Characterization and Analysis of Microplastics 978-0-444-63898-4

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Comprehensive Analytical Chemistry Volume 75

Characterization and Analysis of Microplastics

Advisory Board Joseph A. Caruso University of Cincinnati, Cincinnati, OH, USA Hendrik Emons Joint Research Centre, Geel, Belgium Gary Hieftje Indiana University, Bloomington, IN, USA Kiyokatsu Jinno Toyohashi University of Technology, Toyohashi, Japan Uwe Karst University of Mu¨nster, Mu¨nster, Germany Gyro¨gy Marko-Varga AstraZeneca, Lund, Sweden Janusz Pawliszyn University of Waterloo, Waterloo, Ont., Canada Susan Richardson US Environmental Protection Agency, Athens, GA, USA

Comprehensive Analytical Chemistry Volume 75

Characterization and Analysis of Microplastics Edited by

Teresa A.P. Rocha-Santos University of Aveiro, CESAM, Aveiro, Portugal

Armando C. Duarte University of Aveiro, CESAM, Aveiro, Portugal

Elsevier Radarweg 29, PO Box 211, 1000 AE Amsterdam, Netherlands The Boulevard, Langford Lane, Kidlington, Oxford OX5 1GB, United Kingdom 50 Hampshire Street, 5th Floor, Cambridge, MA 02139, United States Copyright © 2017 Elsevier B.V. All rights reserved. No part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying, recording, or any information storage and retrieval system, without permission in writing from the publisher. Details on how to seek permission, further information about the Publisher’s permissions policies and our arrangements with organizations such as the Copyright Clearance Center and the Copyright Licensing Agency, can be found at our website: www.elsevier.com/permissions. This book and the individual contributions contained in it are protected under copyright by the Publisher (other than as may be noted herein). Notices Knowledge and best practice in this field are constantly changing. As new research and experience broaden our understanding, changes in research methods, professional practices, or medical treatment may become necessary. Practitioners and researchers must always rely on their own experience and knowledge in evaluating and using any information, methods, compounds, or experiments described herein. In using such information or methods they should be mindful of their own safety and the safety of others, including parties for whom they have a professional responsibility. To the fullest extent of the law, neither the Publisher nor the authors, contributors, or editors, assume any liability for any injury and/or damage to persons or property as a matter of products liability, negligence or otherwise, or from any use or operation of any methods, products, instructions, or ideas contained in the material herein. ISBN: 978-0-444-63898-4 ISSN: 0166-526X For information on all Elsevier publications visit our website at https://www.elsevier.com

Publisher: Zoe Kruze Acquisition Editor: Poppy Garraway Editorial Project Manager: Shellie Bryant Production Project Manager: Vignesh Tamil Designer: Miles Hitchen Typeset by TNQ Books and Journals

Contents Contributors to Volume 75 Series Editor’s Preface Preface

1.

Microplastics e Occurrence, Fate and Behaviour in the Environment

xi xiii xv

1

Joa˜o Pinto da Costa, Armando C. Duarte, Teresa A.P. Rocha-Santos

2.

1. Introduction 1.1 Sources of Microplastics in the Environment 1.2 Primary Microplastics 1.3 Secondary Microplastics 2. Fate of Microplastics in the Environment 2.1 Spatial and Temporal Distribution 2.2 Degradation 2.3 The ‘Missing Link’ in Plastic Mass Balance 3. Behaviour and Effects of Microplastics 3.1 Physical Effects 3.2 Chemical Effects 4. Methodologies Used for the Identification and Characterization of Microplastics 5. Key Challenges and Road Map for Further Research Acknowledgements References

1 4 5 5 6 6 8 11 12 12 13

Microplastics Sampling and Sample Handling

25

16 19 20 20

Monica F. Costa, Armando C. Duarte 1. Introduction 2. Sampling 3. Samples Handling 3.1 Contamination 4. Water Sampling Using Plankton Tow Nets 4.1 Pelagic Plastics Sampled by Other Techniques 5. Ice and Snow 6. Food Resources 6.1 Sampling From Stomach Contents

25 27 29 31 32 34 34 35 36 v

vi Contents 7. Microbiota of the ‘Plastisphere’ 8. Sampling Microplastics From Beaches 8.1 Image Analysis as a Sampling Method for Microplastics on Beaches 9. Sediment Traps for Microplastic Sampling From the Water Column 10. Deep-Sea Sediments 11. Conclusion Acknowledgements References

3.

Morphological and Physical Characterization of Microplastics

37 37 40 40 41 42 43 43

49

Andre´s Rodrı´guez-Seijo, Ruth Pereira

4.

1. Introduction 2. Size and Shape 3. Colour 4. Density 5. Concluding Remarks References

49 51 56 58 62 62

Characterization and Quantification of Microplastics by Infrared Spectroscopy

67

Gerrit Renner, Torsten C. Schmidt, Ju¨rgen Schram

5.

1. Introduction to Infrared Spectroscopy of Microplastics 1.1 Molecular Vibrations 1.2 Excitation Processes in Infrared Spectroscopy 1.3 The Infrared Spectrum 2. Mid-Infrared 2.1 Instrumentation 2.2 Techniques and Accessories 2.3 Characterization and Quantification of Microplastics 3. Near-Infrared 3.1 Instrumentation 3.2 Identification of Polymers 4. Applications of FT-MIR Spectroscopy References

68 68 69 75 78 79 81 95 108 108 110 111 115

Characterization of Microplastics by Raman Spectroscopy

119

Paulo Ribeiro-Claro, Mariela M. Nolasco, Catarina Arau´jo 1. Introduction 2. Raman Spectroscopy Basics

119 120

Contents vii

6.

2.1 Principles of Raman Spectroscopy 2.2 Spectrometers in a Nutshell 2.3 Coherent Anti-Stokes Raman Scattering 3. Advantages and Limitations of Raman Spectroscopy 4. State-of-the-Art 5. Final Remarks and Future Outlook Acknowledgements References

120 124 127 129 134 147 148 149

Application of Scanning Electron MicroscopyeEnergy Dispersive X-Ray Spectroscopy (SEM-EDS)

153

Ana Violeta Gira˜o, Gianvito Caputo, Marta C. Ferro

7.

