环境污染指标的重要性差异和信息完整性是区域环境污染强度测算及其分类治理效率评价中的两个重要因素. 为此, 文章先基于~CCSD 方法对环境污染指标进行赋权, 以凸显不同指标间的重要性差异; 再基于~ER 模型对环境污染指标进行合成, 以保证在测算环境污染强度时考虑指标的信息完整性; 最后, 还基于考虑非期望产出的~SBM 模型对环境污染分类治理进行效率评价. 通过对中国内地各个省份在~2006 年至~2016 年间的区域环境污染强度测算及其分类治理效率评价的实例分析, 可以发现: 1) 各省份在不同分类下的环境污染强度存在显著差异, 其中多数省份的环境问题集中于水污染或空气污染; 2) 根据污染强度评价等级的空间分布, 污染最为严重的地区主要集中于中部地区和东部的沿海地区, 而西部地区的环境污染程度较低; 3) 基于分类考虑和指标合成的研究结果更符合各省份实际的环境治理状况, 且更有利于不同省份环境治理效果差异的对比分析.

The different importance and information completeness of environmental pollution indicators are two important factors for the calculation of regional environmental pollution intensity and the efficiency evaluation of classified governance. Therefore, the CCSD method is firstly introduced to highlight the importance of different indicators, and synthesizes indicators based on the ER model is used to assure the information completeness of environmental indicators in the calculation of environmental pollution intensity. Finally, the SMB undesirable output model is applied to evaluate the efficiency of classified environmental pollution governance. In the case we study about pollution intensity evaluation and its efficiency evaluation of classified governance for the environmental pollution of the provinces in the Mainland of China from 2006 to 2016 and evaluate the efficiency of classified governance, which shows that: 1) There are significant differences in the intensity of environmental pollution in different provinces, and most of them focus on water or air pollutions; 2) According to the spatial distribution of pollution intensity evaluation grade, the most serious pollution are mainly concentrated in the central and eastern coastal areas, but the degree of environmental pollution in the western region is relatively low; 3) The results based on the classification consideration and indicator synthesis are more in line with the actual environmental governance, and it is more conducive to the comparative analysis of environmental governance efficiency in different provinces.