Under the interactive background of more emphasis on low-carbon and environmentally friendly agricultural production modes and the coordinated development of agricultural foreign trade, China is paying more and more attention to the coordination between agricultural trade, economic development and ecological agriculture development. This paper selects the relevant data of China from 2002 to 2020 as the research object. Taking the agricultural carbon emission intensity as an indicator of environmental pollution, measuring it and then constructing a time series model for analysis, the research finds that, in the long run, the increase in agricultural carbon emission intensity in China will reduce the level of agricultural trade by 2%, which will also lead to a decline in the overall development level of the agricultural economy by 2 to 4 percent. At the same time, this paper also finds that the current situation of China’s agricultural trade reduces the development of China’s agriculture by 1%, which will also lead to an increase in agricultural carbon emission intensity by about 0.5%. Finally, this paper finds that the development of the agricultural economy makes the overall increase in agricultural trade 2%, and with the development of the agricultural economy, the agricultural carbon emission intensity decreases by 0.1%, but the impact is small. Therefore, it is necessary to improve the construction of a leadership mechanism, implement the development strategy of low-carbon agriculture and provide corresponding financial security and other policy suggestions to promote the coordinated development of China’s agricultural trade and low-carbon agricultural production environment.

Under the background of tighter resource and environmental constraints, whether and how land transfer can promote the green development of agriculture has become a realistic question that needs to be answered urgently. This paper analyzes the internal mechanism between land transfer and agricultural green production by using property rights theory and sustainable development theory. Taking the data of the “investigation on household energy consumption and green agricultural development” in Sichuan Province in 2022 as a sample, it empirically analyzes the impact of land transfer on agricultural green production by using OLS and 2SLS models. The results show that: (1) land inflow significantly improves the level of agricultural green production, with a unit impact of 22.3%; (2) whereas land outflow will inhibit agricultural green production, with a unit impact of 5.46%; (3) the family’s long-term agricultural labor, social capital, migrant experience, non-agricultural income, and household clean energy use have a promoting effect on agricultural green production; (4) age, education level, health level and agricultural subsidies inhibit agricultural green production; (5) the heterogeneity analysis found that the inflow of land would significantly promote the level of green agricultural production of farmers who have environmental awareness, have been village cadres, have purchased agricultural insurance, and have not suffered from agricultural disasters; (6) agricultural training, farmers’ digital literacy, and agricultural related loans have a positive and strengthened regulatory role in the impact of land transfer on agricultural green production. Based on this, this paper gets policy enlightenment from the government, market, and farmers.

The inclusiveness of digital finance brings new opportunities for the development of agriculture, rural areas, and farmers. The purpose of this paper is to clarify how digital finance influences relatively large-scale farmers’ agricultural income. Based on survey data from rural China, this paper systematically investigates the impact of digital finance on relatively large-scale farmers’ agricultural income using the Multiple Intermediary Effect Model. The findings of this study reveal that digital finance has a substantial positive influence on relatively large-scale farmers’ agricultural income, and this effect still exists after considering endogeneity and a series of robustness tests. Further mechanism analyses suggest that agricultural capital, agricultural land, and agricultural workforce play a partial mediating role between digital finance and agricultural income. The development of digital finance has a positive impact on improving agricultural capital investment and land transfer, while it has a negative impact on agricultural workforce. Moreover, the results of the grouping estimation show that digital finance has more significant effects on agricultural income for economic crops and farmers who received agricultural skills training and agricultural services. These results provide a micro explanation to promote relatively large-scale farmers’ agricultural income with the accelerated popularization of digital finance, urgently needed for most emerging countries seeking high-quality rural development.

Energy poverty due to rising energy demand is a matter of global concern. Therefore, examination of the causes of energy poverty and development of effective solutions are urgent concerns. Using survey data on livelihood development in Tibetan farming and pastoral areas in 2019, this study applied logistic and ordinary least squares models to empirically investigate the factors that influence energy poverty in Tibet. We found that energy poverty is (1) unrelated to age, gender, education, marital status, political and village cadre experience, planting, or expenditures related to religious activities; (2) negatively correlated with migrant work, village status, household income, and traffic conditions; (3) positively correlated with employment, area, and breeding; and (4) both positively and negatively affected by family residence altitude. The results offer new insights and empirical evidence for the identification and elimination of energy poverty, improving livelihoods, and promoting rural revitalisation in Tibet.

Improving well-being is a critical problem for worldwide social progress. Research on well-being effects of clean household energy consumption is of great significance for the realization of United Nation’s Sustainable Development Goals (SDGs). Due to the multifaceted role of clean household energy in enhancing well-being as a sustainable development goal, it has attracted extensive academic attention and research but still needs to be further refined through new perspectives. This paper uses data from the 2018 China Health and Retirement Longitudinal Study to conduct an empirical analysis of clean household energy consumption and residents’ well-being using an ordered probit model, the instrumental variables method, a conditional mixed process (CMP) method, and a mechanism analysis model. The results show that (1) household clean energy consumption contributes to residents’ well-being, and the results remained significant after selecting “Do you have an electric Bicycle?” as an instrumental variable to address the endogeneity question. (2) According to heterogeneity research, women’s wellbeing is impacted by clean energy consumption in the household more than men’s. Only in rural locations can clean household energy consumption significantly boost well-being; urban and suburban areas are unaffected. (3) In the mechanism analysis, health condition and depression played a mediating role on the impact of clean household energy consumption on well-being, and social contact played a moderating role on the impact of clean household energy consumption on well-being. The findings and policy recommendations in this paper are suggestive of how we can improve the well-being of residents in low- and middle-income countries and provide reference values for research in related fields around the world.