Factor Decomposition And Decoupling Effect Of China's Industrial Carbon Emissions

At present,all countries in the world are taking measures to reduce carbon dioxide emissions to cope with climate change and its impact.The Chinese government also promised at the Paris Climate Change Conference that by 2030,the carbon dioxide emissions per unit of GDP will fall by 60%to 65%compared to 2005.According to BP World Energy Statistics(2019),carbon emissions from global energy consumption increased by 2.0%in 2018,reaching the highest growth rate in the past seven years.China alone contributed 27.8%of total C02 emissions,ranking first among the world's largest carbon emitters for 13 consecutive years.As the world's largest carbon emitter in recent years,China plays a vital role in the global low-carbon transformation process.The industrial sector is also a major energy consumption and carbon emitter in China.Over the years,the proportion of energy consumption in the industrial sector has been higher than 65%in the country,and carbon emissions accounted for more than 70%of total emissions.Therefore,quantifying the driving factors and decoupling effects of carbon emissions in China's industrial sector has important guiding significance for the industrial sector to achieve low carbon emission reduction targets and sustainable economic development.In this paper,we use the generalized divisia index decomposition method(GDIM)to analyze the driving factors of China's industrial carbon emissions from 2000 to 2016,and then explore the driving force of industrial added value,energy consumption,population,technological progress,output carbon intensity,energy consumption carbon intensity,per capita carbon emissions,technological progress carbon intensity,per capita added value and energy intensity on industrial carbon emission from two aspects:phase analysis and cumulative contribution analysis.On this basis,a decoupling-effort model was constructed combing with the DPSIR framework to measure the decoupling effect of industrial carbon emissions and the decoupling contribution of various driving factors.The results show that,first,from 2000 to 2016,output scale effect,energy consumption scale effect,population size effect,technological progress effect and per capita carbon emission effect play a positive role in the change of industrial carbon emissions,while output carbon intensity effect,technological progress carbon intensity effect,per capita added value effect and energy intensity effect play a negative driving role,and the positive and negative driving effects of the carbon intensity effect of energy consumption are appear.Second,the cumulative amount of industrial carbon emissions in China is increasing,but the cumulative growth rate is slowing down.Among them,the cumulative contribution of output scale effect is the largest,and the cumulative contribution of technological progress effect is second.Third,the decoupling effect of China's industrial carbon emissions presents a phased feature of "no decoupling-weak decoupling-strong decoupling".Among them,the industrial carbon emission showed a "W" type stepped growth without decoupling effect from 2000 to 2011,a "?" type growth from 2011 to 2014 with a weak decoupling effect,and an increasing growth from 2014 to 2016 with a strong decoupling effect.Fourth,in the decoupling contribution of various driving factors,technological progress effect,energy consumption scale efect and per capita carbon emission effect are the main factors that hinder the decoupling of industrial carbon emissions,while output carbon intensity effect and technological progress carbon intensity effect are key factors in achieving decoupling of industrial carbon emissions.The research results of this paper provide a reasonable reference for China's industrial sector to achieve the overall low-carbon goal and formulate corresponding emission reduction policies and measures.Compared with the existing research,the main research contribution of this paper are as follows:(1)In terms of research methods,the generalized divisia index decomposition method(GDIM)was used for the first time to analyze the driving factors of China's industrial carbon emissions.GDIM not only considers the dependence of various factors,but also considers the impact of other absolute and potential factors on industrial carbon emissions.(2)In terms of the decoupling effect analysis,based on the GDIM and the DPSIR framework,this paper constructs the decoupling effort model,analyzes the actual decoupling effect of the government's emission reduction efforts and the role of various factors in the decoupling of industrial carbon emissions,comprehensively reflects the current decoupling of industrial carbon emissions,and points out the direction for strong decoupling of China's industrial carbon emissions.(3)In terms of factor selection,this paper fully consider 10 key factors such as energy consumption scale,carbon emission intensity and technological progress,and measure the impact of each absolute factor on carbon emission changes,and simultaneously study all absolute and relative factors to make the analysis results more accurate and reliable.