Uncovering CO2 emission drivers under regional industrial transfer in China’s Yangtze River Economic Belt: a multi-layer LMDI decomposition analysis

With the relocation of heavy industries moving from downstream region to upstream and midstream regions in the Yangtze River Economic Belt (YREB), it is critical to encourage coordinated low carbon development in different regions within the YREB. This paper uncovers the evolution of CO₂ emissions in different regions within the YREB for the period of 2000–2017. It decomposes regional CO₂ emission changes using the temporal and cross-regional three-layer logarithmic mean Divisia index (LMDI) method. Besides, it decomposes industrial CO₂ emission changes using the temporal two-layer LMDI method. The research results show that economic growth is the major driver for regional CO₂ emission disparities. The mitigation drivers, such as energy intensity and energy structure, lead to a more decreased CO₂ emission in the downstream region than in the upstream and midstream regions. In addition, it proposes several policy recommendations based upon the local realities, including improving energy efficiency, optimizing energy structure, promoting advanced technologies and equipment transfers, and coordinating the development in the upstream, midstream and downstream regions within the YREB.     

Study on decoupling analysis between energy consumption and economic growth in Liaoning Province

Since 1978, Liaoning province has experienced spectacular economic growth, which has led to more energy consumption. The purpose of this paper is to explore the decoupling status between energy consumption and economic growth in Liaoning Province. Firstly, the generalized LMDI method is used to explore the driving forces governing production energy consumption in Liaoning province. Then, the combination of Tapio decoupling indicator and generalized LMDI method is utilized to study what the decoupling status occurred in Liaoning Province and why the decoupling status appeared. During the study period, only four decoupling status occurred: expansive negative decoupling, expansive coupling, weak decoupling, and strong decoupling. The energy intensity decoupling effect played a positive role in the appearance of decoupling. However, the economic structure decoupling effect and investment decoupling effect played a negative role in the appearance of decoupling. Over the study period, the energy structure decoupling effect and labour decoupling effect played a relative small role in the appearance of decoupling.     

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。     

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。     

电力生产CO2排放变化影响因素分解

利用对数平均权重分解法（LMDI）构建了电力生产CO₂排放变化影响因素的分解模型,并利用1985—2009年中国能源平衡表中的数据测算出电力生产CO₂排放量。在此基础上,将该CO₂排放量变化分解为收入效应、电力生产强度效应、电力生产结构效应、人口效应和发电煤耗效应。以1985年为基期并以我国国民经济和社会发展的五年规划为分解区间对这些影响因素进行分解分析.考察各种影响因素变动的背后原因。结合实证分析,给出相应的政策建议。     

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.     

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.     

新疆农业面源污染与农业经济增长的关系——基于脱钩模型和LMDI模型的实证分析

测算1996-2015年新疆农业面源污染、化学需氧量、总氮、总磷的排放量及排放强度,分析各污染单元的污染物排放所占份额变化和排放贡献率,运用Tapio模型实证分析了新疆面源污染排放与农业经济增长的脱钩关系,并基于LMDI分解模型对新疆各污染物排放的时序变化进行因素分解。研究结果表明,新疆农业面源污染的排放量及排放强度变化可划分为“上升-下降-再上升”3个阶段,主要污染物是化学需氧量排放,主要污染单元是畜禽养殖和农田固体废弃物。新疆农业面源污染与经济增长的脱钩关系经历了弱脱钩阶段、负脱钩与扩张连接阶段、不稳定阶段;农业经济增长的规模效应、效益效应和效率效应对新疆农业面源污染排放具有不同的影响,规模效应的贡献整体不明显,效益效应扩大了新疆农业面源污染排放,而效率效应对农业面源污染排放起着阻碍作用,因此,降低单位农业产值的污染排放是新疆农业面源污染防治的主要途径。      

Analysis of decoupling relationship between carbon emissions and water resources utilization in the Qinhe River Basin based on Tapio and LMDI modelsEI北大核心CSCD

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。     

基于KAYA 恒等式和LMDI分解法的淮安市生产用水驱动因素分析

分析了2008—2017年淮安市主要用水指标的变化特征,综合考虑了水资源禀赋、水资源开发利用、人口规模、经济水平、产业结构、用水效率6个因素对淮安市生产用水的影响,基于扩展的KAYA恒等式建立了用水驱动因素分解模型。并应用对数均值迪氏指数法对2008—2017年淮安市生产用水变化进行分解分析,以评价逐年和多年时间尺度上各类驱动因素对生产用水的相对影响程度。结果表明:2008—2017年淮安市用水总量和生产用水量总体呈下降态势,主要用水效率指标均有改善;经济水平和用水效率提升是淮安市2008—2017年生产用水变化的主要驱动因素,两者在逐年和多年时间尺度上对生产用水变化的相对贡献率分别为56.49%、-127.71%和56.63%、-126.57%。研究成果对了解淮安市用水总量及主要用水效率指标的历史发展趋势,正确理解淮安市产业结构与用水结构协调发展具有参考价值。