• Energy Research

Abstract As the process of carbon reduction continues, carbon trading market in China is becoming mature and moving from fragmented pilots to a national unity. This study aims to examine whether there are return and volatility spillovers among China's carbon emissions trading pilots, by using a generalized forecast error variance decomposition as well as a spectral decomposition in VAR process. Empirical results show that there are return and volatility spillovers among China's carbon emissions trading pilots. But all of them are relatively low, with each pilot contributing or receiving no more than 1.5% of impacts in return spillover, and no more than 7% in volatility spillover, which means that the dynamics of price in each pilot are mainly driven by its own factors. However, some characteristics of spillover effect are still worth exploring. The spillover effect presents an approximate “M” shaped fluctuation trend during the period from pre- to post-compliance. In terms of frequency decompositions, return spillover is dominated by short-term effects, while volatility spillover is dominated by long-term effects. Some policy implications are also provided along with these research conclusions.

As the driving force of modern economic development, the evolution of the global energy patterns during major emergencies deserves attention. This study aims to uncover changes in global energy patterns during the COVID-19 epicenter storm. The results reveal concentrated energy trade volume in a few flows, with high-income countries holding greater influence. Amid the epicenter storm, there was a contraction in global energy trade volume, and trading patterns underwent significant shifts: (1) the global natural gas trading center shifted from the Middle East to western Africa initially, then to the United States and Russia; (2) Brazil, a crucial crude oil exporter, saw a weakened position in global crude oil exports; and (3) in the coal trading network, Australia and Russia maintained their position as trading centers throughout the storm. Swift policy adaptation is crucial for resilience and stability amid evolving global energy patterns.

Mitigating climate change requires long-term global efforts. The aim of this study is to simulate the possible paths of CO2 emissions in G20 countries and the world from 2020 to 2050, by using the STIRPAT model and SSP scenarios with different constraints (SSP baseline, SSP-3.4). The results show that: (1) the world’s CO2 emissions cannot peak in the SSP baseline scenarios, but can peak in the SSP-3.4 scenarios through four paths other than the high fossil energy consumption path; (2) for G20 countries, in the SSP baseline scenarios, 13 countries such as China, the United States, and the United Kingdom can achieve the peak, while six countries such as Argentina, India, and Saudi Arabia cannot. In the SSP-3.4 scenarios, Saudi Arabia cannot achieve the peak, while other countries can achieve the peak, and most of them are likely to achieve significant CO2 emission reductions by 2050; (3) climate goals have a crowding-out effect on other sustainable development goals, with less impact on developed countries and a greater impact on developing countries; and (4) the optimization of the energy structure and a low energy intensity can greatly advance the peak time of CO2 emissions.