Handbook of Microplastics in the Environment 3030390403, 9783030390402

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Teresa Rocha-Santos Monica F. Costa Catherine Mouneyrac Editors

Handbook of Microplastics in the Environment

Handbook of Microplastics in the Environment

Teresa Rocha-Santos • Monica F. Costa • Catherine Mouneyrac Editors

Handbook of Microplastics in the Environment With 157 Figures and 91 Tables

Editors Teresa Rocha-Santos Centre for Environmental and Marine Studies (CESAM) and Department of Chemistry University of Aveiro Aveiro, Portugal

Monica F. Costa Departamento de Oceanografia, Laboratório de Ecologia e Gerenciamento de Ecossistemas Costeiros e Estuarinos Universidade Federal de Pernambuco Recife, Brazil

Catherine Mouneyrac Faculty of Sciences Université Catholique de L’Ouest Angers cedex 01, France

ISBN 978-3-030-39040-2 ISBN 978-3-030-39041-9 (eBook) ISBN 978-3-030-39042-6 (print and electronic bundle) https://doi.org/10.1007/978-3-030-39041-9 © Springer Nature Switzerland AG 2022 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors, and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Springer imprint is published by the registered company Springer Nature Switzerland AG. The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland

Preface

Microplastics are ubiquitous contaminants present in all the environment compartments and can be either particles produced for several applications such as microspheres and pellets or particles resulting from fragmentation of bigger plastics. Microplastics can adsorb other contaminants and may cause adverse effects in ecosystems. There are several gaps and research needs in the microplastics area such as the development of analytical methodologies which lead to the existence of yet scarce data on microplastics concentration in the environment. There is also an urgent need to gain knowledge on the environmentally relevant concentrations of microplastics and therefore on the understanding of microplastics degradation, interaction, and impact on the environment. The Handbook of Microplastics in the Environment is a reference source covering the major topics related with microplastics, from their analysis in the environment to their degradation and impact with biota and to their regulation and remediation. Moreover, this handbook brings information and knowledge that will be of fundamental importance to better understand the risk of microplastics as emergent environmental pollutants. The handbook is organized into four main sections. The first section, entitled Analysis of Microplastics in the Environment, is (co)edited by Dr. João P. da Costa and Dr. Armando Duarte and comprises a total of 17 chapters on the analytical methodologies for the identification and quantification of microplastics and on case studies of microplastics’ different environmental compartments. The second section, entitled Microplastics Degradation and Interaction with Chemical Pollutants, is edited by Dr. Lorena Mendoza and comprises 12 chapters. The third section, entitled Fate, Behavior, and Impact of Microplastics, is edited by Dr. Alessio Gomiero and has a total of 11 chapters. The fourth section, entitled Microplastics Regulation and Remediation, is edited by Dr. Juan Santos-Echeandía and comprises a total of 11 chapters. Each section has been written by international authors who are authorities in their field. The editors of the handbook would like to thank the section editors, Dr. João P. da Costa, Dr. Armando Duarte, Dr. Lorena Mendoza, Dr. Alessio Gomiero, and Dr. Juan Santos-Echeandía, for all their work, from author invitation to paper acceptance. Thanks are also due to Dr. Sofia Costa, Ms. Divya

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Preface

Nithyanandam, and Dr. Parasuraman Aiya Subramani for all the help, assistance, and advice. The editors also would like to thank each author; the chapters they submitted were organized into sections of the handbook covering the main issues related to microplastics, thus targeting a broad range of readers. Aveiro, Portugal Recife, Brazil Angers cedex 01, France February 2022

Teresa Rocha-Santos Monica F. Costa Catherine Mouneyrac

Contents

Volume 1 Section I Analysis of Microplastics in the Environment . . . . . . . . . . João P. da Costa and Armando C. Duarte 1

Introduction to the Analytical Methodologies for the Analysis of Microplastics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . João P. da Costa and Armando C. Duarte

1

3

2

Collection and Separation of Microplastics . . . . . . . . . . . . . . . . . . João P. da Costa, Armando C. Duarte, and Monica F. Costa

33

3

SEM/EDS and Optical Microscopy Analysis of Microplastics . . . . Ana Violeta Girão

57

4

Microplastic Characterization by Infrared Spectroscopy . . . . . . . Jun-Li Xu, Martin Hassellöv, Keping Yu, and Aoife A. Gowen

79

5

Microplastics Characterization by Raman Microscopy . . . . . . . . . Barbara E. Oßmann

113

6

Microplastics Detection Using Pyrolysis-GC/MS-Based Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Alexandre Dehaut, Ludovic Hermabessiere, and Guillaume Duflos

7

Airborne Microplastics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Joana C. Prata, Joana L. Castro, João P. da Costa, Mário Cerqueira, Armando C. Duarte, and Teresa Rocha-Santos

8

Microplastics in Soils and Sediment: Sources, Methodologies, and Interactions with Microorganisms . . . . . . . . . . . . . . . . . . . . . . Julie R. Peller, Jon Paul McCool, and Michael Watters

9

Microplastics in Freshwater Ecosystems . . . . . . . . . . . . . . . . . . . . Shaun A. Forrest, Madelaine P. T. Bourdages, and Jesse C. Vermaire

141 177

203 235

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10

Contents

Plastic Debris Flowing from Rivers to Oceans: The Role of the Estuaries as a Complex and Poorly Understood Key Interface . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Rachid Dris, Romain Tramoy, Soline Alligant, Johnny Gasperi, and Bruno Tassin

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11

Microplastics in Polar Samples . . . . . . . . . . . . . . . . . . . . . . . . . . . . V. Tirelli, G. Suaria, and Amy L. Lusher

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12

Microplastics in Wastewater . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Muhammad Tariq Khan, Yan Laam Cheng, Saba Hafeez, Yiu Fai Tsang, Jieqiong Yang, and Asim Nawab

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13

Microplastics in Biota . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Krishna Gautam, Shreya Dwivedi, and Sadasivam Anbumani

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14

Analysis of Microplastics in Food Samples . . . . . . . . . . . . . . . . . . . Juan A. Conesa and Maria E. Iñiguez

377

15

Analysis of Chemical Compounds Related to Microplastics Lorena M. Rios-Mendoza and Mary Balcer

.....

393

16

Identification of Microorganisms Related to Microplastics . . . . . . Deo Florence L. Onda and Kawthar M. Sharief

443

17

Challenges in the Analysis of Micro- and Nanoplastics . . . . . . . . . Peter Kusch

477

Section II Microplastics Degradation and Interactions with Chemical Pollutants . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Lorena M. Rios-Mendoza 18

Microplastics Aggregation, Deposition, and Enhancement of Contaminants Transport . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . D. P. Korfiatis

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19

Sorption of Pollutants on Microplastics . . . . . . . . . . . . . . . . . . . . . Hrissi K. Karapanagioti and Lorena M. Rios-Mendoza

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20

Degradation of Microplastics in the Environment . . . . . . . . . . . . . Patricia L. Corcoran

531

21

Contaminant Release from Aged Microplastic . . . . . . . . . . . . . . . . Tao Lan

543

22

Effects of Biofouling on the Sinking Behavior of Microplastics in Aquatic Environments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Claudia Halsband

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23

Sorption of Pharmaceuticals on Microplastics . . . . . . . . . . . . . . . . Lúcia H. M. L. M. Santos, Sara Rodríguez-Mozaz, and Damià Barceló

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24

Sorptive Properties of Microplastics Extracted from Cosmetics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Sarva Mangala Praveena and Ahmad Zaharin Aris

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Sorption of Potentially Toxic Elements to Microplastics João Frias

........

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Microplastics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . José Antonio Baptista Neto, Christine Gaylarde, and Estefan Monteiro da Fonseca

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27

The Role of Microplastics in Bioaccumulation of Pollutants . . . . . Tania Pelamatti, Lara Roberta Cardelli, and Lorena M. Rios-Mendoza

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28

Pollutants Bioavailability and Toxicological Risk from Microplastics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Farhan R. Khan, Danae Patsiou, and Ana I. Catarino

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Challenges Between Analytics and Degradation/Interactions of Microplastics with Pollutants/Presence of Additives . . . . . . . . . . . Montserrat Filella

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Volume 2 Section III Fate, Behavior, and Impacts of Microplastics . . . . . . . . Alessio Gomiero

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Microplastic Fate and Impacts in the Environment . . . . . . . . . . . . Andy M. Booth and Lisbet Sørensen

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Fate and Behavior of Microplastics in Freshwater Systems . . . . . . Thilakshani Atugoda, Hansika Piyumali, Sureka Liyanage, Kushani Mahatantila, and Meththika Vithanage

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32

Distribution of Microplastics in the Marine Environment . . . . . . . P. Strafella, M. López Correa, I. Pyko, S. Teichert, and Alessio Gomiero

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Sources and Fate of Microplastics in Urban Systems . . . . . . . . . . . Marte Haave and Taran Henriksen

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34

Microplastics Effects in the Terrestrial Environment . . . . . . . . . . . Luís A. Mendes

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Effects of Microplastics in the Cryosphere . . . . . . . . . . . . . . . . . . . Ásta Margrét Ásmundsdóttir and Bettina Scholz

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36

Impact of Microplastics in Human Health . . . . . . . . . . . . . . . . . . . Elora Fournier, Lucie Etienne-Mesmin, Stéphanie Blanquet-Diot, and Muriel Mercier-Bonin

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37

Microplastic Impacts in Fisheries and Aquaculture . . . . . . . . . . . . Amy L. Lusher and Natalie A. C. Welden

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38

Physical Impacts of Microplastics on Marine Species Yoann Garnier, François Galgani, and Françoise Claro

39

Ecological Effects of Chemical Contaminants Adsorbed to Microplastics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1019 Sammani Ramanayaka, Oshadi Hettithanthri, Sandun Sandanayake, and Meththika Vithanage

40

Microplastic: A New Habitat for Biofilm Communities . . . . . . . . . 1049 Mechthild Schmitt-Jansen, Stefan Lips, Hannah Schäfer, and Christoph Rummel

. . . . . . . . . . 1005

Section IV Microplastics: Regulation and Remediation . . . . . . . . . Juan Santos-Echeandía

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41

Microplastics Pollution and Regulation . . . . . . . . . . . . . . . . . . . . . 1071 Jesús Gago, Andy M. Booth, Rachel Tiller, Thomas Maes, and Joana Larreta

42

Microplastic Pollution and Reduction Strategies . . . . . . . . . . . . . . 1097 Katrin Schuhen and Michael T. Sturm

43

Governance and Measures for the Prevention of Marine Debris . . . . 1129 Theresa Stoll, Peter Stoett, Joanna Vince, and Britta Denise Hardesty

44

Removal of Microplastics from Wastewater . . . . . . . . . . . . . . . . . . 1153 Javier Bayo, Sonia Olmos, and Joaquín López-Castellanos

