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Developing effective strategies to reduce future microplastic emissions and manage existing pollution is challenging. These tiny plastic particles come from diverse sources, including clothing fibers, tire wear, packaging, industrial processes, and the breakdown of larger plastics. Their widespread presence allows them to enter the environment through multiple pathways, complicating prevention efforts. Additionally, once released, most microplastics do not biodegrade and tend to accumulate. Removing them from water bodies remains neither cost-effective nor feasible with current technologies.

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.  

According to United Nations Environment Programme (UNEP), the estimated 11 million metric tons of plastic currently entering the ocean annually will triple by the year 2040. Much of this plastic breaks down into microplastics, less than 5 millimeters in size. These tiny particles are accumulating not only in oceans, but in all the world’s ecosystems, from the highest mountains to the Arctic’s pristine wilderness.

This past November, representatives from at least 170 countries gathered in Busan, South Korea, for the fifth session of the Intergovernmental Negotiating Committee (INC-5). They were tasked with developing an international legally binding instrument on plastic pollution. Although this session was initially expected to conclude the negotiations, it ended without a finalized agreement. Consequently, another meeting will be scheduled for 2025 to continue the discussions.

Microplastics have been found in freshwater ecosystems around the world. Yet, because they are still an emerging contaminant, we lack long-term data about their abundance and sources. One way to fill this gap is by analyzing radiometrically dated lake sediment cores to generate a historical record of microplastic pollution in freshwater environments. These cores act like time capsules, preserving microplastics that have settled over the years.

Thursday, November 28, 2024

Researcher Profile: Meet Erin Griffiths

Erin Griffiths is a master’s student in the Ecohydrology Research Group at the University of Waterloo, led by Professor Philippe Van Cappellen who is the Principal Investigator on the Microplastics Fingerprinting project.

Thursday, September 12, 2024

Researcher Profile: Meet Peter Huck

Until his retirement on September 1, 2024, Peter M. Huck was a Professor in the Department of Civil and Environmental Engineering at the University of Waterloo and was the Natural Sciences and Engineering Research Council (NSERC) Industrial Research Chair in Water Treatment for 31 years, until the completion of the Chair in December, 2023. He plans to continue select research activities post retirement.