Quantification of Microplastic in Domestic Greywater Using Image Processing and Machine Learning at Microscopic Level

Abstract

Washing processes of synthetic textiles has recently been assessed as one of the main sources of primary microplastics in the oceans. Plastic microplastics (microbeads, fragments and fibres) pass directly from household water into wastewater systems and are too small to be retained by the standard filters used at wastewater treatment plants. Every day, the water treatment plant discharges 160 trillion litres of water effluents with 8 trillion plastic particles into the aquatic ecosystem. Microplastics are ingested by aquatic creatures such as fish and different crustaceans, and finally, people ingest them at the tertiary level of the food chain. Therefore, to reduce existing quantities of microplastics released in the marine environment, there is a need for innovative methods for detection of microplastics. The aim of our project is to create