Options to enhance China’s national emission trading system design for carbon neutrality

ABSTRACT

To better align the emissions trajectory of China’s power sector with the country’s neutrality target for 2060, China’s national Emission Trading System (ETS) needs to be enhanced. This study uses a power system planning model that incorporates an output-based ETS module to explore the effects of three enhanced ETS options: 1) tightening the benchmark faster, 2) introducing auctions, and 3) transitioning to a cap-and-trade ETS. A cap-and-trade ETS can achieve deep decarbonization at the lowest cost by encouraging cheap renewables. With an increased benchmark stringency under free allocation and output-based ETS, the power sector can achieve the same level of emission reduction at a 5.2% higher cost compared to a cap-and-trade ETS. This is due to the extensive development of carbon capture, utilization, and storage (CCUS) technology, facilitated by the free allowance allocation of the output-based ETS. Introducing auctions into an output-based ETS would encourage both renewables and CCUS and increase the cost by 1.4% compared to the cap-and-trade ETS. First, we suggest that auctioning be introduced into an output-based ETS to cost-effectively encourage a diversified power supply. Subsequently, we recommend turning to a cap-and-trade ETS after 2030 to reduce the cost of decarbonization.

Key policy insights

• The same emission trajectory can be achieved with different technology mixes using different ETS designs.

• Output-based ETS with free allowance allocation leads to high decarbonization costs with large CCUS utilization.

• Introducing auctions into an output-based ETS can reduce emissions with a limited increase in cost and lead to a more diversified technology mix.

KEYWORDS:

• Emission trading system
• decarbonization
• power sector
• allowance auction

Acknowledgments

This study is partly based on a joint IEA-Tsinghua University study on ‘Enhancing China’s ETS for Carbon Neutrality: Focus on Power Sector,’ including some tables and figures reproduced from the joint report. Tsinghua University is solely responsible for this study. This study is not endorsed by the IEA in any manner.

Author contribution

Hongyu ZHANG: Software, Formal analysis, Writing. Heng LIANG: Data curation, Visualization, Writing. Da ZHANG: Methodology, Supervision, Writing. Junling HUANG: Visualization, Writing. Xiliang ZHANG: Conceptualization, Supervision, Writing.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was supported by National Natural Science Foundation of China: [grant nos 72140005, 42341202 and 71974109]; China Three Gorges Corporation research project: [grant no 202303160]; Mobility programme: [grant no M-0708].