Socioeconomic impact assessment of China's CO2 emissions peak prior to 2030

Mi, Zhifu, Wei, Yi-Ming, Wang, Bing, Meng, Jing, Liu, Zhu, Shan, Yuli, Liu, Jingru and Guan, Dabo (2017) Socioeconomic impact assessment of China's CO2 emissions peak prior to 2030. Journal of Cleaner Production, 142 (4). 2227–2236. ISSN 0959-6526

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Abstract

China is the largest emitter of carbon emissions in the world. In this paper, we present an Integrated Model of Economy and Climate (IMEC), an optimization model based on the input-output model. The model is designed to assess the tradeoff between emission deceleration and economic growth. Given that China's projected average growth rate will exceed 5% over the next two decades, we find that China may reach its peak CO2 emissions levels by 2026. According to this scenario, China's carbon emissions will peak at 11.20 Gt in 2026 and will then decline to 10.84 Gt in 2030. Accordingly, approximately 22 Gt of CO2 will be removed from 2015 to 2035 relative to the scenario wherein China's CO2 emissions peak in 2030. While this earlier peaking of carbon emissions will result in a decline in China's GDP, several sectors, such as Machinery and Education, will benefit. In order to reach peak CO2 emissions by 2026, China needs to reduce its annual GDP growth rate to less than 4.5% by 2030 and decrease energy and carbon intensity levels by 43% and 45%, respectively, from 2015 to 2030.

Item Type:	Article
Uncontrolled Keywords:	carbon emissions,peak,input-output,optimization model,integrated assessment model,china,sdg 8 - decent work and economic growth,sdg 13 - climate action ,/dk/atira/pure/sustainabledevelopmentgoals/decent_work_and_economic_growth
Faculty \ School:	Faculty of Social Sciences > School of Global Development (formerly School of International Development) Faculty of Science > School of Environmental Sciences
UEA Research Groups:	Faculty of Social Sciences > Research Centres > Water Security Research Centre
Depositing User:	Pure Connector
Date Deposited:	10 Dec 2016 00:05
Last Modified:	21 Oct 2022 08:31
URI:	https://ueaeprints.uea.ac.uk/id/eprint/61690
DOI:	10.1016/j.jclepro.2016.11.055

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