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Published on: March 28, 2015
Volatile solids demonstrate better performance and reliability as a normalization parameter in upper sewershed
Lena Carolin Bitter1, Richard Kibbee1, Gabriela C Jiménez1
1Department of Civil and Environmental Engineering, Carleton University, 1125 Colonel By Drive, Ottawa, ON, K1S 5B6, Canada.
Volatile solids (VS) are a more reliable parameter for normalizing SARS-CoV-2 concentrations in wastewater surveillance than total solids, PMMoV, or flow. VS normalization improves trend detection and public health decision-making.
Area of Science:
- Environmental science
- Public health
- Virology
Background:
- Wastewater-based epidemiology relies on normalization parameters to account for population and system variability.
- Commonly used parameters like total solids (TS), pepper mild mottle virus (PMMoV), and flow often show inconsistencies across different locations and time.
Purpose of the Study:
- To assess the reliability of volatile solids (VS) as a normalization parameter for SARS-CoV-2 RNA concentrations in wastewater.
- To compare the performance of VS with TS, PMMoV, and average daily flow.
Main Methods:
- Quantified SARS-CoV-2 RNA in liquid and solid wastewater fractions.
- Evaluated normalization parameter performance by analyzing trends relative to raw SARS-CoV-2 concentrations.
- Identified site-specific factors influencing normalization reliability, including weather events and sewer travel times.
Main Results:
- Volatile solids (VS) remained relatively unaffected by weather events and inorganic solids, unlike TS.
- PMMoV showed high variability due to seasonal and dietary changes, with sewer travel time impacting normalization.
- Flow normalization was useful in precipitation-impacted systems but faced measurement challenges.
Conclusions:
- Volatile solids (VS) demonstrated superior reliability for normalizing SARS-CoV-2 concentrations compared to TS, PMMoV, and flow.
- VS normalization is less susceptible to weather, inorganic solids, and sewer travel time variations.
- Using VS enhances the accuracy of wastewater surveillance data interpretation for public health.
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