Nan Li

This paper explores the impact of China's energy Internet development on carbon emission reduction and its internal transmission mechanism, and uses panel data of 30 provinces from 2000 to 2020 to construct comprehensive development indicators of energy Internet through entropy weight method for empirical test. The results show that the development of energy Internet can promote carbon emission reduction, and the increase of renewable energy utilization is an important mechanism for the comprehensive development level of energy Internet to restrain carbon emissions. The heterogeneity analysis shows that, according to the degree of carbon emissions, the energy Internet has obvious effect on carbon emission reduction in regions with low carbon emissions and regions with moderate carbon emissions. According to economic region, the development of energy Internet can significantly curb carbon emissions in the western region. Finally, it is found that in the context of the development of energy Internet, the development of renewable energy can promote the consumption of natural gas and improve the efficiency of energy conversion. In addition, the government's emphasis on regional technological development can bring external reinforcement effect on carbon emission reduction. The research expands the discussion of diversified carbon emission reduction paths, promotes the explanation of the effect and influence mechanism of energy Internet to promote carbon emission reduction, and helps to provide beneficial policy enlightenment for the adjustment of the layout of energy Internet in China to better help achieve the goal of carbon neutrality.

Previously conducted studies have established that the digital economy has a one-way inhibition effect on carbon emissions. Against this background, this paper aims to analyze the coordinated development effect of the interaction between the digital economy and carbon emissions reduction. The entropy weight method, coupling and coordination degree model, Dagum Gini coefficient and Moran’s I index have been carried out as research methods in this paper. The results showed that: (1) The coupling and coordination of China’s digital economy and carbon emissions reduction shows an overall growth trend, but the coupling and coordination among regions, provinces and cities show a large imbalance. (2) In the sample period, the overall difference in the coupling and coordination between digital economy development and carbon emissions reduction shows an expanding trend, and the overall difference results are attributed to regional differences. (3) There is a significant spatial correlation in the coupling and coordination degree of digital economy development and carbon emissions reduction among cities. The paper systematically grasps the status of coupling and coordination development, the source of difference and spatial correlation between the digital economy and carbon reduction in Chinese cities. A dependence relationship has been established, which is digital economy development and carbon emissions reduction, and an interactive promotion pattern has been revealed between the digital economic system and the carbon emissions reduction system.

Driven by the information technology revolution, using artificial intelligence to promote intelligent manufacturing while achieving carbon emissions reduction is increasingly the focus of international attention. Given this, based on the fact that China’s industrial manufacturing is more intelligent, this paper uses industrial sector data and robot data from 2000 to 2017 to examine the impact of intelligent manufacturing on industrial carbon dioxide emissions and to discuss its internal mechanism. The research found that intelligent manufacturing significantly inhibits carbon dioxide emissions in the industrial sectors. The emission reduction effect is more obvious in industries with higher carbon emissions and intelligence. The mechanism test shows that intelligent manufacturing mainly achieves industrial emission reduction by reducing fossil energy consumption in the production process and improving energy use efficiency. The research findings of this paper provide favorable evidence for using new technologies, such as artificial intelligence, to achieve carbon emissions reduction, and validate the importance of intelligent manufacturing in tackling climate change in the future. It provides an essential reference for developing countries to use artificial intelligence for their carbon emissions reduction goals.