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Optimising microplastics analysis for quantifying and identifying microplastic fibres in laundry wastewater

The Science of The Total Environment 2024 7 citations

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This methodological paper optimized microplastic analysis protocols for identifying and quantifying particles in environmental samples, comparing extraction, digestion, and spectroscopic identification approaches to improve accuracy and reduce contamination.

Polymers
Study Type Environmental

Current methods for measuring microplastic fibres (MPF) are cumbersome, time consuming and unscalable for routine high throughput analysis. This study reports a method for rapidly extracting, quantifying and analysing MPFs in laundry wastewater with several key improvements which vastly enhance overall efficiency and scalability of analysis. FT-IR surveying is employed as a preliminary step in analysis to quickly determine what polymers are present in a sample prior to fluorescence treatment. Using random quadrating, whole 25 mm filter membranes were surveyed in <30 min with high recovery rates. In industrial laundry wastewater samples, polyester was the most common MPF, however acrylic, nylon, cotton and rayon were all ubiquitous. The study also demonstrates that an excitation wavelength of 365 nm was optimal for fluorescing PET fibres like polyester which were stained with Nile Red, but not 495 nm, which is commonly used in microplastic analysis. Finally, a custom ImageJ macro was written to automatically enumerate and describe MPFs on filter membranes using just a single stitched fluorescence image. In just a few seconds, concentrations of up to 40,000 fibres/L were analysed in industrial laundry wastewater samples with a lower particle size limit of 20 μm. This study highlights the need for more optimised and scalable analysis workflows which maintain high levels of reliability and accuracy.

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