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Wastewater-based epidemiology (WBE) is successful in the detection of the spread of SARS-CoV-2. This review examines the methods used and results of recent studies on the quantification of SARS-CoV-2 in wastewater. WBE becomes essential, especially with virus transmission path uncertainty, limitations on the number of clinical tests that could be conducted, and a relatively long period for infected people to show symptoms. Wastewater surveillance was used to show the effect of lockdown on the virus spread. A WBE framework tailored for SARS-CoV-2 that incorporates lessons learnt from the reviewed studies was developed. Results of the review helped outline challenges facing the detection of SARS-CoV-2 in wastewater samples. A comparison between the various studies with regards to sample concentration and virus quantification was conducted. Five different primers sets were used for qPCR quantification; however, due to limited data availability, there is no consensus on the most sensitive primer. Correlating the slope of the relationship between the number of gene copies vs. the cumulative number of infections normalized to the total population served with the average new cases, suggests that qPCR results could help estimating the number of new infections. The correlation is improved when a lag period was introduced to account for asymptomatic infections. Based on lessons learnt from recent studies, it is recommended that future applications should consider the following: 1) ensuring occupational safety in managing sewage collection and processing, 2) evaluating the effectiveness of greywater disinfection, 3) measuring viral RNA decay due to biological and chemical activities during collection and treatment, 4) assessing the effectiveness of digital PCR, and 5) conducting large scale international studies that follow standardized protocols.

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Several previously reported laboratory studies related to transport of solutes through packed columns were utilized to develop predictive relationships for mass-transfer rate coefficient. The data were classified into two groups: those obtained under rate-limited mass transfer between mobile and immobile water regions (physical nonequilibrium conditions), and those derived from rate-limited mass transfer between instantaneous and slow sorption sites (sorption nonequilibrium conditions). The mass-transfer coefficient in all these studies was obtained by fitting breakthrough data to a transport model employing a first-order rate limitations with a "constant" mass-transfer coefficient, independent of flow conditions. This study demonstrated that the mass-transfer coefficient in these models is dependent on system parameters including pore-water velocity, length-scale, retardation coefficient, and particle or aggregate size. Predictive relationships were developed, through regression analysis, relating mass-transfer coefficient to residence time. The developed relationships adequately estimated previously reported field mass-transfer values. Successful simulations of field desorption data reported by Bahr [J. Contam. Hydrol. 4 (1989) 205] further demonstrate the potential applicability of the developed relationships.

Batch and column techniques were utilized to determine retardation coefficients of two nonionic organic compounds: benzene and dimethylphthalate. Three sandy soil materials with medium to high organic C content were used as sorbents. Batch data consistently overestimated retardation coefficients of the two compounds. Several previously reported factors that may cause discrepancy between the two techniques were experimentally investigated. Sorption nonsingularity, sorption nonequilibrium, presence of immobile water regions in the column, and reduction in particle spacing in the column were eliminated as the cause of this discrepancy. Loss of sorbent from the column is unlikely to be the cause of the discrepancy. Although rapidly mixed batch tubes are subjected to soil abrasion, it causes no apparent impact on the value of sorption distribution coefficients. Batch isotherms at two solids concentrations were identical, indicating that differences in solids concentration between batch and column setup is not a significant factor. This was also confirmed by a column study. Sorption nonlinearity was found to have a minor impact. Column residence time had a major impact on one of the cases studied, but no effect on the other cases. When column residence time was accounted for, some differences in sorption distribution coefficients, which seemed to be independent of the organic C content, were noticed. In this study, all previously suggested causes for the discrepancy between batch‐ and column‐determined retardation coefficients were investigated and rejected. It remains unclear why the values determined by the two techniques were different.