Research Topic

Construction of regularized regression model for chlorine disinfection of rotavirus in secondary treated wastewater

Research Abstract

Reuse of treated wastewater is one of the promising options to solve water shortages. Water-borne viruses which can remain in secondary treated wastewater need to be sufficiently inactivated. Log-reduction values of virus is determined by disinfection intensity; however, disinfection efficiency is affected by physicochemical and biological factors of secondary treated wastewater. The objective of this study is to establish a universal method to determine appropriate disinfection intensity to achieve sufficient log-reduction value of virus in secondary treated wastewater using machine learning and mathematical modeling. In this study, I construct a regularized regression model for rotavirus inactivation in secondary treated wastewater, in which the operational parameters of wastewater treatment plant are used as explanatory variables.