A1 Journal article (refereed)
Potential of interactive multiobjective optimization in supporting the design of a groundwater biodenitrification process (2020)

Saccani, G., Hakanen, J., Sindhya, K., Ojalehto, V., Hartikainen, M., Antonelli, M., & Miettinen, K. (2020). Potential of interactive multiobjective optimization in supporting the design of a groundwater biodenitrification process. Journal of Environmental Management, 254, Article 109770. https://doi.org/10.1016/j.jenvman.2019.109770

JYU authors or editors

Publication details

All authors or editors: Saccani, Giulia; Hakanen, Jussi; Sindhya, Karthi; Ojalehto, Vesa; Hartikainen, Markus; Antonelli, Manuela; Miettinen, Kaisa

Journal or series: Journal of Environmental Management

ISSN: 0301-4797

eISSN: 1095-8630

Publication year: 2020

Volume: 254

Article number: 109770

Publisher: Elsevier

Publication country: United Kingdom

Publication language: English

DOI: https://doi.org/10.1016/j.jenvman.2019.109770

Publication open access: 

Publication channel open access: 

Publication is parallel published (JYX): https://jyx.jyu.fi/handle/123456789/66671

Abstract

The design of water treatment plants requires simultaneous analysis of technical, economic and environmental aspects, identified by multiple conflicting objectives. We demonstrated the advantages of an interactive multiobjective optimization (MOO) method over a posteriori methods in an unexplored field, namely the design of a biological treatment plant for drinking water production, that tackles the process drawbacks, contrarily to what happens in a traditional volumetric-load-driven design procedure. Specifically, we consider a groundwater denitrification biofilter, simulated by the Activated Sludge Model modified with two-stage denitrification kinetics. Three objectives were defined (nitrate removal efficiency, drawbacks on produced water, investment and management costs) and the interactive method NIMBUS applied to identify the best-suited design without any a priori evaluation, as for volumetric-load-driven design procedures. When compared to an evolutionary MOO algorithm, the interactive solution process was faster, more understandable and user-friendly and supported the decision maker well in identifying the most preferred solution (main design/operating parameters) to be implemented. Approach strength has been proved through both sensitivity analysis and positive experimental validation through a pilot scale biofilter operated for three months. In synthesis, without any “a priori” evaluation based on practical experience, the MOO design approach allowed obtaining a preferred Pareto optimal design, characterized by volumetric loading in the range 0.85–2.54 kgN m−3 d−1 (EBCTs: 5–15 min), a carbon dosage of 0.5–0.8 gC,dos/gC,stoich, with SRTs in the range 4–27 d.

Keywords: water purification; water treatment; decision support systems; multi-objective optimisation; Pareto efficiency

Free keywords: water treatment; interactive method; NIMBUS method; IND-NIMBUS; decision support; pareto optimality

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Ministry reporting: Yes

Reporting Year: 2020

JUFO rating: 1