The case for credit: toward a mechanistic model of solids partitioning and virus removal for secondary biological wastewater treatment

Regulatory frameworks for potable reuse often include stringent log reduction value (LRV) targets for viruses and protozoa. To reliably protect public health while also considering the sustainability of advanced water treatment, it is critically important to accurately and rapidly assess pathogen removal and avoid under-crediting of any unit process in a potable reuse treatment train. This study systematically evaluates secondary biological wastewater treatment across solids retention times (SRTs) ranging from 2 to 20 days and uses culture and molecular methods to characterize attenuation of 12 viruses, including fecal indicators, surrogate bacteriophages, and enteric pathogens. This study also proposes a mechanistic model for physical removal based on a solids partitioning/adsorption framework incorporating mixed liquor suspended solids (MLSS) concentrations. Mean sample-specific partitioning coefficients (K<sub>d</sub>) ranged from 2.1 log<sub>10</sub> mL/g for cucumber green mottle mosaic virus (CGMMV) to 3.8 log<sub>10</sub> mL/g for phiX174. K<sub>d</sub> values were strongly correlated with LRVs, although the resulting adsorption models (sample-specific, linear, and Freundlich) could not fully explain the large variability in virus removal across all conditions. LRVs of 1-3 were observed for all viruses, but the 5<sup>th</sup> percentile LRVs that drive regulatory determinations were often <0.5. This study proposes several approaches for awarding implicit LRVs of ≥1 using quantitative microbial risk assessment (QMRA) coupled with observed secondary treatment performance or secondary effluent concentrations.

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Publication Details

Journal
Water Research
Published
2025-05-17
DOI
https://doi.org/10.1016/j.watres.2025.123857
Citations
3
Primary Topic
SARS-CoV-2 detection and testing
Type
article
Field-Weighted Citation Impact
4.19

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article

The case for credit: toward a mechanistic model of solids partitioning and virus removal for secondary biological wastewater treatment

Andrew P. Black, Tyler Hill, Phillip Wang, Daniel Gerrity et al.
3 citations
Water Research
SARS-CoV-2 detection and testing
4.19
article

The case for credit: toward a mechanistic model of solids partitioning and virus removal for secondary biological wastewater treatment

Andrew P. Black, Tyler Hill, Phillip Wang, Daniel Gerrity, Christina M. Morrison, Jacimaria R. Batista, Katherine Crank, Bonnie Mull
article en
3 citations

Abstract

Regulatory frameworks for potable reuse often include stringent log reduction value (LRV) targets for viruses and protozoa. To reliably protect public health while also considering the sustainability of advanced water treatment, it is critically important to accurately and rapidly assess pathogen removal and avoid under-crediting of any unit process in a potable reuse treatment train. This study systematically evaluates secondary biological wastewater treatment across solids retention times (SRTs) ranging from 2 to 20 days and uses culture and molecular methods to characterize attenuation of 12 viruses, including fecal indicators, surrogate bacteriophages, and enteric pathogens. This study also proposes a mechanistic model for physical removal based on a solids partitioning/adsorption framework incorporating mixed liquor suspended solids (MLSS) concentrations. Mean sample-specific partitioning coefficients (K<sub>d</sub>) ranged from 2.1 log<sub>10</sub> mL/g for cucumber green mottle mosaic virus (CGMMV) to 3.8 log<sub>10</sub> mL/g for phiX174. K<sub>d</sub> values were strongly correlated with LRVs, although the resulting adsorption models (sample-specific, linear, and Freundlich) could not fully explain the large variability in virus removal across all conditions. LRVs of 1-3 were observed for all viruses, but the 5<sup>th</sup> percentile LRVs that drive regulatory determinations were often <0.5. This study proposes several approaches for awarding implicit LRVs of ≥1 using quantitative microbial risk assessment (QMRA) coupled with observed secondary treatment performance or secondary effluent concentrations.

Water ResearchVol. 283
Southern Nevada Water Authority (US), University of Nevada, Las Vegas (US), Biological Consulting Services (United States) (US)
U.S. Environmental Protection Agency, Water Research Foundation
Clean water and sanitation
Openalex Percentile: Top 6%
SARS-CoV-2 detection and testing
4.19
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