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Population balance modeling coupled with extended DLVO theory to describe nanoplastic agglomeration in water

Journal of Contaminant Hydrology 2025 2 citations ? Citation count from OpenAlex, updated daily. May differ slightly from the publisher's own count. Score: 48 ? 0–100 AI score estimating relevance to the microplastics field. Papers below 30 are filtered from public browse.
Dong Zhang, Valentina Prigiobbe

Summary

Researchers coupled population balance equations with extended DLVO colloidal theory to model how water chemistry and UV radiation drive nanoplastic agglomeration in aquatic systems, validating the model against experimental data and demonstrating its potential to predict nanoplastic transport in surface water and improve filtration system design.

Agglomeration of nanoplastic particles (NPs) is a natural process in aquatic systems and it is governed largely by water composition and plastic polymer type. When NPs agglomerate, gravitational settling is enhanced, inhibiting NPs migration in soil and water bodies and therefore favoring NPs accumulation in sediments and on riverbeds. In this paper, the agglomeration of NPs was modeled by coupling the population balance equation (PBE) model with the extended-DLVO (XDLVO) theory. A wide range of water compositions and the effects of UV radiation were considered to provide a comprehensive analysis. Measurements of the evolution of hydrodynamic particle diameter over time in conjunction with physico-biochemical parameters of the investigated systems were taken from the literature and used to validate our calculations. Overall, the model demonstrates strong agreement with experimental measurements and successfully captures the influence of chemical and biological compounds in water, as well as the effect of sunlight. The model has the potential to be integrated into mathematical frameworks to predict NP transport in surface water and groundwater. Additionally, it can guide the design and the operation of advanced filtration units where NP agglomeration could improve removal.

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