| 基于超效率SBM模型的中国城市生态效率时空演变及影响因素 |
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| 作者姓名： | 闫涛 张晓平 赵艳艳 |
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| 作者单位： | 中国科学院大学资源与环境学院, 北京 100049 |
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| 基金项目： | 国家自然科学基金（41771133）和中国科学院战略性先导科技专项A类项目（XDA19040403）资助 |
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| 摘 要： | 运用含有非期望产出的超效率SBM模型，研究2005—2017年中国285个地级以上城市生态效率的时空演变格局，并运用面板回归模型探析城市生态效率的影响因素。结果表明：1）2005—2017年全国城市平均生态效率波动起伏较小，生态效率整体处于上升状态。2）尽管城市间生态效率的差异呈缩小态势，但全国地区间差异仍然较明显，东部地区的城市生态效率远高于其他地区，城市生态效率整体呈现东部地区>全国平均水平>西部地区>东北地区>中部地区的态势。3）全国城市生态效率时空格局演化特征明显。2005年生态效率较高的城市主要分布在珠三角、长三角、山东等省区，其他大部分地区城市生态效率处于较低水平；2017年城市生态效率较高的空间范围明显扩展，珠三角、长三角、山东、河南、河北、湖北和四川等地区的生态效率处于较高水平，其他地区仍处于较低水平。4）城镇化、经济发展、对外开放、科技水平和产业升级对城市生态效率的提升起着显著的促进作用，而较高的工业化比重对于城市生态效率的提升起着抑制作用。因此促进经济集约高效发展、优化产业结构、增加科技投入、加快工业升级、减少资源消耗和污染物排放应是政策制定的优选方向。
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| 关 键 词： | 生态效率 超效率SBM模型 非期望产出 时空演变 |
| 收稿时间： | 2019-12-30 |
| 修稿时间： | 2020-05-30 |
Spatiotemporal evolution of urban eco-efficiency in China and its influencing factors based on super-efficiency SBM model |
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| Authors: | YAN Tao ZHANG Xiaoping ZHAO Yanyan |
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| Institution: | College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China |
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| Abstract: | Urban eco-efficiency is an effective indicator to show the relationship between regional economic development and its impact on resources and environment. The spatiotemporal evolution of the eco-efficiency of 285 cities above the prefecture level in China from 2005 to 2017 was calculated by the super-efficiency SBM model containing the undesirable outputs. The panel regression models were further constructed to analyze the factors that significantly influenced the urban eco-efficiency. The conclusions are as follows. 1) The average urban eco-efficiency across China fluctuated slightly and showed a rising trend. 2) Even though the gap of eco-efficiency between cities decreased gradually from 2005 to 2017, the regional disparity in the whole country was still obvious. 3) The spatiotemporal pattern of urban eco-efficiency among different regions and cities has evolved significantly. The cities with higher ecological efficiency in 2005 were mainly distributed in the Pearl River Delta, the Yangtze River Delta, and Shandong Province. By contrast, the territorial ranges of cities with higher urban eco-efficiency in 2017 were greatly expanded. 4) Results from the regression models showed that factors as urbanization rate, economic development level, openness to foreign economies, science and technology investments, and industrial transition were important determinants promoting the urban eco-efficiency in China. Therefore, high priorities should be given to upgrade industrial structure, increase investments in science and technology, and reduce resources consumption and pollutants emissions when authorities make policies towards regional sustainable development. |
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| Keywords: | eco-efficiency super-efficiency SBM model undesirable output spatiotemporal evolution |
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