With the serious worldwide problem of carbon emissions, carbon emissions’ control and trade have become necessary policies adopted by the governments, after the establishment of the EU Emissions Trading System (EU ETS), China has also implemented a similar carbon emission trading pilot policy which plays a vital role in environmental regulation and influences enterprise behaviors, so this paper will put more focus on the impact of this policy on the enterprise innovation. In this paper, we construct a theoretical model and use the “Chinese Carbon Emissions Trading Pilot Policy” as a quasi-natural experiment to accurately identify the net causal effect of this environmental policy on enterprise innovation. Moreover, we use the synthetic control and difference-in-differences methods to eliminate the endogeneity to a large extent and conduct the robustness tests, difference-in-differences method, placebo test, and permutation test to respectively confirm these results. The results show that the implementation of carbon emissions trading policy will significantly reduce the enterprise innovation in general, this conclusion is contrary to the EU ETS’s effect, which is confirmed by plenty of previous empirical study. However, this policy has different effects across enterprises of different industries and different types of innovation. It can promote enterprise innovation of environmental industry, but it will inhibit enterprise innovation of non-environmental industry; besides, it can promote the development of green technical innovation and inhibit non-green technical innovation, which is basically identical to the causal effect of EU ETS.

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.

In the face of increasingly severe climate change and its disastrous effects, how to effectively tackle it and reduce carbon dioxide emissions has become an important global issue. Clean development mechanism (CDM) project implementation provides an opportunity for more developing countries to actively participate in global climate governance. As the largest global emitter of carbon dioxide, have China’s CDM projects slowed down carbon dioxide emissions? In order to answer this question, the study constructs panel data at the provincial level from 2000 to 2017 to investigate the emission-reduction effects of China’s CDM projects. Results showed that China’s CDM projects’ implementation significantly reduced carbon dioxide emissions per unit of gross domestic product (GDP) and the growth rate of carbon dioxide emissions. The emission reduction effects of different types of CDM projects have obvious heterogeneity. In addition, this study further found that China’s CDM projects’ implementation can not only effectively substitute traditional fossil energy, but also improve energy-utilization efficiency.

How to better explore a diversity of emissions reduction paths has become the key to China achieving carbon peak and carbon neutralization goals as well as transforming the existing energy structure as soon as possible. Based on this, from the perspective of information flow, this study used the differences-in-differences method (DID) to identify the “net effect” of the carbon emissions reduction caused by China’s environmental information disclosure. The results showed the following: first, environmental information disclosure could effectively promote regional carbon emissions reductions and had a better effect on the central and western regions and low carbon emissions density regions. Second, the achievement of carbon emissions reduction targets was mainly attributed to the positive impact of information disclosure in the process of “coal withdrawal.” Finally, this study also found that environmental information disclosure helped to promote the positive effect of clean energy development on “coal withdrawal,” and the promotion of public awareness regarding environmental supervision helped to strengthen the external impact of environmental information disclosure on regional carbon emissions reduction.

Environmental violation by enterprises is a common problem in environmental management worldwide. To restrict enterprises' environmental pollution behaviors, China has implemented a public supervision system based on environmental information publicity, which guides the public to participate in environmental governance and supervises enterprises' environmental pollution behaviors. This study exploits a quasi-natural experiment based on the disclosure policy of the Pollution Information Transparency Index in China from 2008 and the difference-in-differences method to evaluate the disclosure effect of public supervision on enterprises' environmental violations, and to examine its environmental benefits and their realization path. We find that the public supervision system is conducive to the disclosure of enterprises' environmental violations. At the same time, public supervision has achieved the expected environmental benefits, mainly realized by reducing enterprises' output to reduce polluting emissions, and this mechanism is more obvious for high-polluting enterprises.

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.