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Improving of an easy, effective and low-cost method for isolation of microplastic fibers collected in drying machines filters

The Science of The Total Environment 2023 18 citations ? Citation count from OpenAlex, updated daily. May differ slightly from the publisher's own count.
Maja Vujić, Vasiljević Sanja, Rocha-Santos Teresa, Agbaba Jasmina, Zoran Čepić, Radonić Jelena, Tubić Aleksandra

Summary

Researchers improved and validated a low-cost method for isolating microplastic fibers from water samples, addressing methodological gaps in measuring fiber release from clothing in both washing and mechanical drying processes.

Microplastic fibers have been found to be a dominant form of microplastics in water matrixes, and textile industry and domestic washing of synthetic textiles as one of its main sources. Additionally, there is a lack of knowlidge about microplastic fiber release during mechanically drying clothes and textiles due to differences in the isolation of microplastic fiber methods. Limited information available in the literature in terms of the isolation of microplastic fibers from organic-rich samples after using different household equipment represents one of the main challenges leading us to our main goal, to optimise an effective, simple, and low-cost method for the isolation of microplastic fibers from textile fibers of different origins without damaging their structure. This is achieved by primarily removing mineral matter by using density separation with a saturated solution of ZnCl followed by removal of organic matter by using hydrogen peroxide (HO) and FeCl as a catalyst. Identification of microplastic fibers was obtained by optical microscope, Fourier-transform infrared spectroscopy and Thermogravimetric analysis. Clear microscope (both optical and SEM) images, high percentage of obtained FTIR spectra overlap with Polymer Sample laboratory, clear TGA of isolated samples confirmed that this method can be used as a simple and effective method for isolation of microplastic fibers from organic components rich samples of different origin.

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