Effective measuring campaigns for reliable and informative full-scale WWTP data

Abstract

Sensor availability and costs are nowadays no longer limiting data gathering at wastewater treatment plants (WWTPs). However, one should be aware that a higher amount of measured data gathered does not necessarily imply that also more information is obtained. In this light, this contribution assesses the general applicability and the added value of a structured experimental design approach for planning measurement campaigns at WWTPs, in view of mass-balance-based data reconciliation. To this end, the results from full-scale WWTP case studies available in the literature were compared to those obtained with the developed structured experimental design procedure. Planning measurement campaigns comprises the selection of (additional) measurements to meet a pre-set main goal. The need for a structured experimental design procedure replacing past expert judgment approaches became clear from the fact that three out of five case studies available in the literature failed to meet the main goal and/or performed unnecessary additional measurements. Translating the main goal into specific key variables was found essential in this respect. The general applicability of the procedure was proven with three outcomes. First, the procedure, involving well-defined steps, could be applied to different WWTP layouts. Second, it ensured the fulfilment of various main goals. Third, it provided useful outcomes, i.e., optimal measurement campaigns, which reduced the need for additional measurements (40–70% less) compared to expert knowledge approaches, hence more information could be obtained with less analytical data. Overall, the experimental design procedure proved a fast and useful tool ensuring the success of subsequent mass-balance-based data reconciliation.