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Dataset for characterization of dissolved organic matter extracted from organic wastes and their effects on the transport of titanium dioxide nanoparticles in acidic saturated porous media in the presence of monovalent electrolyte

This dataset is related to the research article in Chemosphere, entitled ‘The limited facilitating effect of dissolved organic matter extracted from organic wastes on the transport of titanium dioxide nanoparticles in acidic saturated porous media’ [1]. The data summarised the characterization of di...

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Detalles Bibliográficos
Autores principales: Zhang, Ruichang, Zhang, Haibo, Tu, Chen, Luo, Yongming
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6940654/
https://www.ncbi.nlm.nih.gov/pubmed/31909119
http://dx.doi.org/10.1016/j.dib.2019.105021
Descripción
Sumario:This dataset is related to the research article in Chemosphere, entitled ‘The limited facilitating effect of dissolved organic matter extracted from organic wastes on the transport of titanium dioxide nanoparticles in acidic saturated porous media’ [1]. The data summarised the characterization of dissolved organic matter (DOM) extracted from organic wastes and their effects on the transport of titanium dioxide nanoparticles (TiO(2) NPs) in acidic saturated porous media in the presence of monovalent electrolyte. Three types of dissolved organic matter were extracted from organic materials, including swine manure, sludge, and sediment, using deionized water, and were characterized with UV–Vis, FTIR and elementary analysis. The adsorption of DOM onto TiO(2) NPs was evaluated in the presence of NaCl, and zeta potentials of TiO(2) NPs were also determined. Breakthrough column experiments were conducted to quantify the effects of the extracted DOM on the transport behaviours of TiO(2) NPs in acidic porous media compared with humic acid. Moreover, the interaction energy between nanoparticles and between nanoparticles and quartz media was calculated according to the classical DLVO theory. The dataset could be used as a reference for the evaluation and prediction of the environmental fate and subsequent risk of engineered nanomaterials.