1. Introduction 1.1 Scanning Electron Microscopy 1.2 Energy Dispersive X-Ray Spectroscopy 2. Sample Preparation 3. Equipment Operation 4. Microplastics Characterization 5. Final Considerations References

154 155 158 158 161 164 166 166

Application of Pyrolysis-Gas Chromatography/Mass Spectrometry (Py-GC/MS)

169

Peter Kusch 1. Introduction 2. Pyrolysis-Gas Chromatography/Mass Spectrometry to the Analysis of Microplastics 2.1 Instrumentation and Method 2.2 Characterization of Polyethylene, Polypropylene, Poly(ethylene-co-propylene) and Poly (ethylene-co-vinyl acetate) 2.3 Characterization of Polystyrene and Poly (acrylonitrile-co-1,3-butadiene-co-styrene) 2.4 Characterization of Rubbers e Poly(styrene-co-1, 3-butadiene) and Poly(acrylonitrile-co-1,3-butadiene) 2.5 Characterization of Polyamides 2.6 Characterization of Phenolic Resin 2.7 Characterization of Polyurethanes 2.8 Characterization of Poly(ethylene terephthalate) 2.9 Characterization of Poly(vinyl chloride) 2.10 Characterization of Silicone Rubber 3. Conclusion Acknowledgements References

170 172 172

174 182 187 190 192 193 194 197 200 206 206 206

viii Contents

8.

Advanced Analytical Techniques for Assessing the Chemical Compounds Related to Microplastics

209

Lorena M. Rios Mendoza, Satie Taniguchi, Hrissi K. Karapanagioti

9.

210 210 211 211 212 212 213

1. Introduction 2. Plastic Additives 2.1 Phthalates 2.2 Perfluoroalkyl Substances 2.3 Nonylphenol 2.4 Bisphenol A 2.5 Brominated Flame Retardants 3. Environmental Organic Contaminants Sorbed to Microplastics 3.1 Polychlorinated Biphenyls 3.2 Organochlorine Pesticides 3.3 Polycyclic Aromatic Hydrocarbons 4. Extraction of Organic Compounds From Microplastics 4.1 Soaking/Maceration 4.2 Ultrasound 4.3 Soxhlet 4.4 Accelerated Solvent Extraction 4.5 Comparison of the Different Extraction Methods 5. CleanUp e Purification and Separation of the Compounds 5.1 Adsorption Chromatography 5.2 Chemical Treatments 6. Identification and Quantitation Techniques 6.1 Chromatography 7. Conclusion References

215 218 218 220 220 221 223 224 226 226 226 227 229 229 229 233 234

The Role of Laboratory Experiments in the Validation of Field Data

241

Catherine Mouneyrac, Fabienne Lagarde, Ame´lie Chaˆtel, Farhan R. Khan, Kristian Syberg, Annemette Palmqvist 1. Introduction 2. Microplastics Used in Laboratory Experiments 2.1 Representativeness of Microplactic Used in Laboratory Experiments for Microplastics Found in the Environment 2.2 Validating the Microplastic ‘Vector Effect’ 3. Typical Experimental Designs for Testing Effects of Microplastics 3.1 Waterborne Exposure 3.2 Sediment Exposure 3.3 Dietary Exposure, Trophic Transfer

242 243 243 248 255 255 256 256

Contents

3.4 Outdoor Mesocosms 3.5 Ingestion/Egestion of Microplastics 4. Toxicological Impacts of Microplastic Exposures 4.1 Effects at the Subindividual Level 4.2 Effects at the Individual Level 4.3 Effects at Higher Levels of Biological Organization 5. Conclusion and Future Research Needs References Index

ix 257 257 259 259 260 263 264 265 275

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Contributors to Volume 75 Catarina Arau´jo, CICECO, University of Aveiro, Aveiro, Portugal Gianvito Caputo, Istituto Italiano Di Tecnologia, Genova, Italy Ame´lie Chaˆtel, Universite´ Catholique de l’Ouest, Angers, France Monica F. Costa, Universidade Federal de Pernambuco, Recife, Brazil Joa˜o Pinto da Costa, University of Aveiro, CESAM, Aveiro, Portugal Armando C. Duarte, University of Aveiro, CESAM, Aveiro, Portugal Marta C. Ferro, CICECO and Department of Materials and Ceramic Engineering, University of Aveiro, Campus de Santiago, Aveiro, Portugal Ana Violeta Gira˜o, CICECO and Department of Materials and Ceramic Engineering, University of Aveiro, Campus de Santiago, Aveiro, Portugal Hrissi K. Karapanagioti, University of Patras, Patras, Greece Farhan R. Khan, Roskilde University, Roskilde, Denmark Peter Kusch, Bonn-Rhein-Sieg University of Applied Sciences, Rheinbach, Germany Fabienne Lagarde, Universite´ du Maine, Le Mans, France Catherine Mouneyrac, Universite´ Catholique de l’Ouest, Angers, France Mariela M. Nolasco, CICECO, University of Aveiro, Aveiro, Portugal Annemette Palmqvist, Roskilde University, Roskilde, Denmark Ruth Pereira, Interdisciplinary Centre of Marine and Environmental Research (CIIMAR/CIMAR), Porto, Portugal; Faculty of Sciences of the University of Porto, Porto, Portugal; GreenUP/CITAB-UP, Porto, Portugal Gerrit Renner, Niederrhein University of Applied Sciences, Krefeld, Germany; University of Duisburg-Essen, Essen, Germany Paulo Ribeiro-Claro, CICECO, University of Aveiro, Aveiro, Portugal Lorena M. Rios Mendoza, University of Wisconsin-Superior, Superior, WI, United States Teresa A.P. Rocha-Santos, University of Aveiro, CESAM, Aveiro, Portugal

xi

xii Contributors to Volume 75 Andre´s Rodrı´guez-Seijo, Universidade de Vigo, Vigo, Spain Torsten C. Schmidt, University of Duisburg-Essen, Essen, Germany Ju¨rgen Schram, Niederrhein University of Applied Sciences, Krefeld, Germany Kristian Syberg, Roskilde University, Roskilde, Denmark Satie Taniguchi, University of Sa˜o Paulo, Sa˜o Paulo, Brazil

Series Editor’s Preface I am delighted to introduce this new CAC title edited by Teresa A.P. RochaSantos and Armando C. Duarte on Characterization and Analysis of Microplastics. This book is an excellent addition to the CAC series, and it is our first book in this series on the challenging and well-known environmental problem of microplastics. Plastic pollution has been given considerable attention since the end of 1980s, almost 30 years ago. Because of its nature, plastic can be easily dispersed by wind being transported and fragmented to long distances. Most of us are aware that plastic debris is one of the most ubiquitous problems of our planet. But it was only 5e6 years ago that the issue of micro- and nanoplastics was on the research agenda. Microplastic residues are affecting the aquatic organisms at different trophic levels being a risk for the aquatic life. The volume that you have now in your hands covers the main pillars of microplastic characterization and analysis in nine chapters. First, an introductory chapter on occurrence, fate and behaviour in the environment describes an overview of today’s problem. Next chapters are more specific on sample preparation, morphological and physical characterization, and analysis by different spectroscopic, microscopic and gas chromatography/mass spectrometric techniques. The final chapter reports the role of controlled laboratory experiments that are always needed to validate field data in environmental studies. This book offers a comprehensive view of the characterization and analytical methodologies for microplastics. It is a useful tool for newcomers and practitioners who want to be introduced in this new research field. Senior marine chemists and biologists, environmental chemists, ecologists and hydrologists studying freshwater systems will enjoy reading it too. Recent literature indicates wastewater treatment plants as source of microplastics in the aquatic environment. This book will certainly contribute to a better understanding of microplastic pollution problems at global scale. In this respect, microplastic pollution brings the issue to the public’s attention, as the impacts on aquatic life can create media interest and pressure for government response. Certainly in this particular case, pollution prevention measures are needed and the extremely high usage of plastic bags in our daily life should be avoided as soon as possible.

