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Soft sensor predictor of E. coli concentration based on conventional monitoring parameters for wastewater disinfection control by Jacopo Foschi; Andrea Turolla; Manuela Antonelli is a Environmental Science article available to read on EtoBox.

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Real-time acquisition of indicator bacteria concentration at the inlet of disinfection unit is a fundamental support to the control of chemical and ultraviolet wastewater disinfection. Culture-based enumeration methods need time-consuming laboratory analyses, which give results after several hours or days, while newest biosensors rarely provide information about specific strains and outputs are not directly comparable with regulatory limits as a consequence of measurement principles. In this work, a novel soft sensor approach for virtual real-time monitoring of E. coli concentration is proposed. Conventional wastewater physical and chemical indicators (chemical oxygen demand, total nitrogen, nitrate, ammonia, total suspended solids, conductivity, pH, turbidity and absorbance at 254 nm) and flowrate were studied as potential predictors of E. coli concentration relying on data collected from three full-scale wastewater treatment plants. Different methods were compared: (i) linear modeling via ordinary least squares; (ii) ridge regression; (iii) principal component regression and partial least squares; (iv) non-linear modeling through artificial neural networks. Linear soft sensors re

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Author

Jacopo Foschi; Andrea Turolla; Manuela Antonelli

Publisher

Elsevier BV

Published

2021

Language

EN

Field

Environmental Science (Physical Sciences)