Xu Jun, Jiang Yuchen, Guo Xin, Jiang Li
School of Business, Jiangsu Normal University, Xuzhou 221116, China.
Int J Environ Res Public Health. 2021 May 27;18(11):5761. doi: 10.3390/ijerph18115761.
Industrial waste discharged by heavy pollution industry is one of the main causes of global environmental degradation. Research on the environmental efficiency of high-polluting industry is necessary to tackle the problem of global environmental pollution. Using panel data of 19 sub-industries in China's heavy pollution industry from 2001 to 2015, this article employs Data Envelopment Analysis (DEA) and Malmquist index (MI) to measure the environmental efficiency of heavy pollution industry from both the dynamic and static perspectives. The results show that the environmental efficiency of China's heavy pollution industry maintains an upward trend but did not reach the optimal level. The general trend shows a phased trend of increasing first and then decreasing. Besides, there are inter-industry differences in the environmental efficiency across the examined sub-industries. Based on the research findings, this article proposes a set of corresponding countermeasures to solve the global pollution problem, such as reducing energy inputs and minimizing the volumes of the main categories of emissions in high-polluting industry, as well as improving the production management in the group of high environmental efficiency and strengthening technical capabilities in the group of low environmental efficiency.
重污染行业排放的工业废物是全球环境恶化的主要原因之一。研究高污染行业的环境效率对于解决全球环境污染问题很有必要。本文利用2001年至2015年中国重污染行业19个细分行业的面板数据，运用数据包络分析（DEA）和Malmquist指数（MI）从动态和静态两个角度衡量重污染行业的环境效率。结果表明，中国重污染行业的环境效率呈上升趋势，但未达到最优水平。总体趋势呈现出先上升后下降的阶段性趋势。此外，在所考察的细分行业中，环境效率存在行业间差异。基于研究结果，本文提出了一系列相应的对策来解决全球污染问题，如减少能源投入、最大限度减少高污染行业主要排放物的排放量，以及提高环境效率高的群体的生产管理水平和增强环境效率低的群体的技术能力。
