In order to reduce carbon emissions for sustainable development, we analyzed the impact of China’s digital economy development on carbon emissions. Based on the panel data of 30 Chinese provinces from 2009 to 2019, we measured the level of development of China’s digital economy using the entropy method. The relationship between the digital economy and carbon emissions was analyzed from multiple perspectives with the help of the fixed-effects model, the mediated-effects model and the spatial econometric model. The results indicate that the digital economy plays a significant inhibitory role in carbon emissions. In addition, the digital economy inhibits carbon emissions through the innovation effect and the industrial structure upgrading effect. Moreover, the digital economy exhibits a significant spatial spillover effect in dampening carbon emissions. Finally, there is regional heterogeneity in the direct and spatial spillover effect. The findings provide a basis for the digital economy to contribute to carbon emissions reduction and provide relevant policy references for achieving carbon neutrality and sustainable development.

In order to achieve low carbon transformation and green development in agriculture, we analyzed the effects of different types of socialized services on agricultural carbon emissions based on provincial panel data from 2010 to 2020 in China. We further analyzed the possible ways for agricultural social services to reduce the intensity of agricultural carbon emissions with the help of mediating effect model. The results show that socialized services can provide basic services, production and operation services, financial services, and circulation services for the agricultural production chain, which can significantly reduce the agricultural carbon emissions intensity. The results of the intermediation effect suggest that socialized services can break the labor constraint by promoting the scale effect, and thus reduce the agricultural carbon emissions intensity. However, the mediation effect of technology diffusion is not significant. The reason is that although the diffusion of agricultural technology can improve the efficiency of resource utilization, the diffusion of technology also leads to the use of elements such as high concentrations of chemicals and heavy agricultural tools which may increase carbon emissions. In addition, the effect of socialized services on reducing agricultural carbon emissions intensity shows obvious spatial heterogeneity, with the reduction gradually increasing from coastal to inland provinces and from eastern to western regions.

In order to clarify the coordinated development status between the digital economy and the ecological environment in the context of rapid development of the digital economy and frequent ecological environment problems, we constructed an evaluation system using data related to the digital economy and the ecological environment in China from 2011 to 2019. And the level of coordinated development is calculated with the help of entropy method and the Coupling Coordinated Development (CCD) model. Further, we analyzed the spatial and temporal evolutionary trends of their coordinated development levels with the kernel density analysis and the Dagum Gini coefficient decomposition. The results of the entropy method and CCD show that both the level of digital economy, the level of ecological environment and the level of coupling coordination between the two have increased. And the level of coordinated development shows regional heterogeneity, with the highest in the eastern region, followed by the central region, and the lowest in the western region. The results of the kernel density analysis show that there is heterogeneity in the development process of CCD scores over time across regions. The results of the Dagum Gini coefficient decomposition show that the overall inter-regional differences, as well as intra-regional differences, are fluctuating and decreasing. And the overall imbalance mainly comes from the differences in development levels between regions. The analysis of the above methods provides a basis for understanding the spatial and temporal evolution characteristics of the coordinated development of China’s digital economy and ecological environment. And it also provides relevant policy recommendations for promoting coordinated and sustainable development among regions.