45

Soil Remediation Under Microplastics Pollution . . . . . . . . . . . . . . 1173 Esperanza Huerta Lwanga and Juan Santos-Echeandía

46

Remediation of Contaminated Waters with Microplastics . . . . . . . 1203 Irma Pérez-Silva, T. Montesinos-Vázquez, and M. E. Páez-Hernández

47

Role of Microorganisms in Eco-remediation Ana L. Patrício Silva

. . . . . . . . . . . . . . . . . 1237

Contents

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Protection of Underground Aquifers from Micro- and Nanoplastics Contamination . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1277 Diana Campos and João L. T. Pestana

49

Surveillance of Seafood for Microplastics . . . . . . . . . . . . . . . . . . . . 1311 Tanja Kögel, Alice Refosco, and Amund Maage

50

Microplastics and the UN Sustainable Development Goals . . . . . . 1345 Carla Elliff, Maria Teresa Castilho Mansor, Rita Feodrippe, and Alexander Turra

51

Microplastics into the Anthropocene . . . . . . . . . . . . . . . . . . . . . . . 1363 Juliana A. Ivar do Sul and Matthias Labrenz

Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1379

About the Editors

Teresa Rocha-Santos has graduated in analytical chemistry (1996) and obtained a PhD in chemistry (2000) and an aggregation in chemistry (2018), both from the University of Aveiro, Portugal. Presently, she is a principal researcher at the Centre for Environmental and Marine Studies (CESAM) and the Department of Chemistry at the University of Aveiro (since 2014) and vice coordinator of CESAM (from 2021). Her research concentrates on the development of new analytical methodologies fit for purpose and on the study of emerging contaminants (such as microplastics) and their fate and behavior in the environment and during wastewater treatment. She has published 170 scientific papers (October 2021) and has an h-index of 43 (October 2021). She is the editor of seven books. She is a member of the editorial boards of Current Opinion in Environmental Science and Health, Elsevier (since 2017); Data in Brief, Elsevier (since 2018); Science of the Total Environment, Elsevier (since 2018); Sensors, MDPI (since 2018); and Molecules, MDPI (since 2018). She is associate editor of the Euro-Mediterranean Journal for Environmental Integration, Springer (since 2016), and the Journal of Hazardous Materials (since 2019) and co-editor-in-chief of the Journal of Hazardous Materials Advances (since 2021).

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About the Editors

Monica Costa has completed BSc in Oceanography (UERJ, 1988), MPhil in Analytical Chemistry/Marine Chemistry (PUC-Rio, 1991), and PhD in Environmental Sciences (ENV-UEA Norwich UK, 1997). She is Full Professor in Chemical Oceanography and Marine Pollution at Federal University of Pernambuco (UFPE). Her teaching and research interests are chemical oceanography and marine pollution. She is also involved in research and in guiding BSc, MPhil, and PhD students in Integrated Coastal Zone Management and water quality; plastic marine debris; chemical contamination of water, sediments and biota at coastal and marine systems; aquatic toxicology; oil/tar pollution on beaches; and environmental education in coastal and marine issues, including collaborations with traditional populations. Catherine Mouneyrac Professor of Ecotoxicology, vice rector for research and valorization (Université Catholique de l’Ouest Angers, France), holds a PhD (University of Lyon I, France) in animal physiology and a DSc in aquatic ecotoxicology (University of Nantes, France). Her general field of research concerns the response of organisms to natural and chemical stress, namely nanomaterials. At the interface of fundamental and applied research, she aims to fulfill the gap between ecological and (eco)toxicological approaches, the final objective being to help environmental diagnosis. She collaborates with researchers all around the world and has participated in the conception and realization of numerous national and international scientific projects (NanoSalt, NanoReTox, and NANoREG, among others). She is part of the expert committee on the assessment of the risks related to physical agents, new technologies, and development areas at the French Agency for Food, Environmental and Occupational Health & Safety (ANSES). She is a scientific officer at French National Research Agency (ANR) and has been selected as a decision maker to follow the national study course of Institut des Hautes Etudes pour la Science et la Technologie (http://www.ihest.fr).

About the Section Editors

João P. da Costa Centre for Environmental and Marine Studies (CESAM) and Department of Chemistry University of Aveiro Aveiro, Portugal João Pinto da Costa is an assistant researcher at the Center for Marine and Environmental Studies and the Department of Chemistry at the University of Aveiro (Portugal). Presently, his research focuses on the development of strategies for the adequate assessment of the prevalence of emerging contaminants, namely (micro) plastics, as well as their fate and behavior in the terrestrial and aquatic environments. He is also particularly interested in bio-based approaches for the mitigation of plastic contamination (biodegradation of microplastics). João graduated in biotechnological engineering from the University of the Algarve (Portugal), and, soon thereafter, successfully completed his master’s degree in medical diagnostics at Cranfield University (UK). In 2014, he obtained his PhD in environmental chemistry from the University of the Algarve. João was also a Fulbright Fellow, under the framework of the INOV Contacto Program, in 2006, during which he worked at a biotech-based drug discovery company in California (USA). In recent years, João has had the opportunity to develop research activities in a wide field of areas, including proteomics, nanotechnology, bioremediation, food technology, and biosensing applications. João is the author or co-author of over 75 publications, with an h-index of 25.

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About the Section Editors

Armando C. Duarte Centre for Environmental and Marine Studies (CESAM) and Department of Chemistry University of Aveiro Aveiro, Portugal Armando da Costa Duarte (AdCD) graduated in chemical engineering (1977) at the University of Oporto (Portugal) and obtained a PhD in public health engineering (1981) from the University of Newcastle-upon-Tyne (UK). In 1977, AdCD started working at the University of Aveiro (Portugal), and in 1995, he was appointed Professor of Environmental and Analytical Chemistry, lecturing on the quality of data provided by a plethora of methods based on analytical chemistry for supporting decisions on food safety, health and environmental protection, and sustainable development. In 2006, the Portuguese Foundation for Science and Technology (FCT) awarded AdCD a prize for Scientific Excellence, and from 2013 to 2016, he was a member of the FCT Scientific Council for Natural and Environmental Sciences. In 2019, AdCD retired from lecturing but remained active in research at the University of Aveiro and Center for Environmental and Marine Studies (http://www.cesam.ua.pt/). As a researcher, AdCD has been particularly interested in the application of fit-forpurpose analytical methods for decoding complex samples and characterization of environmental quality, with more than 555 scientific publications and 17,000 citations, reaching an h-index (Scopus) of 66. Alessio Gomiero NORCE-Environment Randaberg, Norway Alessio Gomiero graduated in environmental science (2003) at the University of Venice (Italy) and obtained a PhD in environmental science (2009) from the same university. In 2009, he started working at the University of Venice, Department of Environmental Science, section of analytical chemistry, addressing the occurrence and toxicity of endocrine disrupting compounds (EDCs) in the environment and lately contributing to the development of biomonitoring programs and environmental risk assessment procedure to characterize the health

About the Section Editors

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status of coastal and marine ecosystems. Since 2014, he is senior researcher at the Norwegian Research Centre (Norway), and since 2020, he holds the position of associate researcher at the National Research Council of Italy – Institute of Biological Resources and Marine Biotechnologies (Italy). He is a member of several expert groups dealing with pollution in marine and freshwater environments, including pollutants of emerging concern such as pharmaceuticals and plastic litter. As scientist, Alessio is contributing to the field of analytical chemistry, ecotoxicology, and environmental risk assessment. Lorena M. Rios-Mendoza Department of Natural Sciences/Chemistry and Physics Program University of Wisconsin-Superior Superior, WI, USA Lorena M. Rios Mendoza was born in Chihuahua, Mexico. She graduated from the University of Baja California, Mexico, with distinction in Doctorate of Chemistry Oceanology (2001). She had previously earned a BS in chemistry (1989) from the National Autonomous University of Mexico (UNAM). Dr. Rios’ expertise is in environmental chemistry pollution. Her research is mainly on microplastic pollution and its association with persistent organic pollutants. She is a Full Professor of Chemistry in the Department of Natural Sciences at the University of WisconsinSuperior. She has been researching marine plastic debris pollution since 2003 in CA beaches and the Pacific Ocean. She started research on plastic debris contamination in the Great Lakes after participating in the first time collection of microplastic samples in 2012. During summer 2014, she went to the North Pacific Gyre to collect 6-week samples in the “Eastern Garbage Patch.” She has been presenting her research results at the American Chemical Society’s National Conferences and at the International Association for Great Lakes Research. Based on her 2012 research results on microplastic in the Great Lakes, the public and lawmakers have noticed plastic pollution in several areas of the USA. This ended in a ban bill signed by President Obama in 2015 of microbead plastics as ingredients in

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About the Section Editors

cosmetic products. She was invited to participate in the International Pellet Watch project in Japan. She served as a scientific panelist for the Joint Programming Initiative for Healthy and Productive Seas and Oceans (JPI Oceans, Microplastics 2015–2019 and Nanoplastics 2019–2022), Great Lakes Marine Debris Action Plan at the National Oceanic and Atmospheric Administrative (NOAA, 2019–2024), and the International Atomic Energy Agency (IAEA, 2020). She has been an associate editor of the International bilingual Ciencias Marinas since 2019. Juan Santos-Echeandía Spanish Institute of Oceanography (IEO) Oceanographic Centre of Vigo Vigo, Spain Juan Santos-Echeandía completed his PhD at the University of Vigo (Spain) in 2009, working on the biogeochemical cycle of trace metals in seawater, from the coast to open-ocean waters. After three postdoc positions – LEMAR-UBO (Brest, France), IPIMAR (Lisbon, Portugal), and Marine Research Institute (IIM-CSIC) (Vigo, Spain), he joined the Marine Pollution Group of the Spanish Oceanographic Institute in 2016 with a permanent position. His research interests include the biogeochemistry and chemical oceanography of trace elements, including their organic speciation. His interest has recently grown in the study of interactions between metals and microplastics in aquatic environments. Juan is author of more than 55 scientific papers and book chapters. He has supervised two PhD theses.

