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• W3136756256 abstract "Microplastics (MPs), a growing class of emerging pollutants in the environment, have attracted widespread attention due to their adsorption properties. Recent research on MPs has mainly concentrated on seawater, and little work has been conducted on freshwater. Investigating and predicting the adsorption behavior of organic pollutants by MPs are necessary in freshwater. In this study, the adsorption behavior of 13 organic chemicals by polyethylene (PE) and chlorinated polyethylene (CPE) MPs was determined under freshwater conditions. Results shows the majority of the organic chemicals exhibit no distinctive differences in their adsorption on two MPs. However, the adsorption of polycyclic aromatic hydrocarbons and chlorobenzene on CPE is obviously stronger than that on PE, and the result is a counter for two pesticides. Quantitative structure activity relationship (QSAR) analysis was performed for the prediction of adsorption capacity. A QSAR model with acceptable performance (R2 = 0.8586) was built to predict the adsorptive affinity (expressed as logKd) of organic compounds on the PE MPs via multivariable linear regression (MLR) on forty-nine determined and collected data. The octanol/water partition coefficient (logKow) and excess molar refractive index (E) play dominant roles in the model. A QSAR model with satisfactory performance (R2 = 0.9302) was also established for logKd values from CPE MPs in freshwater by using 13 adsorption data determined. The logKow and most negative charge on Cl atom (Q-max,cl) play decisive roles in the adsorption. The findings can provide a scientific basis for the risk assessment of waters contaminated by MPs and organic pollutants." @default.
• W3136756256 created "2021-03-29" @default.
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• W3136756256 date "2021-06-01" @default.
• W3136756256 modified "2023-10-14" @default.
• W3136756256 title "Prediction of organic compounds adsorbed by polyethylene and chlorinated polyethylene microplastics in freshwater using QSAR" @default.
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• W3136756256 doi "https://doi.org/10.1016/j.envres.2021.111001" @default.
• W3136756256 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/33713711" @default.
• W3136756256 hasPublicationYear "2021" @default.
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