Journal
JOURNAL OF WATER AND HEALTH
Volume 14, Issue 6, Pages 879-889Publisher
IWA PUBLISHING
DOI: 10.2166/wh.2016.096
Keywords
Bayesian estimation; left-censored data; log-normal distribution; paired and unpaired data; virus reduction efficiency; wastewater reclamation and reuse
Categories
Funding
- Japan Society for the Promotion of Science [26249075]
- Grants-in-Aid for Scientific Research [26249075] Funding Source: KAKEN
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The virus reduction efficiency of each unit process is commonly determined based on the ratio of virus concentration in influent to that in effluent of a unit, but the virus concentration in wastewater has often fallen below the analytical quantification limit, which does not allow us to calculate the concentration ratio at each sampling event. In this study, left-censored datasets of norovirus (genogroup I and II), and adenovirus were used to calculate the virus reduction efficiency in unit processes of secondary biological treatment and chlorine disinfection. Virus concentration in influent, effluent from the secondary treatment, and chlorine-disinfected effluent of four municipal wastewater treatment plants were analyzed by a quantitative polymerase chain reaction (PCR) approach, and the probabilistic distributions of log reduction (LR) were estimated by a Bayesian estimation algorithm. The mean values of LR in the secondary treatment units ranged from 0.9 and 2.2, whereas those in the free chlorine disinfection units were from -0.1 and 0.5. The LR value in the secondary treatment was virus type and unit process dependent, which raised the importance for accumulating the data of virus LR values applicable to the multiple-barrier system, which is a global concept of microbial risk management in wastewater reclamation and reuse.
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