4.7 Article

Explore the influence mechanism of carbon emissions decline on energy intensity with two-layer factor decomposition method in Beijing-Tianjin-Hebei region

期刊

ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
卷 26, 期 4, 页码 4041-4055

出版社

SPRINGER HEIDELBERG
DOI: 10.1007/s11356-018-3912-z

关键词

Carbon emissions; Energy intensity; Two-layer decomposition; Influence mechanism; Policy implications; Beijing-Tianjin-Hebei

向作者/读者索取更多资源

Understanding the intrinsic mechanism behind changes on energy intensity provides insights about reducing carbon emissions and promoting the sustainable development of Beijing-Tianjin-Hebei (BTH) region. Although various studies have found a causal relationship between energy intensity and energy-related carbon emissions, the internal mechanisms are still unclear. This paper presents a comprehensive analysis of the impact of energy intensity on carbon emissions from 2005 to 2015. With an association established between logarithmic mean Divisia index (LMDI) and generalized Fisher index (GFI), two-layer factor decomposition model is proposed to explore the factor analysis in-depth. (1) LMDI method proves that energy intensity is the main contributor that reduces carbon emissions in BTH. (2) GFI model further decomposes energy intensity into five effects, namely energy substitution, technology progress, labor productivity, capital substitution, and labor-capital resources allocation. (3) The results reveal that the effect of capital-energy substitution in declining energy intensity surpasses technology progress. (4) Energy-labor substitution has increased energy intensity, while energy-energy substitution is negligible. For the coordinate development of BTH, the government should aim at energy intensity and attach importance to encouraging entrepreneurship, accelerating the construction of carbon trading market, allocating resources rationally, and guiding the capital flow into energy-efficient direction.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.7
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据