| 基于LMDI模型的中国主要大气污染物的空间差异及其影响因素分析 |
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| 引用本文： | 刘满芝,杨继贤,马丁,丁志华.基于LMDI模型的中国主要大气污染物的空间差异及其影响因素分析[J].资源科学,2015,37(2):333-341. |
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| 作者姓名： | 刘满芝 杨继贤 马丁 丁志华 |
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| 作者单位： | 中国矿业大学管理学院, 徐州221116;美国劳伦斯伯克利国家实验室环境能源技术部, 美国加利福尼亚州伯克利94720,兖州煤业股份有限公司机电环保部, 邹城273500,美国劳伦斯伯克利国家实验室环境能源技术部, 美国加利福尼亚州伯克利94720;清华大学能源环境经济研究所, 北京100084,中国矿业大学管理学院, 徐州221116 |
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| 基金项目： | 国家"十二五"科技支撑计划项目(编号:2012BAC20B01);国家社会科学基金(编号:10CJY028);中国博士后科学基金面上资助项目(编号:2014M551708);江苏省博士后科研资助计划(编号:1302079B);国家级大学生创新训练计划项目(编号:201410290046) |
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| 摘 要： | 为挖掘大气污染物排放量和污染治理效果的主要影响因素,本文运用LMDI分解模型,对全国和30个省份2000-2010年间的主要大气污染物排放量的变化进行因素分解,并通过构建四象限法评价地区差异。在此基础上,从技术效应、结构效应和规模效应三方面分析治理投资等因素对SO2去除量的贡献。研究结果显示:在影响大气污染物排放量变化的五个因素中,大气污染物末端治理措施、能源结构和能源强度对SO2、烟尘的排放量变化率呈现负向效应,尤其是末端治理措施负向效应最大,"十五"时期和"十一五"时期,其对SO2排放量变化的贡献度均值由-10.4%变为-49.9%、对烟尘的贡献度由-60.7%变为-73.7%,而经济规模和煤炭污染强度呈现正向效应,经济规模贡献度高达50%以上,但呈下降趋势。针对SO2去除量变化率的分解结果显示中国大气污染治理由规模和结构拉动型转为技术和规模拉动型,各省间技术效应和结构效应差别较大、规模效应差异小。
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| 关 键 词： | 大气污染物 LMDI 空间差异 四象限法 中国 |
Spatial disparity and factor analysis of major air pollutant emissions in China based on LMDI methods |
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| LIU Manzhi,YANG Jixian,MA Ding and DING Zhihua.Spatial disparity and factor analysis of major air pollutant emissions in China based on LMDI methods[J].Resources Science,2015,37(2):333-341. |
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| Authors: | LIU Manzhi YANG Jixian MA Ding and DING Zhihua |
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| Institution: | School of Management, China University of Mining and Technology, Xuzhou 221116, China;Environmental Energy Technologies Division, Lawrence Berkeley National Laboratory, Berkeley CA 94720, USA,Mechanical & Electrical Environment Protection Department, Yanzhou Coal Mining Co., Ltd, Zoucheng 273500, China,Environmental Energy Technologies Division, Lawrence Berkeley National Laboratory, Berkeley CA 94720, USA;Institute of Energy, Environment and Economy, Tsinghua University, Beijing 100084, China and School of Management, China University of Mining and Technology, Xuzhou 221116, China |
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| Abstract: | In order to evaluate the main influencing factors of air pollutant emissions and pollution control, we used the Log Mean Divisia Index(LMDI)method to explore the impacts of five factors (end-of-pipe measures, coal pollution intensity, energy structure, energy intensity and economic output on SO2 and soot emission quantity)in China from 2000 to 2010. In addition, we employed the four-quadrant method to evaluate provincial spatial disparities for main air pollutant emissions. Then, a decomposition model of the effect of end-of-pipe treatment measures on air pollutants was applied, and three factors including investment air pollutant removal intensity, air pollution control investment proportion of economic scale, and economic scale were constructed to measure the technical effect, structure effect and scale effect on end-of-pipe treatment measures, respectively. The results show that air pollutant end-of-pipe treatment measures, energy structure and energy intensity possess negative effects on emissions changes in SO2, soot, and atmospheric pollutant end-of-pipe treatment measures has the biggest negative effect. In the 10th and 11th Five Year Plans the average contribution degree to SO2 emission rate decreased from -10.4% to -49.9%, and average contribution degree to soot decreased from -60.7% to -73.7%. Economic scale and coal pollution intensity have positive effects, in which the contribution degree of economic scale is over 50% and exhibiting a declining trend. The decomposition results of SO2 removal rate show that the character of Chinese air pollutant control measures transferred from the type of scale and structure pull to the type of technology and scale pull. The spatial disparity analytical results show that differences among the provinces in technical effects and structural effects are large, while differences in scale effect are small. |
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| Keywords: | air pollutants LMDI spatial disparity four-quadrant method China |
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