Microplastics seem an ever-increasing blight in waterways, but methods to measure them are evolving, and experts believe no single technology will fill this gap.
In late July, separate studies appeared to reveal high concentrations of microplastics in the tidal Thames, which are being ingested by wildlife.
Research by Alex McGoran of Royal Holloway reported on the ingestion of microplastics by estuarine crabs. Tangles of plastic fibres were found filling the stomach of many crabs. Typically, microplastic ingestion is low in many species, so these results came as a shock, he said.
In another project, Katharine Rowley recorded many forms of microplastic in the Thames, ranging from glitter, microbeads to plastic fragments. Her study found that 93.5% of microplastics in the water column were most likely formed from the fragmentation of larger plastic items, with food packaging thought to be a significant source for these plastics.
Professor René Garello, IEEE fellow and Professor at IMT Atlantique (a technological university in France) commented on the innovations that are being used to track microplastics in the seas and oceans, which might also be required to perform similar measurements in rivers. Effectively tracking and locating plastic in the ocean is a huge challenge, he said, but “we are seeing the emergence of new and collaborative methods of addressing this.” He said the process of quantifying the mass of disintegrating plastics in the ocean requires taking spatially distributed measurements of all sizes and classes of debris on a global scale, as well as the plastic beneath the surface.
Clearly, he said, “this is not a problem that any single technology or nation can solve.” He continued: “Scientists must focus on the acquisition of data from multiple sources – such as satellite imaging mixed with global and local observations – to create models of surface current circulation and give indicators of the levels of plastic presence.”
Another challenge is extracting meaningful information from such a diverse dataset, he said, and improving our ability to make decisions from it. He said: “Given the sheer volume of data, there is a definite need to implement artificial intelligence (AI) in some capacity – via a machine learning or deep learning-based approach – to make sense of what is collected.”
