摘要
仅次于工业能源消费总量的生活消费用能作为第二用能部门,日益受到广泛关注.探究生活能源消费变化及其影响因素,并比较各区域的空间差异是预测生活能源消费趋势、制定居民节能措施的前提.本文运用LMDI分解模型,对全国和29个省份的2000 -2012年间的生活能源消费密度变化进行因素分解,分解成能源消费结构、能源强度、经济发展水平三个影响因素,分别表示结构效应、技术效应、经济效应,并通过构建四象限法评价空间差异,在此基础上,基于影响因素未来发展的两种情景,预测组合的8 种情景下2016-2030 年间区域生活能源消费密度的变化趋势.研究结果显示%十五”时期和“十-五”时期,全国生活能源消费密度变化率由52. 43 % 降为43. 71M .在影响各地区生活能源消费密度的三因素中,经济发展水平对生活能源消费密度变化产生较大的正向经济效应,对各区域的贡献度均值由63.47 % 上升为67. 28% , 能源强度产生由正转负的技术效应,对各区域贡献度均值由4.19% 降为-24.89%, 能源结构产生负向结构效应,对各区域贡献度均值由-20.36 % 变为-0.83% .文章表明中国各区域的生活能源消费密度增长趋势放缓,且密度变化由经济和技术拉动型变为经济和结构拉动型.各区域间经济效应差异变小且比较稳定,而技术效应差异缩小,结构效应差异变大.8种情景预测结果显示经济因素仍然是导致居民生活能源消费密度增加的主要驱动因素.
As the second largest energy-consuming sector after industry,residential energy consumption has received increasing attention in China.To predict the consumption trend and develop residential energy-saving measures,the variation of residential energy consumption and its influence factors were explored,and the spatial differences among regions were contrastively analyzed. According to Logarithmic Mean Divisia Index(LMDI)model,the variation of energy consumption density in the whole nation and 29 provinces from 2000 to 2012was decomposed into three influence factors,which include energy consumption structure,energy intensity and economic level,respectively representing structure effect,technology effect and economy effect.The four-quadrant method was employed to evaluate the provincial spatial disparities.Variation tendency of residential energy consumption density over the period 2016-2030 were predicted as eight scenarios.Research results show that throughout the implementation process of 10 th and 11 th Five-year Plan,the national residential energy consumption density change rate decreased from 52.43% to 43.71%.Among the three factors influencing the regional residential energy consumption density,economic level exerted the largest positive economy effect,and its average contribution to the change rate increased from 63.47% to 67.28% during this period.By contrast,energy intensity produced first positive and then negative technology effects,whose average contribution degree decreased from 4.19% to-24.89%.Energy structure negatively affected the consumption density,and its average contribution rate changed from-20.36% to-0.83%.Decomposition results suggest that the increasing trend of residential energy consumption density in different regions of China is slowing down,and the driving factors of density change is transferring from economy and technology to economy and structure.The spatial disparity analysis results indicate that among the 29 provinces the economic difference is small and stable,while the discrep
出处
《中国矿业大学学报（社会科学版）》
2016年第2期48-56,共9页
Journal of China University of Mining & Technology(Social Sciences)
基金
国家自然科学基金"煤炭价格波动机理及对我国实体经济的传导效应研究"(项目编号:71573255)
中国博士后科学基金面上资助项目"福利损失补偿视角下供运需协同的电煤应急储备规模研究"(项目编号:2014M551708)
江苏省博士后科研资助计划"国家煤炭应急储备最优规模的决策模型研究"(项目编号:1302079B)
江苏省高校哲学社会科学基金项目"居民习惯性节能行为的信息干预机理及优化机制研究"(项目编号:2015SJD435)
国家级大学生创新训练计划项目"中国城市居民绿色消费的现状
行为阻隔和引导政策研究"(项目编号:201410290046)
关键词
生活能源消费密度
因素分解
LMDI
空间差异
四象限法
情景预测
residential energy consumption density
factors decomposition
LMDI
spatial difference
four-quadrant method
scenario forecast
