Literature DB >> 27883919

Bayesian belief network modelling of chlorine disinfection for human pathogenic viruses in municipal wastewater.

Guido Carvajal1, David J Roser2, Scott A Sisson3, Alexandra Keegan4, Stuart J Khan5.   

Abstract

Chlorine disinfection of biologically treated wastewater is practiced in many locations prior to environmental discharge or beneficial reuse. The effectiveness of chlorine disinfection processes may be influenced by several factors, such as pH, temperature, ionic strength, organic carbon concentration, and suspended solids. We investigated the use of Bayesian multilayer perceptron (BMLP) models as efficient and practical tools for compiling and analysing free chlorine and monochloramine virus disinfection performance as a multivariate problem. Corresponding to their relative susceptibility, Adenovirus 2 was used to assess disinfection by monochloramine and Coxsackievirus B5 was used for free chlorine. A BMLP model was constructed to relate key disinfection conditions (CT, pH, turbidity) to observed Log Reduction Values (LRVs) for these viruses at constant temperature. The models proved to be valuable for incorporating uncertainty in the chlor(am)ination performance estimation and interpolating between operating conditions. Various types of queries could be performed with this model including the identification of target CT for a particular combination of LRV, pH and turbidity. Similarly, it was possible to derive achievable LRVs for combinations of CT, pH and turbidity. These queries yielded probability density functions for the target variable reflecting the uncertainty in the model parameters and variability of the input variables. The disinfection efficacy was greatly impacted by pH and to a lesser extent by turbidity for both types of disinfections. Non-linear relationships were observed between pH and target CT, and turbidity and target CT, with compound effects on target CT also evidenced. This work demonstrated that the use of BMLP models had considerable ability to improve the resolution and understanding of the multivariate relationships between operational parameters and disinfection outcomes for wastewater treatment.
Copyright © 2016 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Bayesian belief networks; Chlorination; Modelling; Multilayer perceptron; Removal efficiency; Virus

Mesh:

Substances:

Year:  2016        PMID: 27883919     DOI: 10.1016/j.watres.2016.11.008

Source DB:  PubMed          Journal:  Water Res        ISSN: 0043-1354            Impact factor:   11.236


  4 in total

1.  Interlaboratory Comparative Study to Detect Potentially Infectious Human Enteric Viruses in Influent and Effluent Waters.

Authors:  Walter Randazzo; Joaquín Piqueras; Zoran Evtoski; Guadalupe Sastre; Raquel Sancho; Carina Gonzalez; Gloria Sánchez
Journal:  Food Environ Virol       Date:  2019-06-01       Impact factor: 2.778

2.  Comparative study on the efficacy of sodium hypochlorite, aqueous ozone, and peracetic acid in the elimination of Salmonella from cattle manure contaminated various surfaces supported by Bayesian analysis.

Authors:  Ameer Megahed; Brian Aldridge; James Lowe
Journal:  PLoS One       Date:  2019-05-23       Impact factor: 3.240

Review 3.  Where do we stand to oversee the coronaviruses in aqueous and aerosol environment? Characteristics of transmission and possible curb strategies.

Authors:  Bin Ji; Yaqian Zhao; Abraham Esteve-Núñez; Ranbin Liu; Yang Yang; Ange Nzihou; Yiping Tai; Ting Wei; Cheng Shen; Yan Yang; Baimimng Ren; Xingxing Wang; Ya'e Wang
Journal:  Chem Eng J       Date:  2020-10-27       Impact factor: 13.273

4.  Influence of surface properties and antecedent environmental conditions on particulate-associated metals in surface runoff.

Authors:  Zhenyu Wang; Pei Hua; Heng Dai; Rui Li; Beidou Xi; Dongwei Gui; Jin Zhang; Peter Krebs
Journal:  Environ Sci Ecotechnol       Date:  2020-02-08
  4 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.