Contributors

Soline Alligant Ecole des Ponts ParisTech, LEESU (UMR MA 102) Université Paris-Est Créteil, Créteil Cedex, France Sadasivam Anbumani Ecotoxicology Laboratory, Regulatory Toxicology Group, CSIR-Indian Institute of Toxicology Research (IITR), Lucknow, India Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, India Ahmad Zaharin Aris Department of Environment, Faculty of Forestry and Environment, Universiti Putra Malaysia, Serdang, Selangor, Malaysia Ásta Margrét Ásmundsdóttir School of Business and Science, University of Akureyri, Akureyri, Iceland Thilakshani Atugoda Ecosphere Resilience Research Centre, Faculty of Applied Sciences, University of Sri Jayewardenepura, Nugegoda, Sri Lanka Mary Balcer Department of Natural Sciences, University of Wisconsin-Superior, Superior, WI, USA José Antonio Baptista Neto Department of Geology and Geophysics/ LAGEMAR – Laboratório de Geologia Marinha, Instituto de Geociências, Universidade Federal Fluminense, Niterói, Brazil Damià Barceló Catalan Institute for Water Research (ICRA), Girona, Spain Universitat de Girona, Girona, Spain Department of Environmental Chemistry, IDAEA-CSIC, Barcelona, Spain Javier Bayo Department of Chemical and Environmental Engineering, Technical University of Cartagena, Murcia, Spain Stéphanie Blanquet-Diot Université Clermont Auvergne, INRAE, UMR 454 MEDIS (Microbiology, Digestive Environment and Health), Clermont-Ferrand, France Andy M. Booth SINTEF Ocean, Trondheim, Norway xix

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Contributors

Madelaine P. T. Bourdages Geography and Environmental Studies, Carleton University, Ottawa, ON, Canada Diana Campos CESAM and Department of Biology, University of Aveiro, Aveiro, Portugal Lara Roberta Cardelli Acquario di Cattolica, Cattolica, RN, Italy Joana L. Castro Centre for Environmental and Marine Studies (CESAM) and Department of Chemistry, University of Aveiro, Aveiro, Portugal Centre for Environmental and Marine Studies (CESAM) and Department of Environment and Planning, University of Aveiro, Aveiro, Portugal Ana I. Catarino Vlaams Instituut voor de Zee, Flanders Marine Institute, InnovOcean site, Oostende, Belgium Mário Cerqueira Centre for Environmental and Marine Studies (CESAM) and Department of Environment and Planning, University of Aveiro, Aveiro, Portugal Yan Laam Cheng Department of Science and Environmental Studies, The Education University of Hong Kong, Tai Po, Hong Kong Françoise Claro UMS PatriNat OFB CNRS MNHN, Muséum National d’Histoire Naturelle, Paris, France Juan A. Conesa Department of Chemical Engineering, University of Alicante, Alicante, Spain Patricia L. Corcoran Department of Earth Sciences, University of Western Ontario, London, ON, Canada Monica F. Costa Departamento de Oceanografia, Laboratório de Ecologia e Gerenciamento de Ecossistemas Costeiros e Estuarinos, Universidade Federal de Pernambuco, Recife, Brazil João P. da Costa Centre for Environmental and Marine Studies (CESAM) and Department of Chemistry, University of Aveiro, Aveiro, Portugal Estefan Monteiro da Fonseca Department of Geology and Geophysics/ LAGEMAR – Laboratório de Geologia Marinha, Instituto de Geociências, Universidade Federal Fluminense, Niterói, Brazil Alexandre Dehaut Laboratoire de Sécurité des Aliments - Unité physico-chimie des produits de la pêche et de l’aquaculture, ANSES, Boulogne-sur-Mer, France Rachid Dris Ecole des Ponts ParisTech, LEESU (UMR MA 102) Université ParisEst Créteil, Créteil Cedex, France Armando C. Duarte Centre for Environmental and Marine Studies (CESAM) and Department of Chemistry, University of Aveiro, Aveiro, Portugal

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Guillaume Duflos Laboratoire de Sécurité des Aliments - Unité physico-chimie des produits de la pêche et de l’aquaculture, ANSES, Boulogne-sur-Mer, France Shreya Dwivedi Ecotoxicology Laboratory, Regulatory Toxicology Group, CSIRIndian Institute of Toxicology Research (IITR), Lucknow, India Carla Elliff Oceanographic Institute, University of São Paulo, São Paulo, Brazil Lucie Etienne-Mesmin Université Clermont Auvergne, INRAE, UMR 454 MEDIS (Microbiology, Digestive Environment and Health), Clermont-Ferrand, France Rita Feodrippe Oceanographic Institute, University of São Paulo, São Paulo, Brazil UNESCO Chair on Ocean Sustainability, Institute of Advanced Studies, University of São Paulo, São Paulo, Brazil Montserrat Filella Department F.-A. Forel, University of Geneva, Geneva, Switzerland Shaun A. Forrest Geography and Environmental Studies, Carleton University, Ottawa, ON, Canada Elora Fournier Université Clermont Auvergne, INRAE, UMR 454 MEDIS (Microbiology, Digestive Environment and Health), Clermont-Ferrand, France Toxalim (Research Center in Food Toxicology), Université de Toulouse, INRAE, ENVT, INP-Purpan, UPS, Toulouse, France João Frias Marine and Freshwater Research Centre (MFRC), Galway-Mayo Institute of Technology (GMIT), Galway, Ireland Jesús Gago Centro Oceanográfico de Vigo, Instituto Español de Oceanografía (IEO), Vigo, Spain François Galgani Ifremer, Immeuble Agostini, Bastia, France Yoann Garnier UMS PatriNat OFB CNRS MNHN, Muséum National d’Histoire Naturelle, Paris, France Johnny Gasperi Ecole des Ponts ParisTech, LEESU (UMR MA 102) Université Paris-Est Créteil, Créteil Cedex, France GERS-LEE, Université Gustave Eiffel, Bouguenais, France Krishna Gautam Ecotoxicology Laboratory, Regulatory Toxicology Group, CSIR-Indian Institute of Toxicology Research (IITR), Lucknow, India Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, India Christine Gaylarde Department of Microbiology and Plant Biology, Oklahoma University, Norman, OK, USA

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Contributors

Ana Violeta Girão Department of Materials and Ceramic Engineering, University of Aveiro – CICECO, Aveiro, Portugal Alessio Gomiero NORCE-Environment, Randaberg, Norway Aoife A. Gowen School of Biosystems and Food Engineering, University College Dublin, Dublin, Ireland Marte Haave Norwegian Research Centre, Climate and Environment, Bergen, Norway Department of Chemistry, University of Bergen, Bergen, Norway Saba Hafeez College of Earth Environmental Sciences, University of Punjab, Lahore, Pakistan Claudia Halsband Akvaplan-niva, Tromsø, Norway Britta Denise Hardesty Oceans and Atmosphere, CSIRO, Battery Point, TAS, Australia Centre for Marine Socioecology, University of Tasmania, Hobart, TAS, Australia Martin Hassellöv Department of Marine Sciences, University of Gothenburg, Göteborg, Sweden Taran Henriksen Norwegian Research Centre, Climate and Environment, Bergen, Norway Ludovic Hermabessiere Department of Ecology and Evolutionary Biology, University of Toronto, Toronto, ON, Canada Department of Civil and Mineral Engineering, University of Toronto, Toronto, ON, Canada Oshadi Hettithanthri Ecosphere Resilience Research Centre, Faculty of Applied Sciences, University of Sri Jayewardenepura, Nugegoda, Sri Lanka Esperanza Huerta Lwanga Wageningen University and Research (WUR) – A Soil Physics and Land Management Group, Wageningen, The Netherlands El Colegio de la Frontera Sur. Agroecología, El Colegio de la Frontera Sur, Unidad Campeche, Campeche, Mexico Maria E. Iñiguez Department of Chemical Engineering, University of Alicante, Alicante, Spain Juliana A. Ivar do Sul Leibniz Institute for Baltic Sea Research, WarnemündeRostock, Germany Hrissi K. Karapanagioti Department of Chemistry, University of Patras, Patras, Greece Farhan R. Khan Department of Biosciences, University of Oslo, Oslo, Norway

Contributors

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Muhammad Tariq Khan Department of Science and Environmental Studies, The Education University of Hong Kong, Tai Po, Hong Kong Tanja Kögel Contaminants and biohazards, Institute of Marine Research, Bergen, Norway Department of Biological Sciences, University of Bergen, Bergen, Norway D. P. Korfiatis Physics Department, University of Patras, Patras, Greece Peter Kusch Department of Applied Natural Sciences, Bonn-Rhein-Sieg University of Applied Sciences, Rheinbach, Germany Matthias Labrenz Leibniz Institute for Baltic Sea Research, WarnemündeRostock, Germany Tao Lan China National Institute of Standardization, Beijing, PR China Joana Larreta AZTI, Marine Research, Basque Research and Technology Alliance (BRTA), Pasaia, Spain Stefan Lips Department of Bioanalytical Ecotoxicology, Helmholtz Centre for Environmental Research GmbH – UFZ, Leipzig, Germany Sureka Liyanage Chemical and Microbiological Laboratory, Industrial Technology Institute, Colombo, Sri Lanka Joaquín López-Castellanos Department of Chemical and Environmental Engineering, Technical University of Cartagena, Murcia, Spain M. López Correa CNR-ISMAR, Consiglio Nazionale delle Ricerche, Istituto di Scienze Marine, Bologna, Italy GZN, GeoZentrum Nordbayern, Nürnberg, Erlangen, Germany

Friedrich-Alexander-Universität

Erlangen-

Amy L. Lusher Norwegian Institute for Water Research (NIVA), Oslo, Norway Amund Maage Contaminants and biohazards, Institute of Marine Research, Bergen, Norway University of Bergen, Bergen, Norway Thomas Maes Grid-Arendal, Arendal, Norway Kushani Mahatantila Chemical and Microbiological Laboratory, Industrial Technology Institute, Colombo, Sri Lanka Maria Teresa Castilho Mansor Oceanographic Institute, University of São Paulo, São Paulo, Brazil Secretariat for Infrastructure and Environment of São Paulo State, São Paulo, Brazil Jon Paul McCool Department of Geography and Meteorology, Valparaiso University, Valparaiso, IN, USA

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Contributors

Luís A. Mendes CESAM and Department of Chemistry, University of Aveiro, Aveiro, Portugal Muriel Mercier-Bonin Toxalim (Research Center in Food Toxicology), Université de Toulouse, INRAE, ENVT, INP-Purpan, UPS, Toulouse, France T. Montesinos-Vázquez Área Académica de Química, Lab. 2, Universidad Autónoma del Estado de Hidalgo, Mineral de la Reforma, Mexico Asim Nawab State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Beijing Normal University, Beijing, China Barbara E. Oßmann Bavarian Health and Food Safety Authority, Erlangen, Germany Sonia Olmos Department of Chemical and Environmental Engineering, Technical University of Cartagena, Murcia, Spain Deo Florence L. Onda Microbial Oceanography Laboratory, The Marine Science Institute, University of the Philippines, Diliman, Quezon City, Philippines M. E. Páez-Hernández Área Académica de Química, Lab. 2, Universidad Autónoma del Estado de Hidalgo, Mineral de la Reforma, Mexico Ana L. Patrício Silva Centre for Environmental and Marine Studies (CESAM) and Department of Biology, University of Aveiro, Aveiro, Portugal Danae Patsiou Institute of Oceanography, Hellenic Centre for Marine Research, Anavyssos, Greece Tania Pelamatti Instituto Politécnico Nacional, Centro Interdisciplinario de Ciencias Marinas (CICIMAR-IPN), La Paz, Baja California Sur, Mexico Pelagios Kakunjá A.C, La Paz, Baja California Sur, Mexico Julie R. Peller Department of Chemistry, Valparaiso University, Valparaiso, IN, USA Irma Pérez-Silva Área Académica de Química, Lab. 2, Universidad Autónoma del Estado de Hidalgo, Mineral de la Reforma, Mexico João L. T. Pestana CESAM and Department of Biology, University of Aveiro, Aveiro, Portugal Hansika Piyumali Ecosphere Resilience Research Centre, Faculty of Applied Sciences, University of Sri Jayewardenepura, Nugegoda, Sri Lanka Department of Natural Resources, Faculty of Applied Sciences, Sabaragamuwa University of Sri Lanka, Belihuloya, Sri Lanka Joana C. Prata Centre for Environmental and Marine Studies (CESAM) and Department of Chemistry, University of Aveiro, Aveiro, Portugal

