中国能源消费碳排放变化的驱动因素研究

将DEA中基于能源投入的Shephard距离函数引入到LMDI分解模型中,建立了1995~2010年中国6大产业能源消费碳排放7因素分解模型.研究结果显示, 产业结构效应、经济产出效应、人口规模效应、能源绩效效应对碳排放的增加具有一定的拉动作用,其中经济产出效应的累积贡献率最大为135%,产业结构效应、人口规模效应、能源绩效效应对碳排放累积贡献率分别为10.74%、9.39%、0.65%;潜在能源强度效应对碳排放下降的累积贡献率最大为54.6%,说明产业能源强度的调整空间较大,且抑制效应逐年增强;能源结构效应、能源技术进步效应对我国碳减排的累积贡献率分别为0.2%和1.04%,贡献微弱,亟待提高;从产业层面研究发现,农林牧渔业、建筑业、批发零售和住宿餐饮业和其他行业的低碳发展较好,工业、交通运输仓储和邮政业低碳发展不佳,工业始终是我国碳排放的主要来源.

Driving factors of carbon emissions from energy consumption in China-Based on LMDI-PDA method

The DEA-Shephard distance function of energy input was taken into a seven-factor LMDI decomposition model, which was built of carbon emissions from the energy consumption of six major industries in China from 1995to 2010.The empirical results revealed that industrial structure, economic output, population size, and energy efficiency had a pulling effect on industrial carbon emissions from energy consumption, and the cumulative effect of economic output had the maximum contribution of 135%. The cumulative effects of industrial structure, population scale, and energy efficiency on carbon emissions were 10.74%, 9.39%, and 0.65% respectively. Energy intensity with a cumulative contribution of 54.6% has the largest potential to reduce carbon emissions, which meant industrial energy intensity had larger room for improvement, and the inhibitory effect was increasing; the cumulative contributions of energy structure and energy technological progress to China's carbon emissions reduction were 0.2% and 1.04%, they had weak contributions, so needed to be improved; In terms of the industrial carbon reduction, agriculture, forestry, animal husbandry and fishery, construction, wholesale and retail and catering industry and other industries had been better in reducing carbon emissions. Transportation, storage and postal industry had been lagging behind in carbon reduction. Industrial carbon emissions had always been the major source of carbon emissions in China.