Properties and linkages of some index decomposition analysis methods

We study the properties and linkages of some popular index decomposition analysis (IDA) methods in energy and carbon emission analyses. Specifically, we introduce a simple relationship between the arithmetic mean Divisia index (AMDI) method and the logarithmic mean Divisia index method I (LMDI I), and show that such a relationship can be extended to cover most IDA methods linked to the Divisia index. We also formalize the relationship between the Laspeyres index method and the Shapley value in the IDA context. Similarly, such a relationship can be extended to cover other IDA methods linked to the Laspeyres index through defining the characteristic function in the Shapley value. It is found that these properties and linkages apply to decomposition of changes conducted additively. Similar properties and linkages cannot be established in the multiplicative case. The implications of the findings on IDA studies are discussed.     

建筑业挥发性有机物排放与行业经济增长的响应关系研究

挥发性有机物（Volatile organic compounds,VOCs）排放是绿色建筑关注的重点。本文基于排放因子法和 Tapio 脱钩理论,研究了 2001~2016 年我国建筑行业 VOCs 排放与行业经济增长之间脱钩关系的变化轨迹,采用 LMDI 分解法对建筑业 VOCs 排放驱动因素进行分解。研究结果表明,自 2001 年开始我国建筑业 VOCs 排放量呈上升趋势,除 2015 年为强负脱钩状态,其他年份均为弱脱钩状态,经济产出效应为我国建筑业 VOCs 排放的最大诱因,并提出建立和完善我国建筑业VOCs 减排的对策和建议。     

Decomposition analysis of energy consumption in Chinese transportation sector

The purpose of this paper is to identify the relations between transportation energy consumption and its impacted factors. We first analyze the current status of transportation energy consumption in China. Then, the logarithmic mean Divisia index (LMDI) technique is used to find the nature of the factors those influence the changes in transportation energy consumption. We find that: (1) In 2006, the transportation energy consumption increased by 7.63 times against that in 1980. (2) Up to 2006, the oil consumed by transportation accounted for 49.6% of that in the whole country, which almost equaled to the net oil import. (3) In the light of the increasing energy consumption intensity, the energy-utilization effectiveness of transportation sector has been declining gradually. (4) The transportation activity effect is the most important contributor to increase energy consumption in the transportation sector and the energy intensity effect plays the dominant role in decreasing energy consumption.     

Handling zero values in the logarithmic mean Divisia index decomposition approach

The Logarithmic Mean Divisia Index (LMDI) decomposition approach has many desirable properties. It has been recommended by Ang [2004a. Decomposition analysis for policymaking in energy: which is the preferred methods? Energy Policy 32, 1131–1139] for adoption in energy and energy-related environmental index decomposition analysis (IDA). A complication associated with this approach is the treatment of zero values in the data set. Several studies show that replacing the zero values with a small number gives converging results. In a recent paper, Wood and Lenzen [Zero-value problems of the logarithmic mean Divisia index decomposition method. Energy Policy, in press] argue that this strategy is not necessarily robust and recommend using the analytical limits proposed in Ang et al. [1998. Factorizing changes in energy and environmental indicators through decomposition. Energy 23, 489–495]. We compare these two strategies and extend earlier works by generalizing the analytical limits of LMDI.     

安徽省产业用水结构变化的驱动因子识别与分析

以安徽省2001~2011年近10年来的水资源利用情况为背景,以产业用水结构为研究对象,调查分析了安徽省2001~2011年三大产业用水结构变化的分布特征及其演变规律,在分析安徽省水资源状况、特点及其用水现状的基础上,基于扩展的Kaya恒等式将影响安徽省产业用水结构变化的因素分为经济水平、产业结构、用水强度三个方面,并建立了基于LMDI的分解模型计算各驱动因子的贡献度,最后对安徽省17个地级市产业用水变化的驱动因子进行识别与分析,并根据分析结果提出提高用水效率的指导性建议。     

基于Tapio和LMDI模型的沁河流域碳排放与水资源利用脱钩关系分析

在界定沁河流域研究范围和对沁河流域碳排放趋势特征分析的基础上,采用Tapio脱钩模型分析了碳排放与水资源利用的脱钩关系,并采用LMDI模型分析影响碳排放的主要驱动因素。结果表明:沁河流域整体碳排放呈现波动增长态势,但碳排放增长率波动下降;沁河流域碳排放与水资源利用多数时间处于强负脱钩和扩张负脱钩状态,但逐渐出现强脱钩与弱脱钩状态,水碳关系逐渐向好;水资源利用效应和碳排放强度效应是驱动沁河流域碳排放增长的主要因素,用水效益效应是驱动碳排放减少的主要因素,碳排放强度效应与供水结构效应驱动效果逐渐变得更为显著。     

中国有色金属行业能源消耗碳排放影响因素分析

运用平均对数迪氏指数法(LMDI)对我国有色金属行业2000—2011年能源消耗碳排放的变动特点和主要影响因素进行研究,基于LMDI模型的情景分析,对2020年有色金属行业的碳排放进行预测。结果表明,经济规模是促进碳排放的最主要因素,能源强度是减缓碳排放的主要因素,能源结构和碳排放系数的影响较小。我国有色金属行业的减排潜力很大,未来减排关键在于控制经济规模的扩张和降低能源强度。     

中碳强度指数与中国低碳发展

中碳强度指数是为全国节能减排行业提供一个以单位国内生产总值(GDP)二氧化碳排放量为载体的指数系统,可有效反映时间序列上地区或行业碳排放强度的变化.2005—2011年中碳强度指数总体呈下降趋势.按中碳强度指数将我国各省级行政区分为五类,其中:大部分地区的指数均集中在0~100之间;指数高于100的四类和五类地区主要是煤炭生产大省和西部欠发达地区;而指数低于0的一类地区主要是经济发达地区.采用对数均值迪氏分解(LMDI)法分析陕西、贵州两省碳强度的影响因素时发现,能源强度下降是其碳强度指数下降的主要原因.结合\"十二五\"各地区的减排目标,预测了各省级行政区在剩余年份达成目标的压力,结果显示,我国的碳减排任务艰巨,其中内蒙古、宁夏等省份面临巨大的减排压力.     

科研投入抑制碳排放了吗？——基于LMDI模型和STIRPAT模型的碳排放影响因素分析

节能减排是全球共同关注的重要问题,近年来中国不断加大科研投入、改善能源结构、实现产业结构升级以减少碳排放。虽然中国高污染产业的科研经费支出较高,但是对于抑制二氧化碳排放进而改善工业整体环境效应的方向和力度仍缺乏具体的衡量指标。为进一步分析科研投入对碳排放的作用效果,本文首先将科研规模效应引入分析碳排放影响因素的LMDI模型,从经济规模、科研规模、能源结构及能源强度的分解结果进行讨论;同时为了弥补LMDI模型在弹性分析方面的不足,引入扩展的STIRPAT模型,采用总体能源强度指标和科研投入效率因素,结合省际面板数据进行进一步比较分析。研究结果表明：1）科研投入的增加对碳排放无显著抑制效果,但科研效率的提高以及产业结构升级有助于减少碳排放;2）能源结构和能源强度与碳排放量显著负相关;3）新旧动能转换重大工程的提出和实施对碳减排有明显的促进作用。最后结合模型结果提出增强科研投入针对性,提高科研投入效率;出台节能减排政策,鼓励技术创新;推进新旧动能转换,实现产业结构优化升级等政策启示。