2004–2011年中国省域生态补偿差异分析（英文）

编号 zgly0001584057

文献类型 期刊论文

文献题名 2004–2011年中国省域生态补偿差异分析（英文）

作者 刘春腊  刘卫东  陆大道  陈明星  徐美 

作者单位 DepartmentofResourcesandEnvironmentScience  HunanNormalUniversity  InstituteofGeographicSciencesandNaturalResourcesResearch  KeyLaboratoryofRegionalSustainableDevelopmentModeling  CAS  SchoolofTourism  CentralSouthUniversityofFor 

母体文献 Journal of Geographical Sciences 

年卷期 2017年02期

年份 2017 

分类号 X321 

关键词 provincialeco-compensation  difference  measure  China 

文摘内容 In this study, we developed a theoretical framework to analyze the provincial differences in eco-compensation and selected appropriate measurement methods to investigate these differences in the operation of the eco-compensation framework. Via the use of the coefficient of variation, Atkinson index, and Gini coefficient, we investigated the overall differences in Chinese provincial eco-compensation time series data from 2004 to 2014 and studied the driving mechanism underlying these differences. The results showed that:(1) The provincial eco-compensation standard has geographical features. For example, the provinces crossed by the HU Huanyong Line, or located to its northwestern side, have obtained extensive eco-compensation.(2) There was a trend for differences in eco-compensation to increase over time, but with some fluctuations in 2006, 2009, and 2014 as shown by the coefficient of variation, in 2005, 2007, 2011, 2013, and 2014 as shown by the Gini coefficient, and in 2007, 2008, 2011, and 2012 as shown by the Atkinson index.(3) Time series curves indicated that while the signals from the three metrics(coefficient of variation, Atkinson index, and Gini coefficient) differ in a short-term analysis, they show the same tendency in the longer term. The results indicate that it is necessary to evaluate the differences in eco-compensation at the provincial level over a long period of time.(4) Via the calculation of the virtual Gini coefficient, we found that among the factors that influence provincial differences in eco-compensation, the economic value of eco-resources played the decisive role, explaining more than 73% of the difference. The cost of environmental pollution abatement was the second most important factor, accounting for more than 19% of the difference. The input to environmental pollution abatement had the least influence, accounting for less than 8% of the difference. The results agreed with those obtained from other studies, and could be used as a reference by policy makers.