Improving the quality of wastewater treatment plant monitoring by adopting proper sampling strategies and data processing criteria

Monitoring is a crucial operation for plant management. However, proper sampling procedures and data processing criteria are not always adopted. Wastewater treatment plants work under dynamic conditions, which poses a challenge for a correct performance assessment. The aim of this work is to analyse some important aspects of wastewater sampling and data processing, to identify case by case methods which should to be adopted in order to obtain reliable and consistent information on plant performance. The study was conducted through simulations and real data analyses. It turned out that: a) the preferable 24-hour composite sampling procedure is the flow-proportional mode; in addition, the required sampling frequency (i.e. the number of sub-samples to be taken to make the 24-h composite sample) increases as the percentage of population discontinuously discharging the monitored substance decreases; b) a Variability Index was defined to help find the minimum sampling frequency (i.e. the number of 24-h composite samples per year) for the calculation of annual mass flows with an acceptable uncertainty; and c) criteria were proposed for the identification of pseudo-steady state periods needed to calculate reliable mass balances and plant performance indicators. (c) 2021 Published by Elsevier B.V.

Automated summary

Monitoring is a crucial operation in plant management, but proper sampling procedures and data processing criteria are not always adopted. This study analysed important aspects of wastewater sampling and data processing to identify methods that should be adopted to obtain reliable and consistent information on plant performance.