In the context of China’s population urbanization, the quality and pattern of farmers’ livelihoods are undergoing significant changes. Reducing emissions and sequestering carbon in agriculture is a crucial pathway for China to achieve its “dual carbon” goals. How to balance low-carbon agricultural development with the changing livelihood patterns of farmers has become an important issue in China’s agricultural and rural development. This study examines the impact of farmers’ livelihoods on agricultural carbon emission efficiency and explores regional disparities based on panel data from 31 provinces and municipalities in China from 2002 to 2020. The findings are as follows: (1) The quality of farmers’ livelihoods in China is conducive to an improvement in agricultural carbon emission efficiency (ACEE). (2) From a national perspective, the higher the livelihood of non-farm employment in the region, the higher the agricultural carbon emission efficiency. The livelihood of agricultural production has a significantly negative correlation with agricultural carbon emission efficiency. (3) Improvement in the quality of farmers’ livelihoods (QFL) in the eastern and western regions has a significant positive impact on the efficiency of agricultural carbon emissions, and the impact is larger in the western region, while there is no statistically significant relationship in the central region. The reason for this difference may be that the migration of agricultural labor from the western region to the eastern region and the local urban employment of eastern farmers have led to this, while the migration and local urban employment of agricultural labor in the central region is relatively limited. This paper provides policy insights into promoting both farmers’ income growth and low-carbon agricultural production in a coordinated manner.

In modern society with a highly developed Internet, online public opinions on swine epidemic diseases have become one of the important influencing factors for the fluctuation of pork prices. In this paper, the Baidu AI large model, Time-Varying Parameter-Stochastic Volatility-Vector Auto Regression (TVP-VAR) and Latent Dirichlet allocation (LDA) approaches are employed to investigate the dynamic impact of online public opinion regarding live swine epidemic diseases on fluctuations in pork price. The results show that: (1) Online public attention and negative sentiment exert significant time-varying impacts on pork price fluctuations, with these impacts being most pronounced in the short term and gradually diminishing over the medium and long term. (2) During the outbreaks of swine epidemic diseases, the impulse impact of online public attention and negative sentiment on pork price fluctuations exhibits distinct stage-specific characteristics. Initially, the impact is negative and subsequently turns positive before eventually waning. (3) The online discourse surrounding swine epidemic diseases can be categorized into four topics including disease transmission, vaccine technology, industry development, and disease prevention and control. Online public attention towards these four topics associated with negative sentiments generally contributes to variations in pork prices. Based on findings, several policy recommendations are proposed, including the timely release of swine epidemic disease information, the establishment and enhancement of the online public opinion monitoring and early warning system, as well as adherence to routine prevention and control of pig epidemic diseases.