Quantitative evaluation on the efficiency of wastewater treatment plants (WWTPs) is a key issue that needs to be solved. For this purpose, data envelopment analysis (DEA) was employed to establish a comprehensive efficiency evaluation system on WWTPs, including three inputs of operating cost, electricity consumption and labor, three desirable outputs of chemical oxygen demand (COD) removal rate, ammonia nitrogen (NH3–N) removal rate and reclaimed water yield, and one undesirable output of dry sludge yield. 861 WWTPs in China were assessed by a slacked-based DEA model based on cluster benchmarking. The technology gap ratio (TGR) confirmed that large WWTPs operated more efficiently than small ones. The WWTPs had an average efficiency score of 0.611. Among them, 170 samples were relatively efficient with a score of 1, which means these samples could be a benchmark for other inefficient samples. Different degrees of input excesses or output shortfalls existed in 691 inefficient samples and these samples should be the key objects to improve the operational efficiency. Furthermore, through the Kruskal-Wallis test, the influent COD concentration and capacity load rate showed significant effects on the WWTP performance. These findings, derived from a simple but effective framework, have potential value for managers to make decisions
