Multi-criteria analyses of wastewater treatment bio-processes under an uncertainty and a multiplicity of steady states

This paper presents a multi-criteria evaluation methodology for determining the operating strategies for bio-chemical, wastewater treatment plants based on a model analysis under an uncertainty that can present multiple steady states. The method is based on Monte Carlo (MC) simulations and the expected utility theory in order to deal with the analysis of choices among risky operating strategies with multi-dimensional outcomes. The motivation is given by a case study using an anaerobic digestion model (ADM) adapted for multiple co-substrates. It is shown how the multi-criteria analyses' computational complexity can be reduced within an approximation based on Gaussian-process regression and how a reliability map can be built for a bio-process model under uncertainty and multiplicity. In our uncertainty-analyses case study, the reliability map shows the probability of a biogas-production collapse for a given set of substrates mixture input loads.

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► We model a wastewater treatment process that under uncertainty presents multiplicity.
► We propose a multi-criteria evaluation methodology.
► Pareto efficient solutions are found and process reliability is discussed.