Effect of cationic, anionic and non-ionic surfactants on transport of microplastics: Role of adhesion of surfactants on the polyethylene surface

Sun, Huimin; Zhou, Shi; Jiang, Yanji; Qin, Zhiming; Jiao, Fei; Sun, Yuebing; Wang, Jun; Yin, Xianqiang

doi:10.1016/j.jhydrol.2022.128051

Cited by 27 publications

(2 citation statements)

References 43 publications

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“…To determine the optimal EPS concentration for dispersing MPs, we first assessed the organic carbon composition of EPS derived from biofilms, where EPS predominantly consisted of hydrophilic chromophoric dissolved organic carbon (CDOC), accounting for 89% of its total (carbon) mass concentration (Table S5). EPS with high CDOC content adsorbed on the surface of MPs, improving the hydrophilicity and stability of MPs . Chromatographic fractionation indicated that the dominant components of EPS were humic substances and their degradation products, along with soluble microbial products such as amino acids, alcohols, and sugars (Table S5 and Figure S5a).…”

Section: Resultsmentioning

confidence: 99%

“…EPS with high CDOC content adsorbed on the surface of MPs, improving the hydrophilicity and stability of MPs. 38 Chromatographic fractionation indicated that the dominant components of EPS were humic substances and their degradation products, along with soluble microbial products such as amino acids, alcohols, and sugars (Table S5 and Figure S5a). Finally, by employing 1−4 and 10−32 μm PE spheres as model MPs to assess dispersion, we identified the optimal EPS concentration to create the most stable suspension was 9 mg C L −1 (Table S6).…”

Section: Microplastics Are Effectively Dispersed In Watermentioning

confidence: 99%

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Differentiating Microplastics from Natural Particles in Aqueous Suspensions Using Flow Cytometry with Machine Learning

Wang,

Li,

Kroll

et al. 2024

Environ. Sci. Technol.

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Microplastics (MPs) in natural waters are heterogeneously mixed with other natural particles including algal cells and suspended sediments. An easy-to-use and rapid method for directly measuring and distinguishing MPs from other naturally present colloids in the environment would expedite analytical workflows. Here, we established a database of MP scattering and fluorescence properties, either alone or in mixtures with natural particles, by stain-free flow cytometry. The resulting highdimensional data were analyzed using machine learning approaches, either unsupervised (e.g., viSNE) or supervised (e.g., random forest algorithms). We assessed our approach in identifying and quantifying model MPs of diverse sizes, morphologies, and polymer compositions in various suspensions including phototrophic microorganisms, suspended biofilms, mineral particles, and sediment. We could precisely quantify MPs in microbial phototrophs and natural sediments with high organic carbon by both machine learning models (identification accuracies over 93%), although it was not possible to distinguish between different MP sizes or polymer compositions. By testing the resulting method in environmental samples through spiking MPs into freshwater samples, we further highlight the applicability of the method to be used as a rapid screening tool for MPs. Collectively, this workflow can be easily applied to a diverse set of samples to assess the presence of MPs in a time-efficient manner.

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Section: Resultsmentioning

confidence: 99%

Section: Microplastics Are Effectively Dispersed In Watermentioning

confidence: 99%