School of Mathematics and Information Engineering, Wenzhou University of Technology, Zhejiang, People's Republic of China.
The Faculty of Science and Engineering, The University of Nottingham Ningbo China, Zhejiang, People's Republic of China.
Environ Monit Assess. 2021 Jul 2;193(7):457. doi: 10.1007/s10661-021-09228-2.
After the concept of ecological efficiency (eco-efficiency) was put forward and constantly supplemented, it generally refers to the maximization of economic benefits with minimum energy consumption and environmental damage. In a new eco-efficiency model proposed by this paper, the input indexes take into account the consumption of capital, human, resources and energy, and the environmental load caused by them. The output indexes take into account GDP, income, and tax revenue. An optimal weighted cross-evaluation efficiency (OWCE) model based on data standardization is proposed, by improving the traditional data envelopment models of CCR and BCC. The OWCE model not only objectively weights but also unifies the comparison scale, and facilitates the establishment of the super-efficiency decomposition model, which is conducive to further exploring the reasons for the difference of eco-efficiency in various regions. Empirically, the eco-efficiencies of 11 provinces (municipalities) along the Yangtze River Economic Belt (YREB) were analyzed based on the data from 2008 to 2019. The results show that there has been a serious imbalance in the 11 provinces, showing a trend of high in the east and low in the west, although the eco-efficiency has been improving continuously in the past 10 years. Shanghai, Zhejiang, and Jiangsu, which are located in the traditional Yangtze River lower delta region, are the top in terms of eco-efficiency, among which Shanghai ranks the first place with absolute advantage, and also is far ahead in sub-efficiencies of basic input, energy consumption, capital and human input, and environmental cost. Geographical location, especially whether it is close to the ocean, and the length of river flow have a certain positive impact on eco-efficiency. Through in-depth analysis, high-energy consumption, high pollution, and low economic output are the main reasons for low eco-efficiency in the middle and upper reaches of the Yangtze River.
在生态效率(eco-efficiency)概念提出并不断补充之后,它通常是指以最小的能源消耗和环境破坏来实现经济效益的最大化。在本文提出的新生态效率模型中,投入指标考虑了资本、人力、资源和能源的消耗以及由此产生的环境负荷。产出指标则考虑了 GDP、收入和税收。本文提出了一种基于数据标准化的最优加权交叉评价效率(OWCE)模型,通过改进传统的 CCR 和 BCC 数据包络模型。OWCE 模型不仅客观地加权,而且统一了比较尺度,便于建立超效率分解模型,有利于进一步探讨各地区生态效率差异的原因。实证方面,本文利用 2008 年至 2019 年的数据,对长江经济带(YREB)沿线 11 个省(直辖市)的生态效率进行了分析。结果表明,11 个省之间存在严重的不平衡,呈现出东部高、西部低的趋势,尽管过去 10 年来生态效率一直在不断提高。位于传统长江下游三角洲地区的上海、浙江和江苏在生态效率方面排名最高,其中上海具有绝对优势,排名第一,在基本投入、能源消耗、资本和人力投入以及环境成本的分效率方面也遥遥领先。地理位置,特别是是否靠近海洋以及河流长度,对生态效率有一定的积极影响。通过深入分析,高能耗、高污染和低经济产出是长江中上游生态效率低的主要原因。