xiii

xiv Series Editor’s Preface

Finally I would like to thank specially Teresa and Armando for the amount of work, time and expertise devoted as editors of this book. I would like to acknowledge as well to the various well-known authors for their contributions in compiling such a world-class and timely book for the CAC series. D. Barcelo´, IDAEA-CSIC, Barcelona and ICRA, Girona, December 9, 2016, Editor in Chief of the Comprehensive Analytical Chemistry Series.

Preface Microplastics are plastic particles with less than 5 mm in size and physicochemical properties (e.g., overall size, density, colour, and chemical composition) that are key contributors to the enhancement of their bioavailability to organisms. Mainly due to their small size, microplastics have the potential of being ingested by benthic and planktonic organisms, thus entering marine food webs with a very low potential of biodegradation. Therefore, a detailed qualitative and quantitative monitoring of microplastics in the marine environment is highly required, and in fact it is already recommended within the framework of the Marine Strategy Framework Directive (MSFD). Due to the methodology currently used, the scarce data on microplastics concentrations are mostly biased towards larger particles. Furthermore, differences observed in different studies in terms of concentration and composition by predominant types of microplastics could also be due to significant methodological differences. Comparison of the quantitative results obtained by published works would be very interesting and of utmost importance, but still is a very hard or even impossible task to perform. Therefore, reliable data on concentrations of microplastics in marine systems and other environmental compartments are still lacking, which makes this book a very timely and useful instrument for dealing with such a hot topic. This comprehensive overview and discussion aims mainly at fulfilling the gap on the knowledge about the analytical techniques and analytical methodologies for microplastics identification and quantification based on published works. This overview includes the assessment of sampling techniques and sample handling, morphological, physical and chemical characterization of microplastics, and the role of laboratory experiments in the validation of field data. Chapter 1 produces the state of the art on the occurrence, fate and behaviour of microplastics in the environment, and it highlights the need for analytical methodologies fit for purpose. Chapter 2 introduces and discusses different sampling strategies to be taken into account for ensuring the appropriate collection of microplastics from several environmental compartments. In Chapter 3 the methodologies used for characterization of the morphological characteristics of microplastics, such as shape and/or the colour, and the physical characteristics of microplastics, such as size, are discussed and put into perspective. Chapters 4 and 5 provide an overview and discuss the analytical methodologies associated with infrared spectroscopy and Raman spectroscopy for characterization of microplastics.

xv

xvi Preface

Chapter 6 shows the application of scanning electron microscopyeenergydispersive X-ray spectroscopy on the identification and characterization of microplastics and also on the characterization of inorganic additives in microplastics fragments. Chapter 7 introduces the use of pyrolysis gas chromatography/mass spectrometry for analysis and identification of degradation products of commercially available synthetic polymers/copolymers and their additives, and subsequent application on microplastics characterization. Chapter 8 is focused on the use of advanced analytical techniques such as gas chromatography high-resolution mass spectrometry and liquid chromatography tandem mass spectrometry for assessing the contaminants related to microplastics. Finally, Chapter 9 discusses the role of laboratory experiments in the validation of field data. The volume editors would like to thank the Comprehensive Analytical Chemistry (CAC) series editor, Prof. Damia´ Barcelo´, for giving us the opportunity of coordinating such an interesting thematic work on ‘Characterization and Analysis of Microplastics’. All the help and advice from Poppy Garraway, the associate acquisitions editor, and Shellie Bryant, the editorial project manager, are also gratefully acknowledged. Thanks are also due to the authors who helped us to assemble a close set of chapters into a book targeting a broad spectrum of readers ranging from the researchers in the field to the undergraduate and graduate students interested in an overview and a primary source of information for pursuing further studies. Teresa A.P. Rocha-Santos Armando C. Duarte

Chapter 1

Microplastics e Occurrence, Fate and Behaviour in the Environment Joa˜o Pinto da Costa,* Armando C. Duarte and Teresa A.P. Rocha-Santos University of Aveiro, CESAM, Aveiro, Portugal *Corresponding author: E-mails: [email protected] and [email protected]

Chapter Outline 1. Introduction 1 1.1 Sources of Microplastics in the Environment 4 1.2 Primary Microplastics 5 1.3 Secondary Microplastics 5 2. Fate of Microplastics in the Environment 6 2.1 Spatial and Temporal Distribution 6 2.2 Degradation 8 2.2.1 Abiotic Degradation 9 2.2.2 Biodegradation 10 2.3 The ‘Missing Link’ in Plastic Mass Balance 11

3. Behaviour and Effects of Microplastics 3.1 Physical Effects 3.2 Chemical Effects 4. Methodologies Used for the Identification and Characterization of Microplastics 5. Key Challenges and Road Map for Further Research Acknowledgements References

12 12 13

16

19 20 20

1. INTRODUCTION Plastics are materials made of a wide number of semisynthetic or synthetic organic compounds that can be moulded into shape while soft, and then set into a form very rigid or slightly elastic. The International Union of Pure and Applied Chemistry (IUPAC) defines plastics as a generic term used in the case of ‘polymeric material that may contain other substances to improve performance and/or reduce costs’ [1]. Comprehensive Analytical Chemistry, Vol. 75. http://dx.doi.org/10.1016/bs.coac.2016.10.004 Copyright © 2017 Elsevier B.V. All rights reserved.

