Evaluation of energy efficiency of wastewater treatment plants: The influence of the technology and aging factors

Maria Molinos-Senante and Alexandros Maziotis

Applied Energy, 2022, vol. 310, issue C, No S030626192200023X

Abstract: Wastewater treatment is an energy-intensive process and therefore, improving the energy efficiency of wastewater treatment plants (WWTPs) is relevant from an economic and environmental perspective. Water companies managing WWTPs operate under monopolistic conditions and thus, benchmarking their performance using robust methods is fundamental for regulation. This study evaluates the energy efficiency of a sample of Chilean WWTPs using a newly developed technique, called stochastic non-parametric envelopment of data (StoNED). This technique integrates non-parametric (non-linear programming) methods with stochastic noise (parametric techniques) and therefore, it overcomes the limitations of both methodological approaches. Moreover, it allows exploring the influence of operating environment on the energy performance of WWTPs. Results evidenced that the Chilean WWTPs were considerably inefficient (average score was 0.433) presenting therefore significant opportunities to save energy (average savings were 203,413 MWh/year). Only 8 out of 203 facilities reported an average energy efficiency score which was greater than 0.81. It was also found that the age of the facilities negatively affected energy efficiency. Recently built WWTPs showed an average energy efficiency score of 0.489, whereas older facilities were found to be considerably inefficient, 0.340 on average. WWTPs using suspended-growth processes, i.e., conventional activated sludge and extended aeration, as secondary treatment were those with the lowest levels of energy efficiency on average. The results and conclusions of this study are useful for policy makers and WWTP operators who want to reduce energy consumption of WWTPs and therefore, their operational costs and environmental impacts.

Keywords: Energy efficiency; Energy savings; Wastewater treatment; Frontier estimation; Non-parametric analysis; Environmental variables (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (2)

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DOI: 10.1016/j.apenergy.2022.118535

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