Abstract:
Plastics have permeated almost every aspect of modern day life with its wide applicability. The tragic consequence is millions of pieces of plastic polluting and harming ...Show MoreMetadata
Abstract:
Plastics have permeated almost every aspect of modern day life with its wide applicability. The tragic consequence is millions of pieces of plastic polluting and harming sea life every day. The road towards a clean sea contains several legs and requires mapping of the ocean water column to determine critical areas. Determining technologies and methods for the detection of microplastics underwater are hence a necessity. Raman spectroscopy is such a technology, in principle able to extract the chemical structure of the object to be viewed by collecting spectral signatures at the point illuminated. This creates the foundation for the research presented in this paper, aiming to cover whether it is possible to classify specific types of microplastics underwater by identifying their respective spectral signatures. Raman spectroscopy has been carried out on three different cases of samples. The first case involves known plastic, ordered from CARAT AS, with the purpose of creating the foundation of a partial least squares discriminant analysis (PLS-DA) model. The second case holds the same base but includes drops of water on top of the original sample. This case provided data for testing the prediction of the PLS-DA model. The third case includes raw plastic pieces, collected from the sea outside Svolvær, Lofoten. The measurements of these samples create the grounds for the last test-set. The results suggest that the method can classify microplastic correctly, both in water and sea-influenced pieces. However, the specific spectra cannot vary too much as a result of industrial and environmental changes altering the condition of the plastic, and thereby the spectrum. This leaves the mapping and classification method best suited for plastics that recently entered the ocean.
Published in: OCEANS 2019 MTS/IEEE SEATTLE
Date of Conference: 27-31 October 2019
Date Added to IEEE Xplore: 20 January 2020
ISBN Information:
Print on Demand(PoD) ISSN: 0197-7385