AI-assisted technology instantly detects nanoplastics in water

A research team led by McGill University has developed the first real-time, on-site technology that can detect and distinguish nanoplastics from all other particles in water – the equivalent of being able to find a needle in a haystack within milliseconds.

The study, “Nanoplastics in Water: 4D Physicochemical Characterization and Rapid In Situ Detection through Artificial Intelligence,” Environmental Science and Technology.

Microplastic pieces are between 1 micrometer and 5 millimeters in size – about the size of a grain of rice. Nanoplastics are much smaller – 1 nanometer is just 0.000001 millimeters. By comparison, the width of a human hair is around 80,000 to 100,000 nanometers.

“This technology has the potential to revolutionize how we monitor and manage plastic pollution, ultimately contributing to protecting the environment,” said lead study author Parisa Arya, James McGill Professor in McGill University's Department of Chemistry and Department of Atmospheric and Oceanic Sciences.

According to the United Nations Environment Programme (UNEP), approximately 2,000 garbage trucks' worth of plastic is dumped into the world's oceans, rivers and lakes every day. Understanding the impact of nanoplastics on ecosystems has been difficult due to limitations in existing detection methods.

This artificial intelligence-driven innovation addresses a critical need: real-time analysis of plastic pollution. The technology, AI-assisted nano-digital in-line holographic microscope, dubbed “AI-assisted nano-DIHM,” has been garnering attention from experts since it was announced in a recent publication.

A practical tool for identifying contamination “hot spots”

“Our study demonstrates that AI-assisted nano-DIHM can automatically detect and distinguish nano- and microplastics, even when they are covered by other particles, providing a comprehensive understanding of plastic pollution in aquatic ecosystems,” Arya said.

The technology provides a practical tool to more effectively identify and address pollution “hot spots.” Preliminary findings from Lake Ontario and the St. Lawrence River show that the AI-assisted Nano-DIHM can identify micro- and nanoplastics within underwater particles.

This pioneering technology, developed in collaboration with the National Research Council of Canada, represents a significant advancement in environmental monitoring.