1

2 Characterization and Analysis of Microplastics

The main feature of these materials is reflected in their etymology: the word plastic originates from the Greek words plastikos (plassiko´2), meaning ‘capable of being shaped’, and plastos (plasso´2), meaning ‘molded’ [2]. Other features include ease of manufacture, low cost, imperviousness to water and chemical, temperature, and light resistance [3]. These characteristics have led plastics to replace and displace many materials, including wood, paper, stone, leather, metal, glass and ceramic and, currently, plastics are present in a huge and expanding range of products, from paper clips to spaceships [4]. This success has manifested itself under many forms, including thermoplastics, natural and modified polymers, and, more recently, due to increasing environmental concerns, biodegradable plastics [5]. The most commonly used types of plastic, including their specific gravity and applications, are highlighted in Table 1. Hence, considering this versatility, it is not surprising that the last detailed report on the annual global production of plastics, for 2015, showed it to exceed 310 million tonnes [6]. While the benefits of plastics are undeniable, this widespread use of plastics, namely in discardable form, such as packaging materials, ultimately leads to their accumulation in the environment and it is estimated that plastic waste constitutes approximately 10% of the total municipal waste worldwide [7]. Although a fraction of this plastic waste is recycled, most of it ends up in landfills, where they may take a few hundred years to decompose [9]. However, of special concern are plastics that enter the marine environment, which have been calculated to be ca. 10% of the total plastics produced [10]. These larger plastic debris, known as ‘macroplastics’, have long been the focus of environmental research, including in specific areas of the ocean, where they tend to accumulate, due to the convergence of surface currents, they tend to accumulate [11], as is the case of the Great Pacific Garbage Patch, illustrated in Fig. 1. This floating debris is continuously mixed by the concerted actions of wind and waves and becomes widely dispersed over huge surface areas and across the top portion of the water column [13]. Besides the obvious aesthetic consequences, which may have economic repercussions in tourism, the environmental impacts of these particles include entanglement, ingestion, smothering, hangers-on, hitch-hiking and alien invasion, as these floating debris can constitute new routes for invasive species [3]. Interestingly, it has also been reported that the species found associated with these plastic debris, known as the Plastisphere, can sometimes differ greatly from the free-floating microbial communities commonly found in the oceans [14]. Nonetheless, there are other perhaps less frequently recognized environmental risks caused by plastic debris, including risks to shipping, fisheries and other maritime activities, such as energy production and aquaculture [15]. These are hardly the sole dangers posed by plastic litter at sea and, in spite of the limited studies detailing its socioeconomic impacts, the main sectors affected have been identified, as depicted in Fig. 2. These consequences are not confined to

TABLE 1 Types of Plastic Commonly Used, Main Applications and Specific Gravity [8] Application

Specific Gravity

Low-density polyethylene (LDPE)

Packaging, general purpose containers, shower curtains, floor tiles.

0.91e0.93

Polyethylene (PE)

Supermarket bags, plastic bottles

0.91e0.96

High-density polyethylene (HDPE)

Milk containers, detergent bottles, tubing

0.94

Polystyrene (PS)

Packaging foam, disposable cups, food containers, CDs, building materials

1.05

High impact polystyrene (HIPS)

Electronics, cups in vending machines, refrigerator liners

1.08

Polyvinyl chloride (PVC)

Pipes, window frames, flooring, shower curtains

1.38

Polypropylene (PP)

Packaging, bottle caps, ropes, carpets, laboratory equipment, drinking straws

0.83e0.85

Polyamides (PA) (nylons)

Textiles, toothbrush bristles, fishing lines, automotive

1.13e1.35

Acrylonitrile butadiene styrene (ABS)

Musical instruments, printers, computer monitors, drainage pipes, protective equipment

1.06e1.08

Polycarbonate (PC)

CDs, DVDs, construction materials, electronics, lenses

1.20e1.22

Polyester (PES)

Textiles

1.40

Polyethylene terephthalate (PET)

Soft drink bottles, food packaging, thermal insulation, blister packs

1.38

Microplastics Chapter j 1

Type

3

4 Characterization and Analysis of Microplastics

FIGURE 1 The Great Pacific Garbage Patch, also commonly referred to as the Pacific trash vortex, is a gyre of marine debris particles, mostly plastic, in the central North Pacific Ocean. Discovered around 1985, it is located roughly between 135 W to 155 W and 35 N to 42 N [12] a. Image credits: NOAA, Great Pacific Garbage Patch. Marine Debris Program, August 19, 2016. Available from: https://marinedebris.noaa.gov/movement/great-pacific-garbage-patch.

national boundaries, and the multiscalar and temporal mechanisms involved in the fate and behaviour of plastics in the environment highlight the relevance of this problem.

1.1 Sources of Microplastics in the Environment Microplastics, plastic particles associated with the millimetre size range, have become of increasing concern due to their threat to environmental quality preservation and related issues. These plastic particles are minute fragments, usually with a size ν11] + [ν21 -> ν20]

ν1

ν2

energy

ν1

= ν0

+

=

+ ν0

FIGURE 4 Simulated Infrared spectrum of 11 vibrational transitions of two different vibrational modes and the related extraction from Jablonski diagram. The entire set of these transitions defines the corresponding sample and can be used as a high characteristic fingerprint, which is a common method for microplastic analysis. Normal transitions v0 / v1 are most probable, while difference and hot transitions are most improbable, which influences signal intensities.

74 Characterization and Analysis of Microplastics

normal transition

Characterization and Quantification of Microplastics Chapter j 4

75

The symmetric stretching vibration of carbon dioxide will not be followed by a change of the bonding dipole moment ðvm =vr ¼ 0Þ; which means that this transition is IR-inactive and will not occur within an Infrared spectrum. The Ce vibrations of polymers have very low values of vm =vr z0 and are almost absent in Infrared spectroscopy, although a polymer consists largely of a CeC backbone. In contrast to this, the bonding dipole moment of C]O within a polyamide will be changed very well during its stretching vibration, which leads to very strong IR intensities.

1.3 The Infrared Spectrum 1.3.1 Units of an Infrared Spectrum The illustration of an Infrared spectrum can vary in some cases and it is important for comparability of different spectra to use same units. Within this chapter, all shown spectra are illustrated using wavenumber v~ (cm 1) as a value of energy of the Infrared radiation and absorbance A as a value of Intensity of the measurement signal. The latter can be deduced by BeereLamberteBouguer law (Eq. 8). A ¼ ε$c$l

(8)

Here, ε is defined as the molar attenuation coefficient, which depends on the second term of Eq. (7). The measured absorbance A is proportional to the concentration c of the sample with a layer thickness l. As an alternative, wavelength l (mm) and transmittance T (%) could be used. These units can be converted into each other as it is shown below (Eq. 9). 1 l A ¼2 v~ ¼

(9) log10 T

1.3.2 Ranges of an Infrared Spectrum The Infrared spectrum can be divided into two parts. Mid-Infrared ranges from 400 to 4000 cm 1, while near-Infrared ranges from 4000 to 12,500 cm 1. These two parts are separated physically by using two different measurement systems (NIR and MIR spectrometers). Within the MIR spectrum, transitions of stretching vibrations of single bonded heteroatom groups will occur between 2800 and 3500 cm 1. Stretching vibrations of double bonded groups and all types of deformation vibrational modes appear between 400 and 1800 cm 1. The latter MIR range is often very complex, which means that transitions need similar energy values and signals often overlap each other. Accordingly, it would be difficult to assign all signals to their corresponding transitions. However, the complete set of

