Microplastics in our ocean waters are a growing problem – but how do you collect quick and effective measurements in-situ, and at the depths needed to properly understand distribution, flow, and uptake by ocean life? Filtration-based methods using FTIR and Raman microscopy are well-proven, but work best for surface measurements where microplastic densities are higher. A collaboration of researchers from Japan and the UK are developing a compact, hybrid system using holography and Raman spectroscopy capable of in-situ monitoring of particle size, shape, and material – offering promise for monitoring at depths where sea life outnumbers the plastics.
Plastic pollution in the oceans is not confined to the surface, nor to discrete items like plastic bags or accumulations like the Pacific Garbage Patch. As these primary sources of plastic pollution break down, they create secondary pollution in the form of microplastics – particles below 5 mm in size – that can more easily be transported to all reaches and depths of the oceans. There, they can be ingested by all types of marine life, becoming part of a food chain upon which many species depend. In-situ monitoring data is needed to assess the extent, distribution, and changes in microplastic buildup in the ocean over time, particularly as a function of depth. This data will aid studies on the interaction of organisms and microplastics, and can be used to improve models of vertical transport. In future, it will help to guide remediation efforts, and gauge their effectiveness.
Many of the existing “collect & separate” methods for identification of microplastics are geared to sampling of surface waters, and require filtration to concentrate the sample sufficiently for detection. The spectra obtained via Raman spectroscopy is information-rich, but being a weak signal, is easier to obtain with a bulk sample. In deeper waters, the density of microplastics is far lower than at the surface, while the presence of native wildlife of similar dimensions can be rich. This poses two challenges for Raman-based detection: 1) achieving the needed signal, and 2) scanning sufficient volumes of seawater in the presence of unwanted background or ‘noise’.
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