4.6 Article

Population balance modeling of homogeneous viral aggregation

期刊

CHEMICAL ENGINEERING SCIENCE
卷 247, 期 -, 页码 -

出版社

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.ces.2021.117035

关键词

Aggregation; Extended DLVO theory; Mathematical modeling; Population balance equation; Virus

资金

  1. Stevens Excellence Doctoral Fellowship Program

向作者/读者索取更多资源

This study presents a model for homogeneous viral aggregation based on the population balance equation (PBE) to describe the evolution of aggregate size, coupled with the extended DLVO theory to account for the energy of interaction between viral particles. The model, verified with literature data, can be an effective tool to simulate the evolution of viral aggregates in water and sediments, providing important insights for viral survival and transport.
Viral aggregation is a natural process which helps viruses to survive in the environment and to resist to disinfection. Aggregation is a complex phenomenon controlled by the isoelectric point of the viral suspension. Previous models describe the energies of interaction between viruses using the extended DLVO theory. However, they do not allow us to predict the evolution of the viral aggregates size, which is critical for viral survival and transport. In this paper, we present a model for homogeneous viral aggregation based on the population balance equation (PBE) to describe the evolution of aggregate size. The PBE was coupled with the extended-DLVO theory to account for the energy of interaction between viral particles affected by virus type and physicochemical conditions. The model was verified with literature data and no parameter fitting was required as all the model parameters are based on the physicochemical properties of the system. Overall, this model can be an useful tool to simulate viral aggregate evolution in water and in sediments. It can be extended to describe heterogeneous viral aggregation and coupled with transport models for the prediction of virus migration and persistence in groundwater. (c) 2021 Elsevier Ltd. All rights reserved.

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