The construction industry plays a crucial role in China’s fulfillment of the goal of achieving “carbon neutrality” in 2060. Based on the data of energy and building materials consumption of the construction industry in China and 30 provinces from 2008 to 2018, this paper constructs a model for measuring provincial CO₂ emissions of China’s construction industry and establishes a Kuznets curve and elastic decoupling model of the industry’s CO₂ emissions. The analysis based on the models shows that: (1) the CO₂ emissions of China’s construction industry show a trend of increasing first and then decreasing; (2) in terms of the decoupling effects, most provinces are in a weak decoupling status of CO₂ emissions; and (3) the Kuznets curve of the provincial construction industry shows an inverted “U” shape in recent years, and it is predicted that the CO₂ emissions of the construction industry will reach the peak in 2034. It is possible for the construction industry to achieve “carbon neutrality”, but long-term efforts must be made for strategic planning, policies and regulations, industry standards, etc.

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.

This paper investigates the development trends and variation characteristics of China’s economy, energy consumption and carbon emissions from 2007 to 2030, and the impacts on China’s economic growth, energy consumption, and carbon emissions under the carbon tax policy scenarios, based on the dynamic computable general equilibrium (CGE) model. The results show that during the simulation period, China’s economy will keep a relatively high growth rate, but the growth rate will slow down under the benchmark scenario. The energy consumption intensity and the carbon emissions intensity per unit of Gross Domestic Product (GDP) will continually decrease. The energy consumption structure and industrial structure will gradually optimize. With the economic growth, the total energy consumption will constantly increase, and the carbon dioxide emissions are still large, and the situation of energy-saving and emission-reduction is still serious. The carbon tax is very important for energy-saving and emission-reduction and energy consumption structure optimization, and the effect of the carbon tax on GDP is small. If the carbon tax could be levied and the enterprise income tax could be reduced at the same time, the dual goals of reducing energy consumption and carbon emissions and increasing the GDP growth can be achieved. Improving the technical progress level of clean power while implementing a carbon tax policy is very meaningful to optimize energy consumption structure and reduce the carbon emissions, but it has some offsetting effect to reduce energy consumption.

The construction of charging infrastructure has a positive effect on promoting the diffusion of new energy vehicles (NEVs). This study uses natural language processing (NLP) technology to explore consumer preferences for charging infrastructure from consumer comments posted on public social media. The findings show that consumers in first-tier cities pay more attention to charging infrastructure, and the number of comments accounted for 36% of the total. In all comments, consumers are most concerned about charging issues, national policy support, driving range, and installation of private charging piles. Among the charging modes of charging piles, direct current (DC) fast charging is more popular with consumers. The inability to find public charging piles in time to replenish power during travel or high energy consumption caused by air conditioning is the main reason for consumers’ range anxiety. Increasing battery performance, improving charging convenience, and construction of battery swap station are the main ways consumers prefer to increase driving range. Consumers’ preference for charging at home is the main reason for their high attention to the installation of private charging piles. However, the lack of fixed parking spaces and community properties have become the main obstacles to the installation of private charging piles. In addition, consumers in cities with different development levels pay different amounts of attention to each topic of charging infrastructure. Consumers in second-tier and above cities are most concerned about charging issues. Consumers in third-tier and above cities pay significantly more attention to the installation of private charging piles than consumers in fourth-tier and fifth-tier cities. Consumers in each city have almost the same amount of attention to driving range.

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.