As a major carbon dioxide-emitting country, China set carbon trading market to reduce enterprise carbon emissions through the rational allocation of carbon quotas among different enterprises and regions. The market has also conducted a preliminary exploration for the country to achieve carbon dioxide emissions peak in 2030 and carbon neutrality in 2060 while actively addressing the challenges of global climate change. This study analysed the emission reduction effect of China's carbon trading pilot policy, especially the role of carbon quota and carbon trading price. The analysis used county-level panel data from 1997 to 2017, regarded the implementation of the carbon trading pilot policy as a quasi-natural experiment, and used the difference-in-differences method. The results showed that, first, the policy implementation not only reduced regional carbon emissions but also inhibited carbon dioxide emissions per capita, with long-term effects. Second, the carbon emission reduction effect brought by the carbon pilot policy showed significant heterogeneous results with the different degrees of regional carbon emissions and environmental supervision. The effect was greater in areas with higher carbon emission density and stronger legal supervision. Third, the difference in carbon quota allocations resulted in different emission reduction effects, among which the historical method had the strongest effect. The carbon quota price and number of enterprises participating carbon trading market were the key factors affecting carbon emission reduction.

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.

Nowadays environmental issues have been of great concern to the world, among which the problem of global warming caused by greenhouse gas emissions is particularly prominent. All countries in the Kyoto Protocol and the Paris Agreement have committed to control greenhouse gas emissions, and China, as the largest carbon emitter, has assumed a heavier burden. China has been striving to develop low-carbon technologies such as hydrogen, nuclear, wind, and solar energy, but the most attention should be paid to CCUS, which many scholars have high expectations that CCUS can help China reduce emissions to some extent. Therefore, this paper presents a prediction that CCUS can reduce 3.8% of carbon emissions for China in 2040 when CCUS emission reductions increase at a rate of 30%. The power and chemical industries could reduce carbon emissions by 2.3% and 17.3%, respectively.

With the frequent occurrence of extreme weather in cities, economic, ecological and social activities have been greatly impacted. The adverse effects of global extreme climate and effective governance have attracted more and more attention of scholars. Considering the differences between developed and developing countries in climate response capacity, a key issue is how to encourage developed countries to provide adequate assistance to developing countries and enhance their enthusiasm to participate in addressing climate change challenges. Given this background, we evaluated the carbon emission reduction effects of developing countries before and after a “quasi-natural experiment” which involved obtaining the assistance of climate-related funding from developed countries. Specifically, we analyzed the assistance behavior for recipient countries and found that climate assistance can effectively reduce the carbon emissions level of recipient countries, and this result has a better impact on non-island types and countries with higher levels of economic development. Furthermore, the achievement of this carbon emissions reduction target stems from the fact that climate assistance has promoted the optimization of the energy structure of recipient countries and promoted the substitution of renewable energy for coal consumption. In addition, climate-related development finance plays a significant role in promoting the scientific and technological level of recipient countries, especially the development impact of the adaptive climate-related development finance. Therefore, this paper suggests that the direction of climate assistance should focus more on island countries and countries with low economic development level, and pay more attention to the “coal withdrawal” of recipient countries and climate adaptation field.

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.