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基于LMDI的长江经济带交通碳排放变化分析
引用本文:杨绍华,张宇泉,耿涌.基于LMDI的长江经济带交通碳排放变化分析[J].中国环境科学,2022,42(10):4817-4826.
作者姓名:杨绍华  张宇泉  耿涌
作者单位:1. 上海交通大学中英国际低碳学院, 上海 201306;2. 上海交通大学环境科学与工程学院, 上海 200240
基金项目:国家自然科学基金资助项目(72088101,71690241,71810107001)
摘    要:基于LMDI分解模型,探究了2000~2019年长江经济带交通运输业碳密度、运输结构、能源效率、能源强度、经济结构、经济水平以及人口规模等因素对交通碳排放的贡献程度及时空特性,并使用泰尔指数测算了碳排放的区域差异性.结果表明,经济规模持续扩张是长江经济带交通运输业碳排放增长的第一主导因素,对碳排放的正向驱动效应为116.33%,其次是人口规模(6.19%);运输结构和经济结构的转变则是抑制碳排放增长的关键因素,其负向驱动率分别为-26.18%和-16.25%;而技术水平(能源效率和能源强度)的提升有助于抑制碳排放增加.此外,基于人均碳排放和碳排放强度的泰尔指数均显示长江经济交通碳排放量的区域差异性明显,其中区域内差异大于区域间差异,且基于碳排放强度的区域差异呈现出“俱乐部趋同”现象.最后,对长江经济带交通绿色发展提出了政策建议.

关 键 词:交通碳排放  LMDI分解  泰尔指数  
收稿时间:2022-03-20

An LMDI-based investigation of the changes in carbon emissions of the transportation sector in the Yangtze River Economic Belt
YANG Shao-hua,ZHANG Yu-quan,GENG Yong.An LMDI-based investigation of the changes in carbon emissions of the transportation sector in the Yangtze River Economic Belt[J].China Environmental Science,2022,42(10):4817-4826.
Authors:YANG Shao-hua  ZHANG Yu-quan  GENG Yong
Institution:1. China-UK Low Carbon College, Shanghai Jiaotong University, Shanghai 201306, China;2. School of Environmental Science and Engineering, Shanghai Jiaotong University, Shanghai 200240, China
Abstract:Employing the LMDI decomposition model, this study examines how factors such as service-based carbon intensity, transportation structure, energy efficiency, energy intensity, economic structure, level of economic development, and population have influenced the carbon emissions of the transportation sector of the Yangtze River Economic Belt over the period of 2000 to 2019, along with the temporal and spatial characteristics. The Theil index is also applied to measure the regional heterogeneity effects, if any. The results show that the continuous expansion of the economy is the primary leading factor for the growth of carbon emissions of the transportation sector in the Yangtze River Economic Belt, and its positive driving effects are at a rate of 116.33%, far exceeding that of population (6.19%), the second leading factor. The changes in the transportation structure and the economic structure are key factors to restrain the growth of carbon emissions, with their negative driving rates being -26.18% and -16.25%, respectively. The technological progress factors (energy efficiency and energy intensity) help slow down the increases also. Besides, both the per capita carbon emissions- and the carbon emission intensity-based Theil index values indicate that heterogeneity between provinces or municipalities exists for carbon emissions of the transportation sector in the Yangtze River Economic Belt, and the differences within regions are greater than those between regions. The carbon emission intensity-based regional differences particularly exhibit "club convergence" effects. Thereupon, policy suggestions are derived for greener development of transportation in the Yangtze River Economic Belt.
Keywords:transportation carbon emissions  LMDI decomposition  Theil index  
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