76 Characterization and Analysis of Microplastics

MIR signals within this range provides a highly characteristic fingerprint for each kind of polymer. Comparing this fingerprint to reference spectra will be a good way to distinguish and identify polymers, as illustrated in Fig. 34. As an example, MIR spectra of polyethylene and polypropylene are shown in Fig. 5. The NIR spectrum (4000e12,500 cm 1) contains all the mentioned overtones and combination bands. The corresponding spectra consist of overlapping signals, which result in very broad vibrational bands. In most cases, it is impossible to assign the origin of an overtone or a combination transition due to the high number of possible linear combinations of normal modes. Regarding this, not the vibrational band itself but the shape of the vibrational band ensemble is a characteristic indicator for each polymer sample. This leads to multivariate spectra evaluation as the method of choice. Analogously to the MIR spectrum (Fig. 5), NIR data of polyethylene and polypropylene are illustrated in Fig. 6.

1.3.3 Critical Values of an Infrared Spectrum The quality of the results of quantification as well as qualification of microplastic samples depends significantly on the quality of the measured spectrum. Regarding this, the detected absorbance A should be lower than a value of 2 [20,21]. Higher absorbance values could lead to overflowed spectra and bad results of analysis, as illustrated in Fig. 7. For quantification, absorbances A < 1 are recommended to ensure linearity, which is required for BeereLamberteBouguer law (Eq. 8).

absorbance

polyethylene

3500

3000

wavenumber [cm-1]

1500

1000

polypropylene

FIGURE 5 FT-MIR spectra of polyethylene and polypropylene. Both have characteristic vibrational bands at 3000 cm 1 and an individual fingerprint between 1500 and 650 cm 1. That is caused by the differences in chemical structure.

Characterization and Quantification of Microplastics Chapter j 4

77

polyamide absorbance

polypropylene

polyethylene

9000

8500

wavenumber [cm-1]

7500

7000

6500

FIGURE 6 FT-NIR spectra of polyethylene, polypropylene and polyamide. All have characteristic shapes of the shown broad vibrational bands, but in contrast to FT-MIR spectra, they cannot be distinguish by individual vibrational bands.

1.3.4 Spectral Resolution In concordance with a finite sampling rate or finite surface of a detector, the number of measured data points within one spectral scan will also be limited. v, which can be detected separately is The smallest difference of energy D~ defined as the spectral resolution R. Two separate signals could be differentiated, if at least one point in between differs significantly. This results in Eq. (10). v R ¼ 2$D~

(10)

Microplastics often differ from pure reference materials and in these cases, library searching is not suitable and has to be combined with manual spectra interpretation [22,23]. In this context, the possibility to interpret spectra of different degraded polymers depends on spectral resolution.

absorbance

4

2

3500

3000

wavenumber [cm-1]

1500

1000

FIGURE 7 FT-MIR spectrum of polyamide 6. The sample was measured in transmittance mode, but its layer thickness is not thin enough resulting in overloading effects. This is a common problem of polyamide analysis by Infrared spectroscopy with transmittance experiments as these are very sensitive to compounds containing oxygen. Measuring with ATR technique or reducing layer thickness are effective solutions to this problem.

78 Characterization and Analysis of Microplastics

On the one hand, it is possible to describe exactly and identify hidden or overlapped transitions by measuring with a high spectral resolution, which is a good way to differentiate between polymer signals and matrix or degradation interferences. On the other hand, a lower spectral resolution is much better in the case of multivariate evaluation, especially using NIR data due to higher information density. However, using an interferometer at a higher spectral resolution, e.g. R ¼ 2 cm 1 instead of R ¼ 4 cm 1, causes an increasing of measurement time t for each scan, which rises proportionally to the reciprocal of R. Rf

1 t

(11)

Using a constant total scanning time, fewer scans could be performed. However, the signal-to-noise ratio S/N increases proportional to the square root of the number of scans n. pffiffiffi (12) S=Nf n

Reversely, a higher spectral resolution R lowers the signal-to-noise ratio S/N. RfS=N

(13)

Therefore, it is necessary to increase number of scans n, if characterization of microplastics requires a high spectral resolution, which depends on the analytical issue. Analogously to the units of an Infrared spectrum, it is also important to measure with same spectral resolutions to ensure a good comparability.

2. MID-INFRARED In the field of microplastic characterization by Infrared spectroscopy, analysis with mid-Infrared systems is most common. As preliminarily remarked, this technique offers information about chemical structures. Next to the polymer itself, which is defined by a high characteristic MIR spectrum from 400 to 4000 cm 1, typical contaminants like proteins can be identified simultaneously. Moreover, it is possible to characterize ageing extent due to a change of chemical structure caused by this process. In general, MIR techniques hardly require any sample preparation [24e26], and, according to a high range of accessories and diverse methods, microplastics of all kinds can be analysed. Another advantage is the high practicability due to short measurement times and the opportunity of empirical as well as theoretical data evaluation. However, in contrast to Raman spectroscopy, MIR techniques are very sensitive for water causing a limitation to dry samples [20,21,27].

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2.1 Instrumentation The instrumentation design within the MIR spectroscopy can be divided at least into three key types. Conventional stationary FT-MIR spectrometer are most common and can be combined with many accessories. This kind of spectrometer is suitable for microplastic analysis down to a scale of 1 mm per particle, powders or thin films, and identification of polymers is a common analytical task. In general, these instrument types allow short measurement times and do not require complex sample handling. The analysis of smaller microplastics is currently performed with FT-MIR microscopy. This technique requires highly precision sample handling, resulting in a longer analysis time in comparison to classical FT-MIR spectrometers [24]. However, using a microscope allows analysis of microplastics down to a diameter of a few micrometres. The spatial resolution reaches 10  10 mm. This can be very interesting for the characterization of ageing processes, which caused a change of surface constitution. In addition to this, it is possible to combine multiple measurements at different spots to create a chemical map. The third technique is a handheld FT-MIR. For microplastic analysis, this technology is not very common at present but it could be a very powerful tool if some problems like interference of water and low sensitivity could be solved in the future.

