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Experience learning from low-carbon pilot provinces in China: Pathways towards carbon neutrality

journal contribution
posted on 2024-11-02, 20:30 authored by Shengping Li, Qian Xu, Junli Liu, Liyin Shen, Jindao Chen
As one of the largest carbon emitters worldwide, China has promised to peak its carbon emissions by 2030 and achieve national carbon neutrality by 2060. In order to achieve the carbon reduction goal, the low-carbon pilot (LCP) program has been implemented in China since 2010. It is particularly significant to recognise the effectiveness of the LCP program and learn valuable experience from these LCP provinces. Therefore, this study develops a systemic experience learning approach by analysing the evolution of carbon footprint (CF) and net carbon footprint (NCF) and investigating the impact factors in representative LCP provinces. The results demonstrated that the CF of nine LCP provinces showed an upward trend from 2006 to 2015, and the NCF of eight provinces was larger than 0 except for Yunnan province, with a negative NCF. The implementation of the LCP program is effective since the average annual growth rates of CF and NCF in pilot provinces were significantly lower after they were selected as LCP provinces. Based on the identified four impact factors of CF (i.e., population, GDP per capita, industrial structure, and technology), the low-carbon experience with regional characteristics can be summarised and shared with other regions throughout the country. Accordingly, targeted guidelines are put forward from the perspectives of policy, industry structure, population, and carbon uptake. This study not only develops a new experience learning approach incorporating the regional characteristics but also provides effective pathways towards carbon neutrality.

History

Journal

Energy Strategy Reviews

Volume

42

Number

100888

Start page

1

End page

13

Total pages

13

Publisher

Elsevier

Place published

Netherlands

Language

English

Copyright

© 2022 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/bync-nd/4.0/).

Former Identifier

2006116680

Esploro creation date

2022-10-14

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