Contributors

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Sarva Mangala Praveena Department of Environmental and Occupational Health, Faculty of Medicine and Health Science, Universiti Putra Malaysia, Serdang, Selangor, Malaysia Food Safety and Food Integrity, Institute of Tropical Agriculture and Food Security, Universiti Putra Malaysia, Serdang, Selangor Darul Ehsan, Malaysia I. Pyko GZN, GeoZentrum Nordbayern, Erlangen-Nürnberg, Erlangen, Germany

Friedrich-Alexander-Universität

Sammani Ramanayaka Ecosphere Resilience Research Centre, Faculty of Applied Sciences, University of Sri Jayewardenepura, Nugegoda, Sri Lanka Alice Refosco Contaminants and biohazards, Institute of Marine Research, Bergen, Norway Dipartimento di Scienze della Vita e dell’Ambiente, Università Politecnica delle Marche, Ancona, Italy Lorena M. Rios-Mendoza Department of Natural Sciences/Chemistry and Physics Program, University of Wisconsin-Superior, Superior, WI, USA Teresa Rocha-Santos Centre for Environmental and Marine Studies (CESAM) and Department of Chemistry, University of Aveiro, Aveiro, Portugal Sara Rodríguez-Mozaz Catalan Institute for Water Research (ICRA), Girona, Spain Universitat de Girona, Girona, Spain Christoph Rummel Department of Bioanalytical Ecotoxicology, Helmholtz Centre for Environmental Research GmbH – UFZ, Leipzig, Germany Sandun Sandanayake Ecosphere Resilience Research Centre, Faculty of Applied Sciences, University of Sri Jayewardenepura, Nugegoda, Sri Lanka Lúcia H. M. L. M. Santos Catalan Institute for Water Research (ICRA), Girona, Spain Universitat de Girona, Girona, Spain Juan Santos-Echeandía Spanish Institute of Oceanography (IEO), Oceanographic Centre of Vigo, Vigo, Spain Hannah Schäfer Department of Bioanalytical Ecotoxicology, Helmholtz Centre for Environmental Research GmbH – UFZ, Leipzig, Germany Mechthild Schmitt-Jansen Department of Bioanalytical Ecotoxicology, Helmholtz Centre for Environmental Research GmbH – UFZ, Leipzig, Germany Bettina Scholz Marine Biotechnology, BioPol ehf, Skagaströnd, Iceland Katrin Schuhen Wasser 3.0 gGmbH, Karlsruhe, Germany abcr GmbH, Karlsruhe, Germany

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Contributors

Kawthar M. Sharief Microbial Oceanography Laboratory, The Marine Science Institute, University of the Philippines, Diliman, Quezon City, Philippines Lisbet Sørensen SINTEF Ocean, Trondheim, Norway Peter Stoett Faculty of Social Science and Humanities, Ontario Tech University, Oshawa, ON, Canada Theresa Stoll School of Social Sciences, College of Arts, Law and Education, University of Tasmania, Hobart, TAS, Australia Oceans and Atmosphere, CSIRO, Battery Point, TAS, Australia Centre for Marine Socioecology, University of Tasmania, Hobart, TAS, Australia P. Strafella CNR-IRBIM, Consiglio Nazionale delle Ricerche, Istituto per le Risorse Biologiche e le Biotecnologie Marine, Ancona, Italy Michael T. Sturm Wasser 3.0 gGmbH, Karlsruhe, Germany abcr GmbH, Karlsruhe, Germany Engler-Bunte-Institut (EBI), Chair of Water Chemistry and Water Technology, Karlsruhe Institute of Technology, Karlsruhe, Germany G. Suaria Institute of Marine Sciences – National Research Council, ISMARCNR, La Spezia, Italy Bruno Tassin Ecole des Ponts ParisTech, LEESU (UMR MA 102) Université Paris-Est Créteil, Créteil Cedex, France S. Teichert GZN, GeoZentrum Nordbayern, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany Rachel Tiller SINTEF Ocean, Trondheim, Norway V. Tirelli National Institute of Oceanography and Applied Geophysics – OGS, Trieste, Italy Romain Tramoy Ecole des Ponts ParisTech, LEESU (UMR MA 102) Université Paris-Est Créteil, Créteil Cedex, France Yiu Fai Tsang Department of Science and Environmental Studies, The Education University of Hong Kong, Tai Po, Hong Kong Alexander Turra Oceanographic Institute, University of São Paulo, São Paulo, Brazil UNESCO Chair on Ocean Sustainability, Institute of Advanced Studies, University of São Paulo, São Paulo, Brazil Jesse C. Vermaire Geography and Environmental Studies, Carleton University, Ottawa, ON, Canada Institute for Environmental and Interdisciplinary Sciences, Carleton University, Ottawa, ON, Canada

Contributors

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Joanna Vince School of Social Sciences, College of Arts, Law and Education, University of Tasmania, Hobart, TAS, Australia Centre for Marine Socioecology, University of Tasmania, Hobart, TAS, Australia Meththika Vithanage Ecosphere Resilience Research Centre, Faculty of Applied Sciences, University of Sri Jayewardenepura, Nugegoda, Sri Lanka Michael Watters Department of Biology, Valparaiso University, Valparaiso, IN, USA Natalie A. C. Welden School of Interdisciplinary Studies, University of Glasgow, Dumfries, UK Jun-Li Xu School of Biosystems and Food Engineering, University College Dublin, Dublin, Ireland Jieqiong Yang Department of Science and Environmental Studies, The Education University of Hong Kong, Tai Po, Hong Kong Keping Yu Global Information and Telecommunication Institute, Waseda University, Shinjuku, Tokyo, Japan

Section I Analysis of Microplastics in the Environment Joa˜o P. da Costa and Armando C. Duarte

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Introduction to the Analytical Methodologies for the Analysis of Microplastics João P. da Costa and Armando C. Duarte

Contents Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Sampling and Sample Handling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Marine Water Sampling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Freshwater and Estuarine Sampling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Soil and Sediment Sampling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Biota Sampling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Atmospheric Sampling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Sample Handling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Extraction/Separation of Microplastics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Identification of Microplastics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Recommendations, Knowledge Gaps, and Future Venues of Research . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

4 5 5 8 12 15 17 18 20 23 25 27

Abstract

Ubiquitous and highly pervasive microplastics have been found in all compartments of the environment. However, correctly assessing their prevalence is greatly hampered by the current methodological and technical limitations, as well as data reporting and analysis. Herein, we discuss the most pressing issues associated with the analysis of microplastics in environmental samples (water, sediments, and biological tissues), from their sampling and sample handling to their identification and quantification. Furthermore, the need for analytical quality control and quality assurance associated with the validation of analytical methods, including the use of reference materials for the quantification of microplastics, is also examined. Lastly, the current challenges within this field of research and foreseeable routes to overcome such limitations are discussed. J. P. da Costa (*) · A. C. Duarte Centre for Environmental and Marine Studies (CESAM) and Department of Chemistry, University of Aveiro, Aveiro, Portugal e-mail: [email protected]; [email protected]; [email protected] © Springer Nature Switzerland AG 2022 T. Rocha-Santos et al. (eds.), Handbook of Microplastics in the Environment, https://doi.org/10.1007/978-3-030-39041-9_1

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J. P. da Costa and A. C. Duarte

Keywords

Microplastics · Analytical chemistry · Pollution · Environment

Introduction In recent years, plastic pollution and its consequences have become major causes of concern by scientists, policy-makers, and the public, in general. Owing to the exponentially growing production and use of these materials, plastic has become pervasive throughout the different spheres of the environment. Consequently, plastic particles have been in areas as remote as Antarctica (Reed et al. 2018) and the Mariana trenches (Peng et al. 2018) or isolated, inhabited areas (Allen et al. 2019). This is not surprising, considering that the global production of plastics surpassed 359 million tons in 2018, of which approximately 40% was intended for packaging (PlasticsEurope 2019) and, therefore, for immediate (or nearly immediate), disposal. Plastic pollution is therefore ubiquitous, and although the effects of this pollution are more evident for larger fragments, such as the ingestion of plastic materials by seabirds or whales or the entrapment of seals or sea turtles, smaller particles, commonly referred to as microplastics, could perhaps be more pervasive and constitute a more prominent risk towards global environmental health and, ultimately, to human health (da Costa et al. 2016). Microplastics are commonly defined as plastic particles and 25 mm) and mesoplastics (5–25 mm) can easily be detected by visual inspection, but microplastic recognition requires imaging techniques. Thus, microscopy is a determinant analytical tool for the identification and quantification of microplastics in water samples and aquatic biota, providing crucial information on the size, morphology, and chemical composition of such micromaterials.

Optical Microscopy The ecological effects of microplastics in aquatic systems, terrestrial media, and atmosphere have been under continuous scrutiny. Thus, methods and techniques for detection and identification of such microparticles inevitably evolved over the last decade. Optical-light microscopy (OM) was one of the first techniques used for visual inspection and evaluation of the shape and size of microplastics, clearly boosting the importance of microscopy as an essential imaging tool in materials and life sciences.

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Fig. 1 Schematic representation of micro-/ nanoplastic analysis using microscopy and spectroscopy

Light Microscopy Conventional optical-light microscopy was the first imaging technique enabling the transformation of an object outside the range of the unaided eye resolution into much larger images. The optical microscope is an instrument comprising one or more lenses that produce an enlarged image of an object of interest placed in the focal plane of the lens(es) (Croft 2006). There are two main imaging operating modes in OM, depending on the beam of light path. In the case of opaque and thick material observation, the light beam is reflected off the sample surface, contrast arises from differences in topography and reflectivity, and a common optical microscope is used in the reflection imaging mode. In transmission imaging mode, the beam passes through fine powders, or nearly transparent thin samples (e.g., tens of microns thick); the contrast results from different regions of light absorption, and a polarized microscope is usually used. Polarized light microscopy is a particular specialized use of the transmission imaging mode where contrast is due to differences in birefringence (the refractive index of a material depends on the polarization and propagation direction of light) and thickness of the sample, enabling observation of grains and the specimen thickness (Rane et al. 2018; Murphy 2002; Mertz 2019; Török and Kao 2007; Bradbury et al. 1998).

