (2) China’s agricultural carbon emission efficiency continues to grow but has not achieved a data envelopment analysis (DEA) effect, with the eastern and western regions having higher agricultural carbon efficiency than the central region. The regional differences first narrow and then expand. (3) Agricultural modernization significantly promotes agricultural carbon emission efficiency in both the province and the neighboring provinces, and the interprovincial spillover effect exceeds the direct effect within the province. A nonlinear correlation exists between agricultural modernization and agricultural carbon emission efficiency.

Stabilizing food prices is essential for ensuring food security in an aging society. Using panel data from 30 Chinese provinces spanning 2005 to 2022, this study employs a nonlinear panel model and a Spatial Durbin Model (SDM) to analyze the impact of rural population aging on food prices and its spatial spillover effects. This study derives the following findings based on empirical research: (1) Rural population aging exhibits a significant inverted U-shaped relationship with food prices, with an inflection point at approximately 19.03%. Before reaching this point, rural population aging helps facilitate food prices. When the inflection point is passed, rural population aging adversely impacts food prices. This effect is significant in western regions but not in eastern and central regions. (2) Farmland transfer and agricultural technological progress significantly influence this relationship, causing the curve to reverse into a U-shaped pattern, which implies a gradual future increase in food prices. (3) Local rural population aging has a significant U-shaped spillover effect on food prices in neighboring provinces. These findings indicate that China’s rural population aging presents a complex dynamic for food price fluctuations. To address the current changes in the population and capital structure and ensure food security, the government will need to formulate forward-looking policies, further improve socialized agricultural services, and systematically optimize food production models.