2.1.1 Basic Working Scheme of an Infrared Spectrometer A modern Infrared spectrometer consists of four principal components: Infrared light source, interferometer, sample compartment and detector. Polychromatic Infrared light is emitted by the excitation source. This light beam is cosine-modulated due to the static and moving mirror within the interferometer. The modulated light beam is guided to the sample and is partially absorbed due to excitation of vibrational processes. The residual Infrared radiation is detected as a function of phase shift, a result of the cosine modulation of the Infrared light. The detected signal is recorded as an interferogram and transformed into the Infrared spectrum by Fourier transformation. These basic steps can be found in most MIR spectrometers, and are illustrated in Fig. 8. 2.1.2 Interferometer In current MIR spectrometers, interferometers have been integrated to analyse absorbance of Infrared light simultaneously instead of scanning through all wavenumbers one after the other. The advantages of this technology are a higher signal-to-noise ratio and a better wavenumber accuracy, which are prerequisites for good practice in microplastic characterization. Regarding this, it is possible to compensate light scattering at coarse microplastic

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IR source

static mirror

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interferometer sample beam splitter detector

cosine modulation moving mirror static mirror

FIGURE 8 Principle of an FT-MIR spectrometer. The light source emits polychromatic IR radiation that is cosine modulated within the interferometer, which consists of a beam splitter, a static and a moving mirror. Subsequently, the IR beam passes through the microplastic sample and is partly absorbed as a result of excitation processes and is guided to the IR detector.

surfaces, and besides, broad-banded water interferences, caused by residual moisture. The main idea of each interferometer is splitting the incoming polychromatic Infrared beam into two parts. The phase of one part will be kept static, whereas the phase of the other part will be shifted continuously by changing the path length. After recombination of both split-light beams, they show an interference due to the phase shift, which can be constructive or destructive depending on the corresponding phase shift: l=2 or l=4; respectively. In this context, a recombined wave can be written as Eq. (14): jnet ¼ j1 þ j2 ¼ a$sinðu$tÞ þ a$sinðu$t þ qÞ     q q ¼ 2a$cos $sin u$t þ 2 2 |fflfflfflfflfflfflfflffl{zfflfflfflfflfflfflfflffl}

(14)

cosine modulated amplitude

According to this, the resulting wave jnet is equal to the sum of the static wave j1 and the phase-shifted wave j2 : Using trigonometric identity the cosine modulation of the amplitude can be observed, whereas the frequency u will not change during this process. In addition, the phase shift q is not static but continuously changing and can be described as a function of time t. This leads to continuously varying amplitudes and phases of the interfering waves. Within an interferometer, the phase shift is realized by a beam splitter, a static and moving mirror, as shown in Fig. 9. The moving mirror oscillates between maximum and minimum displacements. In relation to the light beam, which is reflected at the static mirror, path length of the other light beam

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be am

incoming light beam

sp lit te r

from IR source

to sample outcoming light beam moving mirror static mirror

FIGURE 9 Detailed scheme of a Michelson interferometer. The incoming IR beam is divided into two parts when passing through the beam splitter. One part is reflected by a static mirror while the other part is guided to a moving mirror. This results in time-dependent relative path length differences of both IR beam paths leading to a cosine-modulated interference phenomenon of the recombined outcoming IR beam.

changes in dependency of relative mirror position d. In the case of polychromatic Infrared light and with regard to Eq. (14), wavelength-dependent intensity function of the outcoming IR beam is given by Eq. (15).     X qðdðt; vÞ; uÞ qðdðt; vÞ; uÞ jnet ¼ $sin ui $dðt; vÞ þ (15) 2ai $cos 2 2 i

At this point, it is notable that the mirror velocity v is an important parameter for microplastic characterization. The slower the mirror moves, the more time is needed to perform a single scan, which results in higher signal intensities due to longer integration time of the detector. According to the analytical issue, it is recommended to adjust this parameter to analyse main or trace components. Thereby, one has to ensure that relevant absorbance bands do not exceed the limit value (Amax ¼ 2). Especially in the case of contaminant analysis, mirror velocity should be reduced. Detecting the intensity of this modulated light at certain points in time, while the mirror is moving, results in a complex interferogram. If one or a set of frequencies are absorbed, the complex interference pattern changes depending on the absorbed wavelengths, which is illustrated in Fig. 10. The detected light intensity bases on a path length difference domain and can be converted into light intensity of a frequency domain by Fourier transform. This results in a wavenumber-dispersive Infrared spectrum, as can be seen in Fig. 10. This Infrared spectrum forms the basis for characterization of microplastics due to the fact that various polymers have specific sets of vibrational transitions.

2.2 Techniques and Accessories For analysis of microplastics using FT-MIR spectroscopy, every accessory has advantages and disadvantages and the best choice depends on analytical issue

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FIGURE 10 Fourier transform of an Infrared interferogram of polyethylene to its Infrared spectrum including background correction. First, the path length difference resolved interferograms of background and polyethylene þ background are transformed into wavenumber-resolved IR spectra. Subsequently, background correction is performed by spectra division. The entire process is done automatically by common IR instrument software.

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and sample properties, respectively, as presented in Table 1. Accordingly, the following section describes a selection of common MIR techniques.

2.2.1 Transmittance of Thin Polymer Films The transmittance mode is a very simple way to analyse thin polymer films. The interfering IR beam passes through the sample, which is placed in a special magnetic film holder. Such holders are commercially available with standardized sizes down to a diameter of 13 mm. For this reason, it is not suitable to analyse microplastics, but it can be used to measure reference materials to build up a reference spectra library for polymers. The fundamental functionality is illustrated in Fig. 11. During measurement the IR beam passes completely through the sample cross-section, which maximizes the sensitivity. Accordingly, even transitions with low extinction coefficients can be observed. In the case of polypropylene or polyethylene, this is an advantage due to enhancement of very low absorption rates of CeC and CeH vibrational mode transitions. The S/N rises and vibrational bands can be evaluated in a much better way. If the changes in the bonding dipole moment are strong during the vibrational process, as it occurs in C]O vibrations, the enhancement leads to detector overflow effects. Thus, it is not useful to analyse polyamides of each kind with the exception of very thin films. Within Fig. 12, several transmittance spectra are compared to corresponding attenuated total reflectance (ATR) spectra to illustrate advantages and disadvantages of IR transmittance measurements. 2.2.2 Transmittance of Microplastic Particles within KBr Pellets In the former section, it is shown that in the case of PE and PP, the enhancement effect of an IR transmittance measurement results in a very sensitive characterization method. Especially for analysis of ageing processes, e.g. photo-oxidation or biofilm contaminations, this can be very interesting. The problem that microplastics are too small for almost every commercially available sample holder techniques can be solved by creating a potassium bromide (KBr) pellet. The potassium salt is used due to its ionic bond, which hardly absorbs IR radiation, and its glassy character. Under increased pressure (about 10 bar), KBr starts melting and includes and partly solves the microplastic sample. In this context, cryomilling sample pretreatment is useful to ensure, that the KBr/microplastics mixture is distributed homogeneously. The emerging pellet can be placed into a special holder, as shown in Fig. 13. In addition to transmitting processes, the IR beam is reflected at the particles within the pellet but most of the reflected radiation cannot be detected. Signal intensity and S/N of this technique are, therefore, lower than for analysis of a polymer film. A KBr pellet may contain not a single but a blend of different sample particles, e.g. various polymer types, sand or wood. The observed FT-MIR spectrum will therefore contain signals of all these

