Decomposed Driving Factors of Carbon Emissions and Scenario Analyses of Low-Carbon Transformation in 2020 and 2030 for Zhejiang Province

Chuyu Xia, Yan Li, Yanmei Ye, Zhou Shi and Jingming Liu
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Chuyu Xia: Institute of Land Science and Property, School of Public Affairs, Zhejiang University, Hangzhou 310058, China
Yan Li: Institute of Land Science and Property, School of Public Affairs, Zhejiang University, Hangzhou 310058, China
Yanmei Ye: Institute of Land Science and Property, School of Public Affairs, Zhejiang University, Hangzhou 310058, China
Zhou Shi: Institute of Agricultural Remote Sensing and Information Technology Application, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou 310058, China
Jingming Liu: School of Public Policy and Administration Department of Public Administration, Xi’an JiaoTong University, Xi’an 710049, China

Energies, 2017, vol. 10, issue 11, 1-16

Abstract: Climate change has gained widespread attention, and the rapid growth of the economy in China has generated a considerable amount of carbon emissions. Zhejiang Province was selected as a study area. First, the energy-related carbon emissions from 2000 to 2014 were accounted for, and then the Logarithmic Mean Divisia Index (LMDI) decomposition model was applied to analyse the driving factors underlying the carbon emissions. Finally, three scenarios (inertia, comparative decoupling and absolute decoupling) for 2020 and 2030 were simulated based on the low-carbon city and Human Impact Population Affluence Technology (IPAT) models. The results showed (1) carbon emissions increased by 1.66 times from 2000 to 2014, and trends of carbon emissions were used to divide the study period into three phases (rapid, medium growth and slow decrease phases, with annual growth rates of 12.60%, 4.77% and ?1.24%, respectively); (2) the energy intensity effect from 2000–2011 inhibited carbon emissions but was exceeded by the economic output effect, which increased emissions, whereas the energy intensity effect from 2011–2014 outweighed the economic output effect; (3) the scenario analyses revealed that both the comparative and absolute decoupling scenarios would remain consistent with the carbon emissions boundaries in 2020 and 2030, but the comparative decoupling scenario was more reasonable for sustainable development. In addition, appropriate design of emission trading scheme could help to achieve the comparative decoupling by financial incentives.

Keywords: carbon emissions; LMDI; scenario analysis; low-carbon city; IPAT; carbon emission boundaries (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (10)

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