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Impact of nanoplastics on membrane scaling and fouling in reverse osmosis desalination process

Water Research 2023 26 citations ? Citation count from OpenAlex, updated daily. May differ slightly from the publisher's own count. Score: 45 ? 0–100 AI score estimating relevance to the microplastics field. Papers below 30 are filtered from public browse.
Qinghao Yang, Jiaojiao Zhang, Na Zhang, Dong Wang, Xian-Zheng Yuan, Chuyang Y. Tang, Baoyu Gao, Zhining Wang

Summary

This study investigated how polystyrene nanoplastics affect membrane scaling and fouling in reverse osmosis desalination, finding that nanoplastics interacted with silica to alter fouling behavior and reduce membrane performance. The results highlight nanoplastics as a potentially disruptive contaminant for desalination infrastructure.

Polymers

Nanoplastics (NPs) are a prevalent type of emerging pollutant in marine environment. However, their fouling behavior and impact on reverse osmosis (RO) membrane performance remain unexplored. We investigated the relationship between polystyrene (PS), one of the most abundant NPs, with silica scaling and humic acid (HA) fouling in RO. The results demonstrated that the surface potential of NPs played an important role in the combined scaling and fouling process. Compared with the negatively charged NPs (original PS and carboxyl group modified PS, PS-COOH), the amino-functionalized PS (PS-NH) with positive surface charge significantly accelerated membrane scaling/fouling and induced a synergistic water flux decline, due to the strong electrostatic attraction between PS-NH, foulants, and the membrane surface. The amino groups acted as binding sites, which promoted the heterogeneous nucleation of silica and adsorption of HA, then formed stable composite pollutants. Thermodynamic analysis via isothermal titration calorimetry (ITC) further confirmed the spontaneous formation of stable complexes between PS-NH and silicates/HA. Our study provides new insights into the combined NPs fouling with other scalants or foulants, and offers guidance for the accurate prediction of RO performance in the presence of NPs.

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