Sample Size (mm)

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1 mm in size. In contrast, IR microscopy is not capable of identifying particles smaller than 10e20 mm [1,22,40]. The advantage of high resolution may be used to circumvent the problems posed by deposits on the microplastic particles and/or partial degradation of the surface. With microscope assistance, one may locate a clean area on the surface and collect the spectrum from that area. This scenario is perfectly illustrated in Fig. 10, showing three Raman spectra collected at different surface locations of an organically coated plastic particle. In the first spectrum, only carbonaceous signals originating from the biofilm on the plastic’s surface are identified. The second spectrum has a mixed profile, showing elements of the organic coating as well as clearly visible polypropylene bands. Only the latter are visible in the third spectrum, which was collected in a clean sample spot. Thus, excellent Raman spectra could be obtained even when the sample was clearly contaminated. More often, Raman microscopy is used to create 2D images of nonhomogeneous samples falsely coloured according to chemical composition. The combination of Raman microscopy with Atomic Force Microscopy

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FIGURE 10 Raman spectra collected at different surface locations showing the detrimental effect of organic matter coating on the polymer matrix. Corresponding degree of plastic surface fouling (right). Red square designates the point of Raman measurement. Reprinted from R. Lenz, K. Enders, C.A. Stedmon, D.M.A. Mackenzie, T.G. Nielsen, A critical assessment of visual identification of marine microplastic using Raman spectroscopy for analysis improvement, Mar. Pollut. Bull. 100 (2015) 82e91 with permission from Elsevier.

(Raman-AFM) for nanoscale imaging with chemical analysis is possibly the most significant development for materials science studies [16]. Confocal Raman microscopy can be used to analyze structured layered materials or to create 3D images of microplastics inside living organisms. However, due to the inherent weakness of the classical Raman signal, the analysis of microplastics at the subcellular level mostly relies on CARS techniques [5e7]. Surely, not everything is smooth sailing in the field of Raman analysis of microplastics. Instead, this emerging field of study is plagued with various challenges. In the remainder of this section, the various mystifying features affecting spectroscopic Raman readings are exposed and clarified. Before presenting some typical examples of such challenges we shall contemplate two well-known basic Raman disadvantages and the ways in which those may be addressed: fluorescence and laser-induced degradation. A major problem for Raman measurements lies in the high levels of fluorescence (intrinsic or caused by impurities) overlaying the Raman bands. As stated before, in most cases, this can be avoided by shifting the laser wavelength to the NIR spectral region. When fluorescence is caused by sample impurities, it is also possible to increase exposure time prior to recording the spectra and hope for the laser-bleaching effect; laser-induced degradation of the impurities present at the focal point will reduce fluorescence.

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Of course, laser-induced degradation may negatively affect the sample. All samples have a laser power density threshold beyond which structural or chemical modification may occur. As high irradiance is used to generate maximum Raman scattering, this threshold should be always considered to avoid sample damage. Damage results either from direct photodegradation (e.g., photochemical bond cleavage) or from sample heating. In both cases, the problem may be minimized by reducing laser power e but that will be done at the expense of signal intensity e which diminishes. Photodegradation is less prone to occur with NIR lasers but, as in the case of fluorescence, exceptions can be found. Sample heating becomes evident in the Raman spectrum even before sample degradation: due to the associated IR emission, the spectrum baseline is raised and distorted, hampering sample identification. The sample heating effect can be minimized by providing a better heat dissipation (e.g., using larger liquid samples, more compact powder samples or ‘dilute’ the sample in KBr pellets). Black samples can strongly absorb laser light, heat up and produce intense background emission or even degrade. For samples at temperatures above 250 C, intense black body emission can mask the Raman signal. The Raman signal confounding factors in environmental microplastics are well-covered elsewhere in the literature [1]. In general, there is a widespread agreement that challenges are related to multicomponent microplastic samples [17e20], UV degradation [1] and fluorescence [17,21]. Of the various components that microplastics may contain we can highlight, apart from the basic polymer matrix, additive compounds (such as fillers, colourants, pigments, dyes and TiO2), environmental waste (such as carbonaceous materials and organic residuals from animal organisms) and live organisms forming biofilms on the surface [1]. Considering these challenges, all results and interpretations must be taken carefully, thus allowing the correct identification of polymer type. The examples below highlight the most common identification difficulties faced so far. Let us consider the Raman spectra of a coloured microplastic particle (polystyrene with pigment blue 15) obtained from freshwater beach sediment [17]. This represents a case of a strong overlay of the polymer-type spectra due to a more intense compound in the polymer matrix, in this case a colour pigment (Fig. 11). In this particular case, the spectral profile of the pigment is so dominant that the characteristic peak of polystyrene, around 1030 cm 1, could only be observed after 250 s of acquisition time. It was possible to thereby identify the sample as a mixture of polystyrene and pigment Blue 15. It should be highlighted, however, that this long acquisition time is not typical. Examples not plagued with pigment contamination may be successfully identified in merely 1 s [22].

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FIGURE 11 Raman spectra with several acquisition times and corresponding reference spectra (polystyrene and pigment blue 15). Reprinted from H.K. Imhof, C. Laforsch, A.C. Wiesheu, J. Schmid, P.M. Anger, R. Niessner, N.P. Ivleva, Pigments and plastic in limnetic ecosystems: a qualitative and quantitative study on microparticles of different size classes, Water Res. 98 (2016) 64e74 with permission from Elsevier.

