Microplastics Fingerprinting

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Welcome to the Microplastics Fingerprinting project

Plastics pollution is a global and growing environmental hazard with potentially far-reaching consequences for food webs, biodiversity, ecosystem services and human well-being. Of particular concern are microplastics because their small sizes enhance their mobility, toxicity to wildlife, and capacity to leach potentially dangerous contaminants.

The Microplastics Fingerprinting at the watershed scale: from sources to receivers projectseeks to better understand the sources, transport, fate and exposure risks of microplastics at a watershed scale in the lower Great Lakes. In doing so, we hope to inform program and policy approaches that can mitigate risks posed by plastic debris in the environment.    

The project will analyze the reactivity and breakdown of microplastics in river systems and reservoirs, quantify the loads of microplastics delivered to the lower Great Lakes, optimize microplastics elimination in wastewater treatment plants, and determine the abundance and diversity of microplastics in drinking water sources.

This project is supported by the NSERC Alliance Grant competition on plastics science for a cleaner future. The project will contribute to Canada’s Plastics Science Agenda (CaPSA).

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News

Urban areas are increasingly recognized as major contributors to microplastics (MP) pollution, with stormwater runoff serving as a primary transport pathway. While many studies have documented the presence of MPs in stormwater, understanding the underlying causes and accurately forecasting contamination levels requires robust modeling efforts.

Researchers in the Smith Group at the University of Waterloo, in collaboration with the Microplastics Fingerprinting project, have developed a new machine learning model to improve microplastic identification. This model is based on a k-Nearest Neighbors (kNN) approach and analyzes a library of Raman spectra from various plastics to enhance accuracy.