As the number of wastewater treatment plants (WWTPs) increases worldwide and the effluent quality requirements become more demanding, the issue of energy efficiency has been attracting increasing attention from an environmental and economic point of view. Earlier approaches to measuring WWTP energy efficiency such as Data Envelopment Analysis (DEA) have recently focused on controlling for exogenous variables ignoring the possible presence of omitted (not observed) variables. This omission can lead to biased efficiency index. Moreover, since the level of efficiency can be decomposed in two parts, one persistent and one transient, based on such approaches, water utilities may decide to invest in new machines and infrastructure, when instead the origins of inefficiency come from a non-optimal use of some machines or vice versa. The objective of this paper is to investigate how overall inefficiency of WWTPs is decomposed to persistent and transient inefficiency. This allows better evaluation of energy saving measures since both components convey different types of information. While persistent inefficiency reflects long-term structural problems due to, e.g., energy inefficient equipment used for wastewater treatment, transient inefficiency is associated with process operational practices or decisions that take place in the short term. Distinguish between persistent and transient inefficiency, while controlling for exogenous factors, is thus essential to deduce appropriate energy diagnosis and design useful energy efficiency strategies for WWTPs. This research applies a novel approach of Stochastic Frontier Analysis (SFA) for energy demand modelling to estimate the comparative energy efficiency of a comprehensive panel of WWTPs in Switzerland, as far as in known, for the first time.
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