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Fig. 2 Illustrative diagram of the transmission optical microscope and its basic light pathway

In a simple manner, the light transmitted by the illumination source (halogen lamp, lasers, or LEDs) is focused and densified into a more intense one by a condenser lens and illuminates the object of interest fixed onto a mechanical stage. The specimen can be moved under a revolving nosepiece which holds several objective lenses with different augmentation. Most objective lenses are designed to image specimens in air, but higher resolution can be attained when using objectives specially designed to work in immersion media (oil, glycerin, or water) since it reduces the difference between the refractive index of glass and the imaging medium. Independently of the operating imaging mode, the brightness of the image is defined by the light-gathering power of the objective. Finally, the latter collects the light forming a focused real image which, in its turn, is again enlarged by the ocular lenses. The product of the powers of the ocular and objective lenses determines the image yielded magnification (Rane et al. 2018; Goodhew and Humphreys 2000; Murphy 2002; Mertz 2019; Török and Kao 2007; Bradbury et al. 1998; Girkin 2019). A diagram illustrating the basic light pathway in a transmission optical microscope system is depicted in Fig. 2. Other types of optical microscopes are used in materials and life sciences, mainly based on properties exhibited by the material. It is the case of fluorescence microscopy in which some atoms of molecules of the materials absorb light at a certain wavelength and subsequently emit light of longer wavelength, particularly useful in examination of biological samples. Laser scanning confocal microscopy is another technique in which scanning a diffraction-limited point of excitation light across the sample and a confocal “pinhole” eliminates the out-of-focus light rays. The latter enables 3D reconstruction of the acquired optical sectioning images, particularly useful for live cell assessment (Rane et al. 2018; Mertz 2019; Török and Kao 2007; Girkin 2019).

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Optical microscopy was the first characterization technique used to investigate microplastics since naked-eye observation is insufficient to fully recognize such pollutants. It provides information regarding size distribution (depends on the microscope resolution limit), morphology, thickness (depends on the imaging mode), topography (focus series), degradation stage, and color. The size range of the microplastics within a certain sample and their morphology are the most important information given by optical microscopy since it enables visual sorting of the particles prior to any further analysis. Nonetheless, careful inspection is essential because misidentification often occurs between microplastics and marine minerals like shell fragments or coal ash (Eriksen et al. 2013; Wang et al. 2017).

Sample Preparation and Observation The most important requirement for any imaging technique is to produce a sample as representative as possible of the whole specimen. Thus, all the steps carried out during the process need to be carefully addressed in order to preserve the material original features. However, sample preparation in microscopy always depends on the observation purpose as well as on some prior knowledge of the material. Sample preparation for observation under the optical microscope usually starts by choosing the size of the sample. It needs to be representative of the whole specimen and large enough so there is high probability of observing fluctuations on the microstructure features. All samples constantly must be carefully handled, and the use of gloves and suitable tweezers is an intrinsic requirement. The surface of micro-/nanoplastics needs to be handled the minimum in order to preserve possible adsorbed compounds and to avoid introduction of other contaminants. Thus, the tweezers need to be pre-cleaned and present a surface free of any marks that might induce strains or be imprinted at the specimen surface. It is advisable to simply mount the sample for quick inspection under the microscope to first verify if specimen cleaning is required prior to observation. The latter may be necessary since microplastics often are heavily coated with biological material. The best cleaning procedure is distilled water rinsing or, if necessary, careful washing with distilled water in an ultrasonic bath. One should keep in mind that there are watersensitive plastics and that ultrasonic cleaning may induce damages by excessive cavitation (ASTM E2015-04 2014). Other solvents should be avoided because microplastics are mostly polymeric materials and organic solvents will alter the surface of the sample. Mounting the sample should be as simple as possible in order to preserve the as-collected surface and its features during observation, particularly if optical microscopy is used as a pre-screening tool for further examination using SEM. Thus, careful placing of the dried specimen onto a clean glass/quartz petri dish or slide is the best option for direct observation under the objective of the optical microscope. There are other methods of mounting the sample including castable resins or compression mounting. Extreme caution must be taken when adopting these mounting methods since chemical reaction(s) between the specimen and the

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resin may take place and compression is only suitable for high-temperature engineering plastics. Additional preparation steps prior to specimen mounting might be required such as specimen sectioning, grinding, and polishing. The American Society for Testing and Materials (ASTM) authors a standard guide covering recommended procedures for the preparation of polymeric and plastic specimens to be examined by light and electron microscopy, particularly for urethanes, polymethyl methacrylate and polycarbonates, polyimide films or sheets, and polyester thick films or sheets (ASTM E2015-04 2014). Fluorescence tagging is an additional sample preparation step that has been a valuable assistance in screening and sorting microplastics under the optical microscope (Karakolis et al. 2019). Nevertheless, one should keep in mind that many primary plastics include chemical additives like flame retardants, plasticizers, or dyes (Rochman 2015). Thus, dyes and coloring agents can create an additional problem during sample observation. The main limitation of the optical microscope is its spatial resolution which, in its turn, becomes critical in the analysis of micro-/nanoplastics. Spatial resolution and possible misleading imaging interpretation have been overcome with the invention of electron microscopy, generally scanning electron microscopy (SEM). SEM allied with energy dispersive X-ray spectroscopy (EDS) is an advanced imaging and analytical system that readily handles the urgent need for precise characterization of such pollutants as well as other toxic substances that may be adsorbed at the surface of microplastics.

Electron Microscopy In optical microscopy, the extent of identifiable particles is restricted to the technique spatial resolution. The limit is drawn when submicron particles are within the visible light wavelength (400–700 nm). In contrast, electron microscopy (EM) overcomes the problem, enabling accurate size distribution and morphology evaluation of such undetected microparticles. Although the two techniques are used for very different purposes, they may complement each other as essential tools in the analysis of microplastics. Moreover, electron microscopy is a powerful imaging and analytical technique able to cope with the urgency of microplastic characterization becoming a key technique in such assessment.

Scanning Electron Microscopy The main limitation in optical microscopy is the loss of resolution at high magnifications. This has been overcome by electron microscopy (EM), presently with wide application in materials and life sciences. Bearing in mind that light radiation has a wavelength of 400–700 nm, the illumination source of electrons has a wavelength between 0.01 and 0.001 nm. Consequently, the highly energetic electron beam

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enables a theoretical resolution of 0.02 nm for 100 kV electrons. In scanning electron microscopy (SEM), the highly energetic electron beam is focused by electromagnetic lenses and scans the specimen in a raster scan pattern (Goodhew and Humphreys 2000; Reimer 2013; Egerton 2005). Figure 3 illustrates a diagram showing the SEM microscope and its basic electron beam pathway. The electron beam interacts with the specimen and undergoes inelastic and elastic scattering though part of the electron beam is unscattered. In elastic scattering, the direction of the primary electrons is changed, but their overall energy is kept. Inelastically scattered electrons lose part of their energy and change direction. The interaction between the electron beam and the sample, also known as the interaction volume, results in different effects and subsequent signals. Most of the electron beam energy ends up in the specimen as heat, while other events take place and are detected outside the specimen such as emission of secondary electrons, backscattered electrons, or characteristic X-rays (Goodhew and Humphreys 2000; Reimer 2013; Egerton 2005). Secondary electrons are the most used imaging signal in SEM since each primary or incident electrons produce several secondary electrons. Their emission takes place when part of the electron beam energy is transferred to the atoms of the specimen and abandons the sample with very small energy. Another imaging signal

Fig. 3 Illustrative diagram showing the SEM and its basic electron beam pathway

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used in SEM are backscattered electrons which result from collisions between the electron beam and the atoms of the specimen. The latter leave the sample losing part of their energy and scatter “backward” 180
relatively to the incident electron beam. In backscattered electron imaging mode, the signal varies directly with the atomic number of the chemical elements composing the sample since the higher the atomic number, the brighter will be that region. In addition, more secondary electrons can be generated when some of the backscattered electrons exit the specimen. X-ray emission is particularly critical for analytical purposes and results from de-energization of the atoms after production of secondary electrons. SEM imaging is delivered by emission detection of secondary electrons (morphology) or backscattered electrons (BSE) (atomic number), while qualitative and quantitative analytical analysis is given by X-ray emission (energy dispersive X-ray spectroscopy – EDS) (Goodhew and Humphreys 2000; Reimer 2013; Egerton 2005). The region of penetration by the electron beam, the three-dimensional interaction volume, and the subsequent signal emission are the key factors in SEM and defined by the electron beam energy, sample tilting, chemical composition, or specimen preparation (Goodhew and Humphreys 2000; Reimer 2013; Egerton 2005). Samples which are highly sensitive to the electron beam like biological samples or synthetic organic polymers can be more easily observed using a low-voltage microscope or the environmental SEM (ESEM). In the first case, imaging is carried out down to a few tens of volts, reducing charge accumulation and providing high resolution to some extension, although EDS analysis may be slightly compromised (Goodhew and Humphreys 2000; Reimer 1993, 2013). ESEM is mainly the conventional SEM operated in the range of low pressures to, at least, the pressure at which liquid distilled water is observable. It enables imaging of nonconductive samples since accumulated electrical charge accumulation or electrons from the beam itself are scattered by collision with the gas molecules inside the microscope chamber (Goodhew and Humphreys 2000; Kuo 2007; Stokes 2008; Johnson 1996). SEM overcame the limitations of optical microscopy providing crucial information on the morphology, topography, composition, and crystallographic nature of the analyzed specimens. Figure 4 illustrates an exceptional example of SEM imaging showing the microstructure fine details of microplastics if compared to those given by the related optical microscopy images (Pac¸o et al. 2017). As previously stated, SEM enables better and more accurate assessment of microplastics than optical microscopy especially for submicron particles within the visible light wavelength range between 400 and 700 nm. Figure 5 shows SEM images of different morphologies and size ranges for microplastics observed in seawater in a certain region in the Southern Mediterranean Sea (Chouchene et al. 2019). Combination of EDS elemental qualitative/quantitative analysis with SEM imaging is currently a dominant characterization technique in materials and biological sciences. For example, application of SEM/EDS enabled the identification of microshell pieces in ocean fish stomachs, confirming that caution is required in examinations that rely on visual methods alone (Wagner et al. 2017). Other examples of SEM/EDS inspection proved that ingested microplastics in biological samples are

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Fig. 4 Optical (a, c) and correlated SEM (b, d) images showing examples of polyethylene microplastics before and after exposure to the maritime fungus Zalerion maritimum (Pac¸o et al. 2017)

not affected by an extraction method using the digestive enzyme trypsin (CourteneJones et al. 2017) and that deposition and mobilization of traffic-related abrasion particles also take place on surface waters (Sommer et al. 2018). SEM effective application was recently proposed as an advanced imaging and analytical method for the determination of textile fibers in effluents (Haap et al. 2019). The identification of life presence associated with plastic debris such as pennate diatoms, bryozoans, and bacteria was carried out using SEM (De Tender et al. 2017). SEM is a powerful technique enabling accurate determination of the micro-/ nanoplastic particle size distribution, morphology, and chemical composition when associated with EDS. Furthermore, SEM imaging has also been used in the assessment of the microplastic surface conditions which provides important information on the degradation process of such pollutants. Weakened and damaged surfaces due to aging or oxidative and mechanical weathering often present clear evidence of roughness, porosity, and fractures/cracks. Still, SEM observation of micro-/ nanoplastics must be carried out with extreme caution since electron beam damage may occur and induce degradation features on the sample surface.

