Identification of microplastics in wastewater samples by means of polarized light optical microscopy.

Identification of microplastics in wastewater samples by means of polarized light optical microscopy.

Sierra, Ignacio;Chialanza, Mauricio Rodríguez;Faccio, Ricardo;Carrizo, Daniel;Fornaro, Laura;Pérez-Parada, Andrés;
Environmental science and pollution research international 2019
331
sierra2019identificationenvironmental

Abstract

Many reports state the potential hazards of microplastics (MPs) and their implications to wildlife and human health. The presence of MP in the aquatic environment is related to several origins but particularly associated to their occurrence in wastewater effluents. The determination of MP in these complex samples is a challenge. Current analytical procedures for MP monitoring are based on separation and counting by visual observation or mediated with some type of microscopy with further identification by techniques such as Raman or Fourier-transform infrared (FTIR) spectroscopy. In this work, a simple alternative for the separation, counting and identification of MP in wastewater samples is reported. The presented sample preparation technique with further polarized light optical microscopy (PLOM) observation positively identified the vast majority of MP particles occurring in wastewater samples of Montevideo, Uruguay, in the 70-600 μm range. MPs with different shapes and chemical composition were identified by PLOM and confirmed by confocal Raman microscopy. Rapid identification of polyethylene (PE), polypropylene (PP) and polyethylene terephthalate (PET) were evidenced. A major limitation was found in the identification of MP from non-birefringent polymers such as PVC (polyvinylchloride). The proposed procedure for MP analysis in wastewater is easy to be implemented at any analytical laboratory. A pilot monitoring of Montevideo WWTP effluents was carried out over 3-month period identifying MP from different chemical identities in the range 5.3-8.2 × 10 MP items/m.

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ID: 76295
Ref Key: sierra2019identificationenvironmental
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76295
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10.1007/s11356-019-07011-y
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Scimatic Chain (ID: 481)
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