Eco-efficiency of centralized wastewater treatment plants in industrial parks: A slack-based data envelopment analysis

Abstract

China has more than 2500 industrial parks that are above the provincial level and contribute more than half of the GDP of China. Centralized wastewater treatment plants (CWWTPs) are one of the most important environmental infrastructures of these industrial parks, and their performance and efficiency usually directly influences the pollutants discharged and the surrounding water environment. Data envelopment analysis (DEA) is a method that has been increasingly popular for assessing the efficiency of wastewater and wastewater treatment plants (WWTPs) in recent decades. In this study, a slack-based DEA (SBM-DEA) model, which includes five input variables and four output variables, is applied to assess the eco-efficiency of 281 CWWTPs in 126 national-level industrial parks (NIPs). Sensitivity analysis is used to identify the most sensitive input and output variables. Next, a Pearson correlation analysis is used to evaluate the correlations between the eco-efficiency factors and some implicit factors, which are not selected as input and output variables but may have an underlying impact on the eco-efficiency of CWWTPs. Then, the uncertainty and limitations of the DEA method, in terms of its ability to assess the efficiency of CWWTPs, are discussed. Finally, the conclusion is presented and some policy suggestions are proposed to improve the eco-efficiency of CWWTPs in NIPs. The key findings will have referential significance of improving eco-efficiencies of industrial parks around the world.