Fig. 5 SEM images showing examples of several microplastics with different morphologies and sizes (a–c) correspond to fragment surface, (d, e) to fiber surface, (f, g) to foam surface, (h, i) to tube surface, and (j, k) to granule surface (Chouchene et al. 2019)

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Energy Dispersive X-Ray Spectroscopy In the case of electron microscopy, X-rays are highly energetic photons emitted when the incident accelerated electron beam induces electronic transitions within the atoms of the targeted sample. These transitions are characteristic of each chemical element and detected by EDS. Normally, the incident electron beam knocks out an electron from the K-shell (n ¼ 1 shell) of the element, causing a vacancy or hole in that shell which is then filled by an electron from another shell with X-ray emission. The electronic transitions taking place to the K-shell (n ¼ 1) are KX-rays, those to the L-shell (n ¼ 2) are LX-rays, and to the M-shell (n ¼ 3) are MX-rays. The amount of X-ray signal is defined by their energy as well as the average atomic weight of the specimens. For instance, X-rays such as carbon Kα are simply absorbed by the sample, and only a few are detected. The quality of the EDS spectra is highly dependent on the interaction volume and that from which X-rays are generated. Spatial resolution in X-ray microanalysis is equally important since the higher it is, the smaller is the analyzed volume and, consequently, the smaller is the signal intensity greatly interfering with the detection limit for a certain chemical element. EDS spectra provide both qualitative and quantitative information with elemental identification and their amount determination (Goodhew and Humphreys 2000; Bell and Garratt-Reed 2003; Reimer 2013). For example, chlorinated microplastics are easily identified by EDS analysis, especially if associated with BSE imaging (Wang et al. 2017). Although plastics are relatively inert materials, they have become natural physical hosts for transport and release of toxins and surface adsorption of many pollutants like persistent organic pollutants (POPs: polyaromatic hydrocarbons, organochloride pesticides, or polychlorinated biphenyls) (Diepens and Koelmans 2018; Rios Mendoza and Jones 2015; Teuten et al. 2009; Verla et al. 2019; Wang et al. 2018). Heavy metals such as Pb, Zn, Mn, Fe, Cu, Ag, or Al have also been found adsorbed and concentrated at the surface of microplastics (Brennecke et al. 2016; Gao et al. 2019; Munier and Bendell 2018; Rochman et al. 2014; Holmes et al. 2012, 2014; Turner 2016). Association of such pollutants is aggravated by weathering effects since increasing the surface area and porosity of the microplastics creates further intrusion spots and adsorption, with expected bioaccumulation consequences (Bradney et al. 2019). Thus, EDS analysis plays by far an important role toward the identification of such elements which, in their turn, may also give fair indications on the microplastic age and origin (Ashton et al. 2010). EDS analysis of microplastics mainly provides a qualitative spectrum with elemental signals from carbon and oxygen which are the core elements present in most polymeric materials. This is probably the main reason for which EDS is hardly ever applied in microplastic studies where SEM has also been used. Alternatively, the convenience of SEM/EDS has been demonstrated on the identification of PVC microparticles found in fish guts through the strong chlorine peak present in the obtained spectra (Wang et al. 2017). Nonetheless, EDS analysis is essential to verify possible metal adsorption at the microplastic surface. Figure 6 gives an excellent example of effective application of EDS analysis to assess adsorption of iron and

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Fig. 6 SEM images and corresponding EDS spectra of virgin LDPE exposed to H2O2/Fe (a, c) and weathered PP exposed to KOH (b, d) (Prata et al. 2019)

other salts at the surface of low-density polyethylene (LDPE) and weathering of polypropylene (PP) (Prata et al. 2019). It is strongly believed that it should become universally adopted in nano-/ microplastic characterization especially since most of SEM microscopes are equipped with EDS analyzers. In fact, there are only a few studies where EDS was effectively applied on the identification of adsorbed metals at the surface of microplastics. For example, SEM/EDS was crucial to identify for the first time the presence of TiO2 nanoparticles in marine microplastics, demonstrating the ability of plastics to act as a source of transport and release of such nanoparticles into the oceans (Fries et al. 2013). Freshwater river sediments in close proximity to the marine environment were also assessed by SEM/EDS in terms of microplastic concentration and composition (Blair et al. 2019). Another recent study on the distribution and characteristics of microplastics in sediments of a lake in China showed that microplastic weathering easily provides conditions for adsorption of several chemical elements and compounds like calcium, aluminum, or silica (Liu et al. 2019). In a study regarding an efficient digestion protocol for removing organic matter without damaging microplastic samples, the morphological characterization and evaluation of the materials deposited at the surface of microplastics were carried out using SEM/EDS (Prata et al. 2019). SEM/EDS is also the most convenient analytical technique to adopt for elemental identification of particles present in microplastics. For instance, if compared to other analytical techniques such as X-ray fluorescence spectroscopy (XRF), SEM/EDS

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resolves most problems of peak overlapping, for example, Kα for As and Lα for Pb (Turner 2016). Compared to other time-consuming analytical techniques that require careful, multiple-step sample preparation and/or derivatization like flame atomic absorption spectrometry (FAA), chromatographic techniques, or inductively coupled plasma mass spectrometry (ICP-MS), SEM/EDS enables simple and simultaneous elemental identification within a few minutes’ time (Brennecke et al. 2016; Sarzanini 2000; Akhbarizadeh et al. 2017). Therefore, SEM/EDS analysis is the most convenient technique toward fast and direct identification of such metals or nanoparticles adsorbed at large surface areas of microplastics or even if entrapped inside them. Finally, analytical interpretation of SEM/EDS spectra must be carried out very thoroughly since quantitative information is only accurate for flat-polished samples or thin films with irrelevant topography. Consequently, most of SEM/EDS analysis of microplastics is merely qualitative which is already quite valuable in the characterization of microplastics.

Sample Preparation and Observation Sample preparation for SEM/EDS is critical since it is highly sensitive, and introduction of artifacts must be avoided. A careful inspection and description for sample preparation and observation of microplastics using SEM/EDS has been described elsewhere (Rocha-Santos and Duarte 2017). Basically, SEM/EDS is sensitive enough, and sample derivatization is avoided as well as the introduction of artifacts in the specimen. As previously pointed out, sample preparation is a vital step for successful and precise microscopy imaging and analysis. Nonconductive samples such as polymers and microplastics require an electrically conductive surface deposition, with a thin film of a conductive material like carbon (high vacuum evaporation) or gold and alloyed gold/palladium (plasma sputter coater). In high-vacuum evaporation, the conductive material is heated up to its vaporization temperature by application of an electrical discharge, and the evaporated atoms are deposited onto the sample surface. In the plasma sputter coater, the cathode is the metallic source which is bombarded with heavy gas atoms causing the ejection of the target atoms by the ionized gas. The sample is placed opposite on top of the anode and metallic atoms across the magnetron-confined plasma toward the sample and coating its surface, under low vacuum. The latter deposition technique is a good alternative if carbon is an element of interest that requires identification and/or semiquantitative analysis. These methods enable better imaging and avoid most of the damage caused by the highly energetic electron beam. The thickness of the conductive thin film should be around 10 nm, depending on the required conductivity and the sample nature. The conductive film coating should not be too thick because the fine details can be masked or not be easily distinguished and imaged. Conversely, it should also not be too thin since it will enable sample damage by beam heating, radiation damage, or specimen volatility. In a conventional SEM microscope, conductive coating avoids excess of electrons building up on the specimen and enables grounding of the surplus of electrons (Goodhew and Humphreys 2000; Echlin 2011; Kuo

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Fig. 7 SEM images showing examples of (a) deficient conductive coating, (b) electron charge building up, and (c) both effects at the surface of microplastics

2007). Figure 7 depicts some examples of microplastics with deficient conductive carbon coating or electron charging of the specimen providing low quality and drifting on the obtained images. Ultimately, beam damage of the sample takes place compromising the quality of imaging and analytical analysis. Furthermore, the microscope settings and operation mode are equally important in microplastic analysis since chemical bond breaking, mass loss, or volatile material formation greatly contribute to electron beam damage, with subsequent misleading results. The final images and analytical analysis are greatly influenced by the operation mode and the equipment settings adopted by the microscope operator. Ideally, the operator should bear in mind that microplastics are generally polymeric materials easily damaged by thermal effects and ionization radiation exposure and those effects need to be as much as possible minimized. Fundamentally, one should keep in mind that the electron beam acceleration voltage, lenses apertures, and consequent probe current or working distance are a few

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parameters that surely influence the quality and reliability of the SEM/EDS results and must be carefully selected by the microscope operator (Rocha-Santos and Duarte 2017). The ASTM standard offers a general guide for sample preparation of several polymeric and plastic specimens to be examined by light and electron microscopy (ASTM E2015-04 2014). Nevertheless, the sample that retains its original features as much as possible during the least invasive process of preparation is always the best policy (Goodhew and Humphreys 2000; Bell and Garratt-Reed 2003; Echlin 2011; Kuo 2007). EDS analysis immediately provides qualitative information on the elemental composition of a specimen. In contrast, quantitative analysis requires supplementary considerations and implicates prior and accurate specimen preparation as well as some caution while operating the microscope. A more detailed sample preparation process for SEM imaging and EDS analysis of microplastics, with additional indications on the SEM microscope operation method, has been described elsewhere (Rocha-Santos and Duarte 2017).

Vibrational Spectroscopic Imaging Vibrational spectroscopy essentially enables structural information on most organic compounds in the near- (NIR) and mid-infrared (MIR) range. Matter interacts with infrared (IR) radiation (12000-20 cm1) triggering molecular vibrations with subsequent absorption bands. The chemical bond strength, atomic composition of the molecules, and chemical environment define the frequency and intensity of such absorption bands. IR spectroscopy, especially Raman scattering and Fourier transform infrared (FTIR) spectroscopies, provides unique spectral fingerprints of the specimens with wide application as qualitative analytical tools for the identification and characterization of polymeric materials and plastics (Araujo et al. 2018; Käppler et al. 2016; Wrobel et al. 2017). Integration of optical microscopes onto the systems of these spectroscopic techniques for local analysis and mapping of microplastics is briefly discussed.

