我国城镇污水处理厂运行效率评价

污水处理厂运行效率的定量评价是当前污水处理行业管理需要解决的问题,效率研究将有助于政府制订合理政策以促进污水处理厂的发展.基于全要素生产框架,采用DEA(数据包络分析)方法构建了污水处理厂运行效率评价模型,以固定资产总额、年运行费用、污水处理人员数和年耗电量为投入变量,以污水年处理量、BOD5和氨氮削减量为产出变量,对2013年我国74座排放标准为一级A且处理工艺相同的城镇污水处理厂作为样本进行效率评价,基于评价结果,对运行效率和污水厂处理规模之间的关系进行检验,并对样本的投入冗余和产出不足情况进行定量分析.结果显示:有20个样本的运行效率达到相对最优,可以成为其余效率不足样本今后改进的标杆;有10个样本纯技术效率有效但规模效率无效,需要改进其规模;85.2%的DEA无效样本规模报酬为递增状态,表明我国污水处理行业整体上处于规模收益递增的发展阶段;通过KW(Kruskal-Wallis)检验发现,样本污水处理厂具有规模效应,规模越大的运行效率越高;54个DEA无效样本存在不同程度的投入冗余和产出不足,冗余率或不足率较高的样本是今后进行效率改进的重点对象.

Evaluation of Operating Efficiencies of Municipal Wastewater Treatment Plants in China

Abstract: Quantitative evaluation of the efficiency of municipal wastewater treatment plants (WTPs) is a problem for the sewage treatment industry. Efficiency assessment contributes to making WTP development policy more scientific and reasonable. For this purpose, under the framework of the total factor productivity (TFP), data envelopment analysis (DEA) was employed to establish an evaluation model of the efficiency of WTPs, including input indices of gross fixed assets, annual operating cost, employment and annual power consumption, and output indices of wastewater treatment capacity and pollutant reduction of BOD₅ and NH₃-N. A total of 74 samples were selected as the empirical analysis objects, which have the same discharge standard and treatment process. An efficiency index was obtained for each plant by means of mathematical programming techniques, aiming to determine the relationship between WTPs'' efficiency and their scales, and to analyze the sample input redundancy and output slack using a quantitative method. In total, 20 samples reached their relative optimal efficiencies, which means these samples could be benchmarks for other samples. There were 10 samples with pure technical efficiencies, but no scale efficiencies which are needed to improve their scale. 85.2% of the DEA invalid samples showed increasing returns to scale, which indicates the sewage treatment industry in China is in the process of rapid development, with high potential to increase the profits by augmenting investments in the industry. Furthermore, through the Kruskal-Wallis Test, it was determined that the larger plants ran more efficiently than the small plants, which indicates the scale effect in the industry, as was expected. Different levels of input redundancy or output slack existed in the 54 DEA invalid samples; these samples would be the key objects to improve the operating efficiency.