Estimating the carbon abatement potential of economic sectors in China

Shiwei Yu, Lawrence Agbemabiese and Junjie Zhang

Applied Energy, 2016, vol. 165, issue C, 107-118

Abstract: This study estimates the carbon abatement potential of 43 Chinese economic sectors by establishing and utilizing an environmental learning curve (ELC) model of carbon intensity. The model selects energy intensity, per capita value added and fuel consumption mix as the independent variables and obtains its learning coefficients using panel data regression. Based on this model, the carbon abatement potential of 43 economic sectors in 2020 is estimated for business-as-usual (BAU) and planned scenarios. The findings show that: (1) the established learning curves adequately simulate the carbon intensity of different sectors; (2) energy intensity has the strongest positive learning ability among the three variables for all sectors. A reduction in energy intensity will lead to reduced carbon intensities for 42 sectors (all except the agriculture sector). However, an increase in sectoral value added will make it possible to reduce carbon intensity in 34 sectors. Reducing the proportion of coal energy will result in decreased carbon intensities in only ten sectors; (3) the average carbon intensity reduction potential for 43 sectors in 2020 will be 33.0% and 39.0% based on 2012 in two different scenarios. Sectors related to the manufacture of food, medicine, beverages and chemical fiber have the largest carbon intensity potential among the 43 sectors.

Keywords: Carbon emission; Abatement potential estimation; Sectors; Multivariable learning environmental curve (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (17)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:appene:v:165:y:2016:i:c:p:107-118

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DOI: 10.1016/j.apenergy.2015.12.064

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