Micro-infrared and Raman Spectroscopy Micro-infrared and micro-Raman spectroscopies are basically defined by the coupling of an optical microscope onto the spectroscopic system and use it as the probe through which IR radiation illuminates the specimen. This combination assembles all the advantages of the optical microscopy imaging capability to accurate chemical composition determination of the analyzed microplastics (Griffiths 2009; Kazarian et al. 2009; Wessel et al. 2009). Unfortunately, numerous environmental samples contain a high number of detected particles, but spectroscopic characterization of all those particles is unreasonable, and subsampling is required prior to spectroscopic analysis. Therefore, OM is usually first used to identify particles that appear to be microplastics, followed by

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spectral accurate confirmation of its chemical composition and final comparison between the obtained spectrum and a commercial or custom-built spectral library for quick identification. Regarding sample preparation and observation under the coupled microscope, the same standards of optical microscopy should be applied. Again, the size of the sample must be representative, and specimen handling should be clean and cautious in order to avoid the introduction of artifacts. The specimen should be cleaned with distilled water prior to observation, if needed. Finally, mounting the sample must be as uncomplicated as possible onto slides or petri dishes. FTIR spectroscopic identification of chemical composition is not always straightforward or possible. As previously stated, dyes and coloring agents can become an additional problem in the visualization of the specimen. Furthermore, since these compounds also present unique spectral fingerprints, they can mask the spectrum of the underlaying material, and its interpretation may become a puzzle solving problem (Griffiths 2009; Kazarian et al. 2009; Wessel et al. 2009). Finally, quantitative analysis has not been mentioned in this section since it remains a complex method and selection of a representative calibration sample set is hardly ever a simple procedure (Griffiths 2009; Levin and Bhargava 2004; Wessel et al. 2009). The application of the analytical ability of vibrational spectroscopic imaging in microplastic identification is easily recognized in addition to the urgency of this matter which certainly demands the increase of rate for sample accurate analysis. Thus, it is expected that vibrational spectroscopic imaging further technological advancements will take place in the following years.

Final Remarks Regrettably, the oceans became the sink for all types of debris, particularly nonbiodegradable materials such as microplastics and nanoplastics (Fink 2018). Inevitably, these pollutants found their way to poison all forms of sea life and ultimately are finding their way to the top of the food chain. This only means that we are also consuming plastic in the micro- and/or nano-forms surely with serious long-term health implications. The main problem with nonbiodegradable microplastics is that they remain in the environment at the end of their life cycle. Many efforts are being carried out to tackle this problem in all sort of ways including awareness campaigns and recycling policies (Vince and Hardesty 2018). These are key points, and their dissemination is highly important to create an education toward their possible reduction. For example, an online portal for marine litter and microplastics and their implications on marine life and aquatic biota (https:// litterbase.awi.de/) has been developed in order to create as much awareness as possible. Moreover, Marine Litter Database has been created by several authors for an European beach litter database (Addamo et al. 2018). Unfortunately, these measures are not going to immediately solve the problem that lays in our hands. The fastest reduction of microplastics depends on the acquired knowledge of their distribution in the environment as well as their main sources, transport routes,

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and whereabouts. An accurate evaluation of such understanding needs to be reliable which is only attainable if sampling, measurements, and analysis methods are equally reliable. Thus, analytical methods quickly determine the microplastic particle size, distribution, and nature in a consistent manner. The combination of optical particle analysis with FTIR and Raman microscopy enables determination of the particle size and distribution as well as their chemical nature, e.g., their polymeric basis. On the other hand, SEM is critical for the analysis of much smaller particles, and EDS is a powerful analytical tool which enables qualitative information on the elemental composition of the microplastics and/or their surface-adsorbed chemical compounds. On the use of both microscopies, a procedure for microplastics using optical and electron microscopy has been proposed (Wang et al. 2017). Unfortunately, it is not always possible for scientific research on this matter to benefit from free access to all these analytical techniques, though the combination of SEM/EDS with micro-FTIR or Raman allows the most precise approach to the analysis of microplastics. In fact, only recently there have been reported works on microplastic analysis using this approach which are starting the trend on the characterization of such pollutants by applying all these analytical methods (Blair et al. 2019; Carr et al. 2016; Ding et al. 2019). Research in this matter frequently makes use of available databases for FTIR and/or Raman spectra in order to quickly identify the polymeric nature of the analyzed microplastics. Thus, creation of a public database library for microplastic optical and SEM images would also be in the best interest for all of us, and such valuable tool would further contribute to the fast and straightforward analysis of microplastics. Equally important, international standards are in the process of evaluation for possible approval on microplastics, particularly Terminology, classifications and general guidance (ISO/TC 61/SC 14/WG 1) or Characterization of plastics leaked into the environment (ISO/TC 61/SC 14/WG 4), a joint effort to standardization of microplastic analysis and accurate assessment (https://www.iso. org/committee/6578018.html). In summary, it is clearly demonstrated that the use of both imaging and spectroscopic analysis leads to full characterization of microplastics. SEM/EDS provides imaging and analytical analysis on weathering status, morphology, size distribution of microsized particles (SEM), chemical nature (chlorinated plastics), and adsorbed metals at the surface (EDS) and micro-FTIR or Raman spectroscopy on the chemical composition of the polymer and its probable origin.

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Microplastic Characterization by Infrared Spectroscopy Jun-Li Xu, Martin Hassellöv, Keping Yu, and Aoife A. Gowen

Contents Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Laboratory Pre-treatments Prior to Infrared Characterization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Introduction to Infrared Spectroscopy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Principle of Infrared Spectroscopy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Instrumentation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . From Spectroscopy to Imaging . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Infrared Spectroscopy for MP Characterization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Spectral Matching . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Multivariate Analysis for MP Characterization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Pre-selection by Manual Sorting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Spectral Imaging for MP Characterization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Automated Analysis for MP Characterization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Data Processing Example for MP Characterization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Introduction to the Dataset . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Spectral Library . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Multivariate Exploration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Mean Spectrum from Individual Object . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Spectral Matching . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Development of Classification Map . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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J.-L. Xu (*) · A. A. Gowen School of Biosystems and Food Engineering, University College Dublin, Dublin, Ireland e-mail: [email protected]; [email protected]; [email protected] M. Hassellöv Department of Marine Sciences, University of Gothenburg, Göteborg, Sweden e-mail: [email protected] K. Yu Global Information and Telecommunication Institute, Waseda University, Shinjuku, Tokyo, Japan e-mail: [email protected] © Springer Nature Switzerland AG 2022 T. Rocha-Santos et al. (eds.), Handbook of Microplastics in the Environment, https://doi.org/10.1007/978-3-030-39041-9_21

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Applications of FTIR Spectroscopy and Imaging for MP Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . Challenges and Outlooks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

A realistic risk assessment of microplastic pollution must stand on representative data on the abundance, size distribution, and chemical composition of polymers. Infrared spectroscopy is an indispensable tool for the analysis of microplastics (20 μm) using FTIR imaging. Measured

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concentrations ranged from 0 to 7 MP m
3 raw water or drinking water with an overall mean of 0.7 MP m
3. They further reported that the identified particles included polyethylene, polyamide, polyester, polyvinyl chloride, or epoxy resin. Investigation of microplastics in sediments of coastal areas including seabed and beaches is one typical analytical issue. Interestingly, the presence of MP in surficial sediments from the Arctic Central Basin was investigated by Kanhai et al. (2019). Surficial sediments from the various cores were subjected to density flotation with sodium tungstate dihydrate solution. They revealed that 7 of the 11 samples contained synthetic polymers by using FTIR. The detected plastics included polyester, polystyrene, polyacrylonitrile, polypropylene, polyvinyl chloride, and polyamide. With the increased focus on microplastic debris, several groups have studied the influence of microplastic uptake by different organisms. At initial stage, mainly marine invertebrates, but later also vertebrates, were analyzed (Ivleva et al. 2017). MP ingestion was found in a variety of farmed aquaculture species, such as silver carp (Jabeen et al. 2017), oysters (Phuong et al. 2018), tuna (Markic et al. 2018), and mussel (Qu et al. 2018). The abundance of microplastics was lately identified in the stomach contents of three small pelagic species of the Central zone of the Atlantic: Scomber spp., Trachurus trachurus, and Sardina pilchardus (Maaghloud et al. 2020). They examined a total of 251 individuals, and FTIR spectra were compared to a reference spectral library. The results showed the presence of three polymers, polyamide, acrylic, and polystyrene, in 26% of the individuals studied. Polymers were found accumulated in Atlantic horse mackerel (Trachurus trachurus) with 30%, then in mackerels (Scomber spp.) with 27%, and in European pilchardus (Sardina pilchardus) (9%).

Challenges and Outlooks Despite its wide use, however, many limitations and challenges in application of FTIR for MP analysis remain. As stated above, FTIR spectra collected from different modes (e.g., transmission versus ATR) are inherently different. Unfortunately, these differences have not attracted adequate attention when comparing the unknown spectra to literature or matching with spectral library. In addition to this, spectral changes during sample preparation, chemical weathering, natural aging, and biochemical processes, which all have the potential to modify spectral features, are constantly overlooked. Environmental exposure leads to polymer aging and mechanical and oxidative weathering of the plastic surface. Weathering-related changes in infrared spectra have been reported from previous research: hydroxyl groups (broad peaks from 3100 to 3700 cm
1, centered at 3300–3400 cm
1), alkenes or carbon double bonds (1600–1680 cm
1), and carbonyls (1690–1810 cm
1, centered at 1715 cm
1) (Rajakumar et al. 2009; Brandon et al. 2016; Karlsson et al. 2018b). However, most studies on MP identification ignored the spectral change caused by plastic degradation when comparing or matching with the reference spectral library. A time-consuming cleaning procedure, e.g., density separation and purification, is a common solution to extract particles from complex environmental matrices.

