A study of allocative efficiency of PM2.5 emission rights based on a zero sum gains data envelopment model
A study of allocative efficiency of PM2.5 emission rights based on a zero sum gains data envelopment model
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基于零和收益数据包络模型的PM2.5排放权配置效率研究
DOI：
10.1016/j.jclepro.2015.11.025
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发表时间：
2016
影响因子：
11.1
通讯作者：
Zhu Weiwei
中科院分区：
文献类型：
--
作者：
Wu Xianhua;Tan Ling;Guo Ji;Wang Yingying;Liu Hui;Zhu Weiwei
控制雾霾排放是我国环境治理的一项紧迫任务。排污权交易是在污染物排放总量得到控制的前提下实现污染物减排的可行途径，而基于目标总量的初始排污权分配是排污权交易的关键。本文利用投入导向的DEA模型，在总量目标不变的条件下，研究了PM2. 5排放权的省际配置效率。研究结果表明：（1）在初始排污权按照ORG-DEA模型分配后，各省PM2.5排放量将处于一个新的公共DEA前沿，从而实现总量设定下的总体帕累托最优;（2）各省土地面积和大气环境容量两个因素，在实际分配中考虑了资源配置效率，避免了以往资源配置效率评价文献中各评价单位的同质化，使评价结果更符合各省的实际情况。该研究方法可为排污权交易中初始排污权的分配提供指导，研究结果可为中央和地方政府的减霾工作量提供实证支持。
It is an urgent task for China to control haze emission in environmental treatment. Emission right trading is a feasible way to achieve the reduction of pollutant emission on the premise that the total pollutant emission amount is under control, and the allocation of initial emission rights based on the target total amount is the key to emission right trading. In this paper, via the input-oriented ZSG-DEA model, the inter provincial allocative efficiency of PM2.5emission rights is investigated under the condition that the target total amount is fixed. The results showed that (1) after initial emission rights were allocated in accordance with the ZSG-DEA model, PM2.5emission amounts of all provinces would be in a new common DEA frontier so as to realize the overall Pareto optimality with a set total amount; (2) two factors, namely land areas and atmospheric environmental capacities of all provinces, were considered in the actual allocation to avoid the homogenization of all evaluated units found in the previous evaluation literature on allocative efficiency, thereby making the evaluation results more in line with the actual situations in all provinces. Such an investigation approach can provide guidance on the allocation of initial emission rights in emission right trading; and the research results can offer empirical support for haze-reducing work load conducted by central and local governments of China.