Detection of SARS-CoV-2 in sewage has been employed by several researchers as an alternative early warning indicator of virus spreading in communities, covering both symptomatic and asymptomatic cases. A factor that can seriously mislead the quantitative measurement of viral copies in sewage is the adsorption of virus fragments onto the highly porous solids suspended in wastewater, making them inaccessible. This depends not only on the available amount of suspended solids, but also on the amount of other dissolved chemicals which may influence the capacity of adsorption. On this account, the present work develops a mathematical framework, at various degrees of spatial complexity, of a physicochemical model that rationalizes the quantitative measurements of total virus fragments in sewage as regards the adsorption of virus onto suspended solids and the effect of dissolved chemicals on it. The city of Thessaloniki in Greece is employed as a convenient case study to determine the values of model variables. The present data indicate the ratio of the specific absorption (UV
During the COVID-19 pandemic, wastewater-based epidemiology (WBE) has been engaged to complement medical surveillance and in some cases to also act as an early diagnosis indicator of viral spreading in the community. Most efforts worldwide by the scientific community and commercial companies focus on the formulation of protocols for SARS-CoV-2 analysis in wastewater and approaches addressing the quantitative relationship between WBE and medical surveillance are lacking. In the present study, a mathematical model is developed which uses as input the number of daily positive medical tests together with the highly non-linear shedding rate curve of individuals to estimate the evolution of global virus shedding rate in wastewater along calendar days. A comprehensive parametric study by the model using as input actual medical surveillance and WBE data for the city of Thessaloniki (~700,000 inhabitants, North Greece) during the outbreak of November 2020 reveals the conditions under which WBE can be used as an early warning tool for predicting pandemic outbreaks. It is shown that early warning capacity is different along the days of an outbreak and depends strongly on the number of days apart between the day of maximum shedding rate of infected individuals in their disease cycle and the day of their medical testing. The present data indicate for Thessaloniki an average early warning capacity of around 2 days. Moreover, the data imply that there exists a proportion between unreported cases (asymptomatic persons with mild symptoms that do not seek medical advice) and reported cases. The proportion increases with the number of reported cases. The early detection capacity of WBE improves substantially in the presence of an increasing number of unreported cases. For Thessaloniki at the peak of the pandemic in mid-November 2020, the number of unreported cases reached a maximum around 4 times the number of reported cases.
Abstract Accounting for SARS-CoV-2 adsorption on solids suspended in wastewater is a necessary step towards the reliable estimation of virus shedding rate in a sewerage system, based on measurements performed at a terminal collection station, i.e., at the entrance of a wastewater treatment plant. This concept is extended herein to include several measurement stations across a city to enable the estimation of spatial distribution of virus shedding rate. This study presents a pioneer general model describing the most relevant physicochemical phenomena with a special effort to reduce the complicated algebra. This is performed both in the topology regime, introducing a discrete-continuous approach, and in the domain of independent variables, introducing a monodisperse moment method to reduce the dimensionality of the resulting population balance equations. The resulting simplified model consists of a large system of ordinary differential equations. A sensitivity analysis is performed with respect to some key parameters for a single pipe topology. Specific numerical techniques are employed for the integration of the model. Finally, a parametric case study for an indicative—yet realistic—sewerage piping system is performed to show how the model is applied to SARS-CoV-2 adsorption on wastewater solids in the presence of other competing species. This is the first model of this kind appearing in scientific literature and a first step towards setting up an inverse problem to assess the spatial distribution of virus shedding rate based on its concentration in wastewater.
Traditionally, anaerobic digestion has been applied to mixed sludge, combining primary sludge (PS) with secondary sludge. However, recent research has unveiled the advantages of dedicated PS digestion due to its higher energy content. Anaerobic digestion (AD) of primary sewage sludge can offer a sustainable solution for managing sewage sludge while generating renewable energy. The present study provides a comprehensive examination of the current state of knowledge regarding the anaerobic digestion of PS. Co-digestion of PS with organic substrates, including food waste and agro-industrial residues, emerges as a promising approach to boost biogas production. Additionally, the utilization of additives such as glucose and clay minerals has shown potential in improving methane yield. Critical factors affecting AD, such as pretreatment methods, carbon-to-nitrogen (C/N) ratio, temperature, pH, volatile fatty acids (VFAs) levels, organic loading rates (OLR), inoculum-to-substrate ratio (ISR), and the role of additives, have been meticulously studied. Finally, this review consolidates existing knowledge to advance our understanding of primary sewage sludge anaerobic digestion, fostering more efficient and sustainable practices in sludge management and renewable energy generation.
