# Measuring the Performance of Wastewater Treatment in China
## 1 Introduction
In 1984, the water pollution prevention and control law of the People's Republic of China was adopted, which was further revised in 2002. The outline of the 10 th Five-Year Plan of China clarified that the total amount of major urban and rural pollutants discharged would be reduced by 10% compared to 2000, and more measures would be taken to protect and save natural resources. The government has been carrying out ecological civilization construction since 2005. The outline of its 11 th Five-Year Plan presented that the total discharge of major pollutants would decrease 10% from 2006 to 2010. In April 2015, China's State Council formally issued its strictest water plan, 'Water Ten'. It clearly stipulated that the quality of the water environment in the whole country would be improved and that polluted water would be greatly reduced. 'Water Ten' demonstrates the determination and confidence in controlling water pollution but also reflects the serious situation of domestic water pollution. Environmental treatment expense in China has been increased steadily year by year; however, the situation of environmental pollution is still serious. It is crucial to improve the efficiency of wastewater treatment expense to enhance the quality of water environment. Data envelopment analysis (DEA) has been widely used to evaluate environmental performance. The current research on wastewater treatment efficiency mainly focuses on two aspects: (1) On the macrolevel, the literature employs wastewater discharge indicators as factors to evaluate environmental efficiency in certain areas of a country [PERSON] et al. (2016); [PERSON] et al. (2016); [PERSON] et al. (2016); (2) on the microlevel, studies have taken wastewater treatment efficiency by wastewater treatment plants as the research object. [PERSON] et al. [PERSON] et al. (2016) used a double bootstrap DEA (Data Envelope Analysis) to develop a tool for measuring the energy costs of wastewater treatment plants (WWTPs) and to identify how they can be reduced at 127 WWTPs in Tuscany, Italy in 2014. [PERSON] and [PERSON] [PERSON] and [PERSON] (2015) employed the DEA-SBM (slacks-based measure) model to measure the TFE (Total Factor Efficiency) of wastewater control in 39 industrial sectors of China from 2003 to 2014. [PERSON] et al. [PERSON] et al. (2016) analyzed the efficiency of 158 wastewater treatment plantsin the region of Valencia (Spain) using an input-oriented order-m model of conditional efficiency. [PERSON] et al. [17] evaluated the efficiency of a sample of wastewater treatment plants by applying the weighted slacks-based measure model, which assigns weights to the inputs and outputs according to their importance. It can be seen that there are few specific studies on wastewater treatment efficiency measurement in overall China. The assessment of the efficiency of wastewater treatment plants at the microlevel neglects undesired output in the process of water pollution control, which may bias the evaluation results. [PERSON] et al. [18] summarized four types of DEA to deal with undesirable outputs, including: (1) Using a reciprocal of undesirable output to evaluate efficiency [19; 20; 21]; (2) considering undesirable outputs as inputs [22]; (3) employing the data transformation function approach [23; 24]; and (4) using the directional distance function approach [25]. Among those techniques, the directional distance function has been widely applied to solve the problem of efficiency evaluation of undesirable outputs. [PERSON] [26] and [PERSON] et al. [25] extended the output distance function proposed by [PERSON] [27] to the radial directional output distance function. The radial model provides both desirable and undesirable outputs under the same production basis, which allows one to analyze both increasing output and decreasing bad output. [PERSON] et al. [28] used the radial directional distance function to calculate the ecological efficiency of olive plantations in Spain.