4.7 Article

Drivers of carbon emission intensity change in China

期刊

RESOURCES CONSERVATION AND RECYCLING
卷 129, 期 -, 页码 187-201

出版社

ELSEVIER SCIENCE BV
DOI: 10.1016/j.resconrec.2017.10.035

关键词

SDA; Quantile regression; Carbon emission intensity; China

资金

  1. National Natural Science Foundation of China [71573254]
  2. Fundamental Research Funds for the Central Universities [2015XKMS091]

向作者/读者索取更多资源

Carbon emissions per unit of GDP (also called carbon emission intensity, CEI) can be utilized to measure regional carbon emission performance. In this study, structural decomposition analysis (SDA) and quantile regression are employed to investigate the factors that drive changes in CEI in China. Based on input-output SDA, CEI in China during 1992-2012 is decomposed from the perspectives of the total economy and economic sectors. The results specify that the industrial sector is the key sector for energy. conservation and emission reduction. Energy efficiency contributes the most to CEI reduction, whereas input structure, final demand structure, and final product structure are factors that hinder reductions. Furthermore, energy mix, technical progress, industrialization index, and final consumption rate are introduced as proxy variables. To reveal the changes of influencing factors with CEI increasing, the effects of these proxy variables on CEI are explored by quantile regression with panel data of 30 provinces from 1999 to 2014. The results indicate that energy mix, industrialization index, and final consumption rate have positive effects on CEI. As CEI increases, the effect of energy mix increases gradually, whereas the effect of industrialization index tends to decrease, and the effect of final consumption rate increases initially and then decreases. Technical progress and urbanization are both effective in reducing CEI. With CEI increasing, the negative effect of technical progress presents a trend of decrease, then increase. Conversely, the negative effect of urbanization is through the process of increase, then decrease.

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