Methodology Used for the Detection and Identification of Microplastics—A Critical Appraisal

Microplastics in aquatic ecosystems and especially in the marine environment represent a pollution of increasing scientific and societal concern, thus, meanwhile a substantial number of studies on microplastics exist. Although first steps towards a standardisation of methodologies used for the detection and identification of microplastics in environmental samples are made, the comparability of data on microplastics is currently hampered by a huge variety of different methodologies which result in the generation of data of extremely different quality and resolution. This chapter reviews the methodology presently used for assessing the concentration of microplastics in the marine environment with focus on the most convenient techniques and approaches. After an overview of non-selective sampling approaches, sample processing and treatment in the laboratory, the reader is introduced to the currently applied techniques for the identification and quantification of microplastics. The subsequent case study on microplastics in sediment samples from the North Sea measured with focal plane array (FPA)-based micro-Fourier transform infrared (micro-FTIR) spectroscopy shows that only 1.4 % of the particles visually resembling microplastics were of synthetic polymer origin. This finding emphasizes the importance of verifying the synthetic polymer origin of potential microplastics. Thus, a burning issue concerning current microplastic research is the generation of standards that allow for the assessment of reliable data on concentrations of microscopic plastic particles and the involved polymers with analytical laboratory techniques such as micro-FTIR or micro-Raman spectroscopy

Microplastics Detection Using Pyrolysis-GC/MS-Based Methods

International audienceBy now the polymeric nature of microparticles has to be demonstrated before their classification as microplastics. Pyrolysis coupled to gas chromatography and mass spectrometry (Py-GC/MS) has been used for years to characterize polymers. Thanks to three distinct steps, destructuring, separation, and identification, this chapter explains how this technique allows the analyst to ascertain the polymeric composition of different plastic materials and much more. Far from being used as much as vibrational spectroscopy methods for the study of microplastics, Py-GC/MS nevertheless has advantages which will be presented in this chapter, through the presentation of the contributions of this technique in terms of identification and quantification of microplastics. All of the studies presented here allow to outline some good laboratory practices relative to this technique. The last part of this chapter is dedicated to the future of microplastics analysis by Py-GC/MS, including the need of method normalization and the contribution of this technology for the research of nanoplastics and additives

Analytical Methods for Microplastics in Environments: Current Advances and Challenges

Numerous studies have shown the presence of microplastics (MPs) in the environment. As an emerging global contaminant, the concentrations of MPs need to be evaluated, to assess its impacts on ecosystems and humans. This chapter reviews the development of analytical approaches from sample collection to MP characterization and quantification. This chapter contains a critical overview and a comparative assessment of sampling and sample preparation procedures for water, soil,sediment, biological, and atmosphere samples. We discuss sample preparation techniques such as flotation, filtration, digestion of organic matter, and analytical techniques such as morphological and physical classification, identification, and quantification of MPs. Furthermore, we address the advantages and disadvantages of these techniques, compare MP assay methods for different environment matrices, and discuss the challenges in the establishment of standard methods. In future research, it will be important to develop efficient assay protocol, such as basing on fully or semiautomated analysis, and to improve the accuracy of identification and quantification for MPs, especially nanoplastics