中国工业部门能源相关 CO 排放的分解分析：来自 LMDI 方法的证据。
Decomposition analysis of energy-related CO emission in the industrial sector of China: Evidence from the LMDI approach.
机构信息
Asian Demographic Research Institute, Shanghai University, Shanghai, 200444, China.
School of Management and Economics Beijing Institute of Technology, Beijing, 100081, China.
出版信息
Environ Sci Pollut Res Int. 2019 Jul;26(21):21736-21749. doi: 10.1007/s11356-019-05468-5. Epub 2019 May 27.
Energy consumption and increasing CO emissions in China are mainly indorsed to the industrial sector. The objective of this study was to explore the main factors driving CO emissions in China's industry throughout 1991-2016. Based on the log-mean Divisia index (LMDI) method, this study decomposes the change of industry-related CO emissions into energy structure effect, income effect, energy intensity effect, carbon emission, and labor effect. The core results indicate that CO emissions in China's industry experienced a significant increase from 738.5 to 7271.8 Mt during 1991-2013, while it decreased to 6844.0 Mt in 2016. The income effect and labor effect are the top two emitters, which accounted for increases of 351.8 Mt and 57.8 Mt in CO emissions respectively. Additionally, the energy structure effect also played a role in increasing CO emissions. Energy intensity and carbon emission effects are the most important factors in reducing CO emissions. The policy suggestions about the different period-wise analyses in terms of economic growth, energy structure, and energy intensity are provided.
中国的能源消耗和 CO 排放的增长主要归因于工业部门。本研究旨在探讨 1991-2016 年期间中国工业 CO 排放的主要驱动因素。基于对数平均迪氏分解指数（LMDI）方法，本研究将工业相关 CO 排放的变化分解为能源结构效应、收入效应、能源强度效应、碳排放和劳动力效应。核心结果表明，1991-2013 年期间，中国工业 CO 排放量从 738.5Mt 显著增加到 7271.8Mt，而 2016 年则降至 6844.0Mt。收入效应和劳动力效应对 CO 排放的增加贡献最大，分别导致 CO 排放量增加 351.8Mt 和 57.8Mt。此外，能源结构效应也对 CO 排放的增加起到了一定的作用。能源强度和碳排放效应是减少 CO 排放的最重要因素。针对不同时期的经济增长、能源结构和能源强度，本研究提供了相应的政策建议。
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