Experimental design for evaluating WWTP data by linear mass balances

Quan H. Le, Peter J.T. Verheijen, Mark C.M. van Loosdrecht, Eveline I.P. Volcke

Research output: Contribution to journalArticleScientificpeer-review

8 Citations (Scopus)
7 Downloads (Pure)

Abstract

A stepwise experimental design procedure to obtain reliable data from wastewater treatment plants (WWTPs) was developed. The proposed procedure aims at determining sets of additional measurements (besides available ones) that guarantee the identifiability of key process variables, which means that their value can be calculated from other, measured variables, based on available constraints in the form of linear mass balances. Among all solutions, i.e. all possible sets of additional measurements allowing the identifiability of all key process variables, the optimal solutions were found taking into account two objectives, namely the accuracy of the identified key variables and the cost of additional measurements. The results of this multi-objective optimization problem were represented in a Pareto-optimal front. The presented procedure was applied to a full-scale WWTP. Detailed analysis of the relation between measurements allowed the determination of groups of overlapping mass balances. Adding measured variables could only serve in identifying key variables that appear in the same group of mass balances. Besides, the application of the experimental design procedure to these individual groups significantly reduced the computational effort in evaluating available measurements and planning additional monitoring campaigns. The proposed procedure is straightforward and can be applied to other WWTPs with or without prior data collection.

Original languageEnglish
Pages (from-to)415-425
Number of pages11
JournalWater Research
Volume142
DOIs
Publication statusPublished - 1 Oct 2018

Keywords

  • Data reconciliation
  • Data validation
  • Experimental design
  • Mass balances
  • Wastewater treatment plant

Fingerprint Dive into the research topics of 'Experimental design for evaluating WWTP data by linear mass balances'. Together they form a unique fingerprint.

  • Cite this