Measuring and explaining eco-efficiencies of wastewater treatment plants in China: An uncertainty analysis perspective.

In the context of sustainable development, there has been an increasing requirement for an eco-efficiency assessment of wastewater treatment plants (WWTPs). Data envelopment analysis (DEA), a technique that is widely applied for relative efficiency assessment, is used in combination with the tolerances approach to handle WWTPs' multiple inputs and outputs as well as their uncertainty. The economic cost, energy consumption, contaminant removal, and global warming effect during the treatment processes are integrated to interpret the eco-efficiency of WWTPs. A total of 736 sample plants from across China are assessed, and large sensitivities to variations in inputs and outputs are observed for most samples, with only three WWTPs identified as being stably efficient. Size of plant, overcapacity, climate type, and influent characteristics are proven to have a significant influence on both the mean efficiency and performance sensitivity of WWTPs, while no clear relationships were found between eco-efficiency and technology under the framework of uncertainty analysis. The incorporation of uncertainty quantification and environmental impact consideration has improved the liability and applicability of the assessment.