Counting and sizing microplastic fibres, the accurate and easy way

Kunnen, T.H., Gerber, G., Moodley, G.K. and Robertson–Andersson, D.V

University of KwaZulu–Natal

Abstract

With an annual demand for plastic in excess of 245 million tonnes, plastic pollution is ranked as one of the greatest threats to marine life. Marine plastic pollution consists of both macroplastic particles (> 5 mm) and microplastics. Microplastics which are manufactured to be less than 5 mm in size (primary microplastics) are generally used for the purposes of commercial and industrial abrasives, while secondary microplastics result from the disintegration of larger plastic particles. This may occur from physical forces such as abrasion or UV exposure. Currently one of the most common sources of secondary microplastic particles is the shearing of plastic textile fibres from washing machines, and with the increase in domestic appliance reliance, microplastic pollution rates are escalating. The need to accurately and reliably count and size microplastic particles from environmental samples or laboratory experiments is impeded by the slow process of sifting through sand and gut contents and the need to manually evaluate the particles with microscopy. We present here the use of a macro-enabled counting and analysis program coded specifically for IPP (Image Pro Plus) for the automated analysis of fluorescent microplastic fibres. To test the efficiency, accuracy and reproducibility of the above automated counting feature, 50 microfibre images were given to 5 volunteers to manually count and size. This data was compared to data collected from the automated counting feature for accuracy of counts, size measurements and time taken for analysis. The macro showed no statistical differences between the numbers of fibres counted and total length, but there was a statistical difference in fibre width. A significant statistical difference was found for average time taken with 23.90 ± 6.86 vs 1.2 ± 0.77 mins for manual and automated analysis respectively per filter (12 images), resulting in a massive 2382.92% decrease in time.