4.7 Article

The change in energy and carbon emissions efficiency after afforestation in China by applying a modified dynamic SBM model

期刊

ENERGY
卷 216, 期 -, 页码 -

出版社

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.energy.2020.119301

关键词

Energy and carbon emission efficiency; Carbon sequestration; Afforestation; Modified dynamic SBM model

资金

  1. Institute for Industrial Economy of Intelligent Manufacturing, Changzhou Key Laboratory of Industrial Internet and Data Intelligence [CM20183002]

向作者/读者索取更多资源

Despite being the largest energy consumer and carbon emitter in the world, China has experienced the largest increase in green leaf area. Afforestation has been highlighted as the most effective strategy for improving China's energy and carbon emissions efficiency, especially in provinces where significant changes have been observed.
Although China is the largest energy consumer and carbon emitter in the world, it also has experienced the largest increase in green leaf area, as evidenced from 2007 to 2017 when it hit 66.156 million hectares, accounting for 6.891% of the country's total land area. This study considered carbon sequestration in afforestation and introduced it as an exogenous variable into a modified dynamic Slacks-Based Measure (SBM) model to find the change in China's energy and carbon emissions efficiency. Different from previous studies, China's western region had the best efficiency value of 0.718, while the eastern and central regions were 0.699 and 0.590. In some provinces with more restoration of trees, their efficiency value changed greatly, such as Yunnan, Qinghai, Inner Mongolia and Guizhou. The results highlighted that afforestation has become the most effective strategy for China to improve energy and carbon emissions efficiency and for dealing with climate change, which can be ensured through carbon tax and market mechanism policies. (C) 2020 Elsevier Ltd. All rights reserved.

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