Journal
MARINE POLLUTION BULLETIN
Volume 181, Issue -, Pages -Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.marpolbul.2022.113897
Keywords
Microplastics; Infrared spectrometry; Reflectance; Weathering; Pattern recognition; Variable selection
Funding
- EU [101003954]
- JPI Oceans Program [PCI2020112145]
- Spanish Government, MCIN/AEI
- European Union
- QANAP group (Programa de Consolidacion y Estructuracion de Unidades de Investigacion Competitiva) [ED431C 2021/56]
- Universidade da Coruna/CISUG
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This study explores the use of infrared spectra combined with pattern recognition techniques to identify different polymers, regardless of their aging. The results show that it is possible to successfully identify them using a reduced number of spectral wavenumbers with coherent chemical meaning.
The presence and effects of microplastics in the environment is being continuously studied, so the need for a reliable approach to ascertain the polymer/s constituting them has increased. To characterize them, infrared (IR) spectrometry is commonly applied, either reflectance or attenuated total reflectance (ATR). A common problem when considering field samples is their weathering and biofouling, which modify their spectra. Hence, relying on spectral matching between the unknown spectrum and spectral databases is largely defective. In this paper, the use of IR spectra combined with pattern recognition techniques (principal components analysis, classification and regression trees and support vector classification) is explored first time to identify a collection of typical polymers regardless of their ageing. Results show that it is possible to identify them using a reduced suite of spectral wavenumbers with coherent chemical meaning. The models were validated using two datasets containing artificially weathered polymers and field samples.
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