Limitations in Raman spectra analysis due to sample degradation by exposure to UV radiation are illustrated below using the example of polyvinylchloride (PVC) degradation (Fig. 12). PVC is relatively prone to photodegradation in the marine environment as the leakage of the large content of additives, such as photostabilisers, is enhanced under high-humidity conditions. After photodegradation, the Raman spectrum of PVC shows a simultaneous intensity reduction of the neighbouring peaks at 693 and 637 cm 1, which correspond to the characteristic CeCl bonds of the polymer. For the spectrum corresponding to the highest UV exposure (Fig. 12F), a complete absence of these double peaks and the presence of two strong peaks (marked with *) at 1139 and 1540 cm 1, assigned to carbon double bonds (C]C) are observed. Matching results from the spectral library search have shown that the Raman spectrum of the UV degraded PVC sample has changed to such degree that its automated identification was not successful. A strong match was impossible since the only reference for PVC was that of a pristine (nondegraded) sample. In the light of this drawback, it is of utmost importance that spectra of degraded polymers at different degradation stages be included in the reference library, thus increasing the chance of the matching software correctly identifying the polymeric composition. Many organic colourants, pigments and dyes intensely fluoresce in visible light, and thus the identification of polymers in some coloured particles may

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FIGURE 12 Comparison of an untreated control (A) and Raman spectra of a photoexposed polyvinylchloride sample (BeF) and an untreated control. Reprinted from R. Lenz, K. Enders, C.A. Stedmon, D.M.A. Mackenzie, T.G. Nielsen, A critical assessment of visual identification of marine microplastic using Raman spectroscopy for analysis improvement, Mar. Pollut. Bull. 100 (2015) 82e91 with permission from Elsevier.

be hindered by a high fluorescence background. Alternatively, biofilm growth caused by bacterial colonization on the microplastic surface may also be a culprit of fluorescence. Such Raman signal confounding factor is herein illustrated with the Raman spectra of commercially available polyethylene and biodegradable bags incubated in oxic sediment slurries [21]. Their Raman spectra exhibited autofluorescence leading to elevated background at higher Raman shifts and a poor signal-to-noise ratio (Fig. 13). Comparing the Raman peaks of the different treated samples (pristine, inactive and active sediments) the most evident variation was an increased fluorescence in incubated samples.

4. STATE-OF-THE-ART The identification of microplastics through the use of Raman spectroscopy is yet to attain the popularity of FT-IR spectroscopy techniques. At this juncture (August 2016), a search on ISI Web of Knowledge and ResearchGate yields a total of 28 documents on microplastic identification using Raman spectroscopy. Among these one finds 24 original articles [1,5e7,17e20,22e37], 3 reviews [14,38,39] and 1 book chapter [40]. Out of the 24 original works, 75% employ Raman microscopy, 12.5% make use of classical Raman spectroscopy [32,34,36] and the remainder use CARS [5e7]. The overwhelming preference for Raman microscopy over the classical setup is unsurprising, as it dispenses with manual particle

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FIGURE 13 Raman spectra of (A) biodegradable bag and (B) polyethylene bags incubated in oxic sediment slurries. Bag sample without treatment (pristine), bag samples incubated in inactive slurry (inactive) and bag samples incubated in active slurry (active). Reprinted from A. Nauendorf, S. Krause, N.K. Bigalke, E.V. Gorb, S.N. Gorb, M. Haeckel, M. Wahl, T. Treude, Microbial colonization and degradation of polyethylene and biodegradable plastic bags in temperate finegrained organic-rich marine sediments, Mar. Pollut. Bull. 103 (2016) 168e178 with permission from Elsevier.

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collection, thus speeding up the identification process and allowing the detection of very small particles that would otherwise be impossible to collect. CARS has so far only been applied for the visualization of microplastics inside living organisms, as greater complexity has precluded its use in more routine analysis. One-third of the original papers report the analysis of sediments [17,18,22,23,29,33,35,36] while 29% analyzed water samples, both seawater [1,20,30,33,34] and freshwater [26,31]. Biological tissues [5e7,19,24,27,28,32,33] are the most represented sample type, at 39%, while consumer beverages [37] remain uncharted territory, appearing in merely one (4%) of the reviewed articles (Fig. 14). The series of steps mediating the moment of sample collection and that of its unequivocal identification depends heavily upon the type of sample, aquatic ones being the easiest and biological tissues the most cumbersome to process. At present there is no benchmark methodology for microplastic identification, yet a common series of steps is usually followed.

FIGURE 14 Example of plastics from fish stomachs identified by Raman spectroscopy. From left to right, upper row polyethylene, polyethylene terephthalate (PET) and polyethylene; middle row polypropylene; bottom row PET/polypropylene, polypropylene and polyethylene. Reprinted from F. Collard, B. Gilbert, G. Eppe, E. Parmentier, K. Das, Detection of anthropogenic particles in fish stomachs: an isolation method adapted to identification by Raman spectroscopy, Arch. Environ. Contam. Toxicol. 69 (2015) 331e339 with permission from Springer.

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Sample collection Sample isolation: digestion, separation, filtration, drying Visual identification Raman spectrum recording Identity assignment

Some of these steps are fraught with challenges, to which researchers responded with a breadth of solutions. The most relevant solutions for Raman identification will be highlighted and the remainder quickly summarized. Those studies employing CARS will be discussed separately as they do not follow this sequence. The first troublesome step is sample isolation. The task’s degree of difficulty increases as one goes from aquatic, to sediment and to biological samples. In the majority of cases reviewed, scientists dealing with seawater or freshwater simply filter the sample and dry it. When dealing with sediments, one has to contend with the presence of organic and inorganic debris in the same size range as the microplastics intended for analysis, so that a separation process is mandatory, be it classical density separation, froth flotation or centrifugation. Some cases also require a digestion step to remove the organic load that would otherwise clog the filters, hamper visual detection and confound Raman signals when present on the plastic surface. Biological samples almost always require a digestion process, sometimes followed by a separation method. Density separation methods take advantage of the fact that most plastics have densities in the 0.8e1.4 g/cm3 range and employ slightly denser salt solutions that cause them to float, while nonplastic debris with higher densities fall to the bottom. Any cheap and noncorrosive salt solution fits the task, such as NaI [18,33], ZnCl2 [17,22,31], Na2WO4 [28,36], NaCl [29] and HCOOK [35] in concentrations ranging from 1.5 to 1.7 g/cm3. Apparently trivial, the separation step is crucial for securing a representative sample of microplastic particles of all sizes. Until recently, the recovery of very small particles (under 50 mm) was overlooked, partly because the detection methods used were unfit to identify particles of such size. As a result, separation methods were not optimized for very small particle recovery. Raman microscopy allows the identification of particles as small as 1 mm. Aiming to take full advantage of such capacity, Imhof et al. [22] developed a one-step method for density separation, which relies on an apparatus of their own creation, the Munich Plastic Sediment Separator (MPSS), shown in Fig. 15. The new MPSS method was compared with classical density separation and froth flotation using model microplastics. For large particles (1e5 mm), the classical density and the MPSS methods performed equally well, with a recovery rate of 99%. Froth floatation was ruled out since it delivered a mere 55% of particles in all size categories, being much more effective for low

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FIGURE 15 Munich plastic sediment separator apparatus (http://www.hydrobios.de/product/ microplastic-sediment-separator-mpss/).

density polymers while failing to recover denser particles. The advantage of the new MPSS apparatus only becomes evident when recovering small particles (