For sustainable agricultural development, increasing efforts are put on promoting agricultural mechanization and green agricultural development all over the world. Based on the panel data of Chinese provincial agriculture from 2002 to 2018, the System Generalized Method of Moments model and mediation model are constructed to explore the paths of agricultural mechanization affecting green agricultural development. The results show that agricultural mechanization can not only promote the green agricultural development directly but also indirectly by transferring the agricultural labor force and increasing fertilizer input. However, because of the surge of pesticide demand, agricultural mechanization also leads to serious pollution indirectly. With the development of large-scale agricultural machinery, the direct promotion of agricultural machinery on green agricultural development will be more significant. However, it will be less efficient to substitute more agricultural labor force with machinery power. The problem of pesticide abuse will also become more serious. Therefore, it is important for green agricultural development to encourage human capital investment in agricultural mechanization. In addition, more attention should be paid to improving the input efficiency of fertilizers and pesticides so that agriculture will be sustainable in production and the ecological environment.

In the context of China’s dual carbon target, Beijing, as the capital of China, should play an exemplary role in carbon emission reduction. On the premise of optimizing high-emission sectors such as coal and industry, Beijing is still a certain distance from the goal of carbon neutrality. Therefore, on the basis of Beijing’s energy resource endowment, considering Beijing’s economic development and carbon neutrality goals and scientifically and reasonably planning Beijing’s carbon emission reduction path are important tasks. We construct an energy structure optimization model to achieve the goal of carbon neutrality by 2050. The model analysis concludes that the residents and transportation sectors will account for a large proportion of Beijing’s total carbon emissions in the future. To achieve the goal of carbon neutrality, the electricity substitution of fossil energy and the high proportion of external power are two necessary measures, and the optimal path of carbon emission reduction is proposed.

The low-carbon transformation of the power industry is of great significance to realize the carbon peak in advance. However, almost a third of China’s CO₂ emissions came from the power sector in 2019. This paper aimed to identify the key drivers of CO₂ emissions in China’s power industry with the consideration of spatial autocorrelation. The spatial Durbin model and relative importance analysis were combined based on Chinese provincial data from 2003 to 2019. This combination demonstrated that GDP, the power supply structure and energy intensity are the key drivers of CO₂ emissions in China’s power industry. The self-supply ratio of electricity and the spatial spillover effect have a slight effect on increasing CO₂ emissions. The energy demand structure and CO₂ emission intensity of thermal power have a positive effect, although it is the lowest. Second, the positive impact of GDP on CO₂ emissions is decreasing, but that of the power supply structure and energy intensity is increasing. Third, the energy demand of the industrial and residential sectors has a greater impact on CO₂ emissions than that of construction and transportation. For achieving the CO₂ emission peak in advance, governments should give priority to developing renewable power and regional electricity trade rather than upgrading thermal power generation. They should also focus on promoting energy-saving technology, especially tapping the energy-saving potential of the industry and resident sectors.

The deepening of industry-education integration can realize the organic connection of the education chain, talent chain, industrial chain, and innovation chain. It is an essential pathway for universities to develop innovative talents that align with the demands of industrial transformation and high-quality development. Many higher education institutions face challenges in the process of industry-education integration for innovative talent cultivation. For example, the training goals of business-school partnerships are not unified, and the dual-subject training mode is not explicit, etc. The research sample is based on typical case studies from institutions and data collected through questionnaires. The research constructs a talent cultivation mechanism for innovative industry-education integration. The mechanism primarily encompasses five aspects: target positioning, theoretical teaching system, practical teaching system, joint training, and evaluation mechanism. The research employs a combination of survey questionnaires and fuzzy set qualitative comparative analysis for empirical investigation. The research finds that the practical teaching system is a necessary condition for promoting the cultivation of collaborative innovation talents between schools and enterprises. Under the joint influence of the antecedent conditions, three configuration paths for promoting the cultivation of collaborative innovation talents between schools and enterprises have been formed.