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However, it implies an artificial change of sample composition with a risk of losing important information or even damaging microplastic particles. For instance, H2O2 is usually applied to remove organic matter. While many polymers have been shown to resist degradation associated with H2O2, little is known about the influence of chemical treatments on weathered plastics. In order to enable automation, the sample is chemically or enzymatically purified and subsequently concentrated onto filters. A desirable substrate should have the minimum spectral interference and can immobile the particles especially for imaging where the stage moves during scanning. For transmission configuration, the substrate should allow the light to penetrate through particles. The importance of appropriate substrate material for obtaining high-quality results with minimum spectroscopic interference in the FTIR spectra has been stressed by Vianello et al. (2013). Good sample substrates for FTIR should produce low background signals, hold particles in place, have a reasonable pore size, and be as cost-effective as possible. Silicon filter substrate with pore size of 10 μm was recommended by Käppler et al. (2016) using transmission FTIR for MP analysis due to the following advantages. It offers good mechanical stability and enables filtration of aqueous samples due to its well-defined holes. Silicon filter substrate also guarantees sufficient transparency for the broad mid-infrared region of 4000–600 cm
1, and its own vibration bands do not disturb the polymer spectra. On the other hand, Löder et al. (2015) tested different commercially available filter substrates and recommended an aluminum oxide membrane filter (Anodisc, Whatman) for transmission FTIR imaging of environmental MP samples. However, the researchers (Löder et al. 2015) also pointed out this filter material is usable only in a limited spectral range from 3800 to 1250 cm
1. Due to the self-absorption of the Anodisc filter in the mid-infrared fingerprint range (1400–600 cm
1), a distinct identification of potential MP particles and an accurate classification of the polymer type are strongly restricted or even not possible in some cases (Käppler et al. 2015). Moreover, the aluminum oxide filter shows a relative high fragility, which hampers excessive handling. Given that various substrates are used in different experiments, it is important to test the suitability of the selected substrate and any spectral interference that might occur. The use of library matching software also raises some concerns for MP analysis. It aims at comparing the spectrum of the particle with that of custom-made and/or commercial libraries. So many different commercial libraries from different vendors are used for MP analysis, severely hampering the comparability between different studies. More importantly, the likelihood of successful matching greatly depends on the comprehensiveness of the spectral library and the robustness of the matching algorithm. There is no single commercial library broad enough to assure extensive success rates (Araujo et al. 2018). Worse still, most of commercial and custom-made libraries only include spectra from plastics that were not exposed to environmental degradation. In fact, the same plastic can give varied spectral features depending on its molecular structure and conformational characteristics: for example, crystalline and amorphous polyethylene materials show different spectral features. As mentioned earlier, the same type of plastic will present spectral changes after exhibiting interactions with the surrounding marine environment during fragmentation and

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chemical reagents used in purification step. In this context, there requires more research on spectral changes at time scales of degradation in environment and purification in laboratory and more work to build a spectral library specifically tailored to microplastic analysis by collecting plastic spectra at different conditions (e.g., density, color, aging, environment). Spectral pre-processing, chemometric, and machine learning techniques have been mostly neglected for MP analysis. Xu et al. (2019) reported that only 2 studies out of 20 investigations have applied chemometric and pre-treatment methods. Instrumental response functions and sample presentation can significantly impact on the quality of the data gathered. Particles can give rise to a number of artifacts which can distort and greatly reduce the accuracy of a spectral measurement. In fact, different plastics with varying shapes, sizes, and colors might exist in the same collected environmental sample, making it necessary to apply local spatial correction during spectral pre-processing. Database search algorithms are commonly used to make a comparison between the unknown spectrum and each spectrum in the reference database. Various algorithms, e.g., Euclidean distance and Pearson correlation, can be used to create a hit quality index, which is a measure of how well the query spectrum compares against each reference spectrum. While database searches can be considered to be pioneering methods in this field, future routine analyses will require faster and more accurate approaches as the throughput demand will certainly rise. It is anticipated that model-based classification has the potential to be a good alternative to automatically identify each pixel spectrum without any human intervention. Hierarchical classification strategy, which involves hierarchically organizing the classes, creating a tree of categories, and exploiting the information on relationships among them, might be a good tool for microplastic identification in the future due to the inherent hierarchical structure in microplastic identification. Lehtiniemi et al. (2018) reported that MP particle size affected MP uptake of aquatic animals; therefore, Uurasjärvi et al. (2020) suggested that particle sizes, numbers, and masses per sample should all be necessary to report in future studies. In this sense, we need to point out the importance of size fractionation using sieves or filters with different pore sizes prior to spectroscopic analysis. The standardized application of size fractionation enables an inter-comparison between different studies. Additionally, scanning the entire sample area with particles of similar size is more likely to obtain better spectral signal during automated analysis using the same setting. Size separation of MPs into fractions of 1–5 mm and 20 μm–1 mm was suggested by Directive (2013) for EU monitoring purposes. A purification step prior to sieving is suggested when large amounts of biological matrix (e.g., gut contents and tissue) clog the sieve. We also highly recommend the computation of MP-to-non-MP ratio for each sample as a result from automated analysis. This ratio will strongly depend on the sample matrix and the preparation procedure. It could be used to compare different preparation procedures and scanning parameters, e.g., laser source and acquisition time. Finding out this ratio could also help improve toxicological studies as environmental MP concentrations have yet to be determined (Anger et al. 2018). MP characterization results are commonly presented using units which are mass or number of MP per square or cubic meter (g m
2, g m
3, MP m
2, MP m
3). Therefore, it is

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highly recommended to declare the reference unit to ensure comparability. It is important to notice that units based on the number of particles are not comprehensive since there are significant differences in sizes of microplastics; therefore, standardized size categories or even better size distributions for each polymer category should be reported for consistency.

Conclusions FTIR is recognized as a promising tool for MP analysis in environmental samples. The development of methods to automatically determine the FTIR spectra of microplastics is desired; however, numerous analytical challenges hampered the automation procedure. Therefore, more research devoted to methodology development should be encouraged in the future. It is crucial to develop, validate, and improve automated analysis methods to reduce the identification time and enhance accuracy and robustness of the complete analytical chain. The development of an efficient and effective method for identification of MP will improve the current understanding of the presence, persistence, and consequences of MP in the environment and contribute to a realistic, comparable, and reliable risk assessment of MP.

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Microplastics Characterization by Raman Microscopy Barbara E. Oßmann

Contents Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . An Indian Scientist, the Light and Small Plastic Particles . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Theoretical Aspects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Raman Microscopy and Microplastics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Sample Preparation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Choice of Filter Material/Substrate . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Raman Measurement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Outlook . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

Identification and quantification of microplastics in the environment is increasingly important. With decreasing particle size, microplastic numbers and therewith the number of species potentially affected by microplastics rise. However, data on the occurrence of small microplastics (500 μm), probably the easiest method is to use the naked eye, which can be assisted with light microscopy to reach also smaller particles (>100 μm). However, even if these methods are supported by staining, which can lower the detection limit (25 mm, De Tender et al. 2015), which are much easier to capture than MPs. Studies on microscopic fragments from sediments are still currently limited since separation of plastics will entail the use of wet peroxide oxidation (WPO) and density separation (GESAMP 2019), which can both damage the biofilm and destroy the structure. Thus, common methods for MP separation from sediments cannot be applied if one aims to study the biofilm communities, an issue that still necessitates development of new techniques and methods.

Preservation After in situ collection, plastic samples must be carefully preserved for downstream processing and analyses. In contrast to MP quantification work where samples are just usually kept in dry containers (i.e., vials or glass bottles; GESAMP 2019), preservation of samples is crucial for microbial community investigation since the biofilm must be kept intact and preserved. Because laboratory facilities are not readily available in remote areas during sampling or while on field, the samples are needed to be pre-treated first before being stored for transportation. Change in

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temperature during extended storage and their possible exposure to oxygen and light may alter the microbial community composition and affect the results (Malik et al. 2008). Therefore, effective preservation of MP samples for later processing is critical. However, to date, protocols for the preservation of microbial community DNA particularly for microplastics have not been standardized, most of which have also been just adopted from microbial ecological and related studies. Preservation methods differ depending on the type of analysis (i.e., visual or molecular) that will be performed afterwards. Visualization through SEM or fluorescence microscopy requires prior sample preparation which begins with fixation, commonly with clear aldehydes. This avoids introduction of dyes and colored materials that may later interfere with imaging. Taking this into account, after identifying and separating plastic samples, they are immediately fixed in situ in an aldehyde solution, such as formaldehyde/formalin (Carson et al. 2013; Bryant et al. 2016; Harrison et al. 2014), glutaraldehyde (Reisser et al. 2014), or paraformaldehyde (Zettler et al. 2013; Schlundt et al. 2020), before the samples are frozen or kept in cold storage. According to Carson et al. (2013), preserving samples in formalin (or derivatives) precludes molecular techniques, so a different preservation method must be used. Studies that combine visual and molecular approaches usually divide their collected MP particles into two groups and use the appropriate preservation method for each. Dividing a fragment for visualization and DNA work is possible for large debris, making it directly comparable. However, it is extremely difficult and, in some cases, almost impossible for MPs, raising questions on the comparability of results of these methods when used at different samples. This makes plastisphere studies in MPs more challenging. For molecular analysis, it is especially important to preserve the samples effectively to prevent contamination and keep the DNA intact. Cold storage (4 °C) or freezing at
20 °C and
80 °C have been the commonly used preservation method for samples collected for DNA analyses (e.g., Bryant et al. 2016; Harrison et al. 2014; Oberbeckmann et al. 2014). Others add a lysis buffer or DNA/RNA fixative before storing at low temperatures (Debroas et al. 2017; Zettler et al. 2013). Successful DNA extractions have been reported in all these methods, but each preservation approach may also introduce variability. The key then is to be consistent in the use of the methods to make different samplings directly comparable, especially in cases of periodic monitoring, spatial survey, or time-series experiments. Although previously used preservation methods have been successful, De Tender et al. (2017) recommends storing the samples in a lysis buffer at
20 °C since it yielded the highest DNA concentration after extraction. Using the same condition across studies could yield more comparability. However, the use of one standardized method has been a long dilemma in the field of microbiology and a topic of great discussions.

Imaging and Visualization Early studies of the plastisphere were mostly visual identification and imaging, looking at the presence and structure of the biofilms. Although imaging studies

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were limited in taxonomic resolution for species identification especially for bacteria, novel insights were still generated. Imaging allows closer inspection of the biofilm structure at the three-dimensional scale, providing insights on possible interactions, spatial distribution, and mechanisms for attachment, which may not be readily available using other techniques. Details of the biofilm structure, topography, and the surface supporting them are also important in understanding the mechanisms underlying biofilm formation and their attachment (Abed et al. 2012). Popular microscopy tools for the examination of biofilms include light microscopy, scanning electron microscopy (SEM), transmission electron microscopy (TEM), confocal laser scanning microscopy (CLSM), and other fluorescence in situ hybridization (FISH)-based techniques. However, those that have been used in plastisphere studies are, to our knowledge, limited to SEM and modified FISH-based microscopy techniques, namely catalyzed reporter deposition (CARD) and combinatorial labeling and spectral imaging (CLASI).

Scanning Electron Microscopy (SEM) The scanning electron microscope (SEM) has been used as early as 1975 to examine the presence of microbes in plastic surfaces (Sieburth 1975 as cited in De Tender et al. 2017). The images produced during that time revealed that pennate diatoms, filamentous and coccoid bacteria, and bryozoans that colonized were abundant in the surface of the plastics. SEM is an extremely convenient tool in characterizing the surface features of plastics because of its extremely high resolution of visualization (Abed et al. 2012). Even in recent studies, SEM seems to have become the gold standard in providing the visual evidence for the presence of either the plastisphere or certain organisms within (Carson et al. 2013; Zettler et al. 2013). This technique provides information about the morphology and spatial structure of the biofilm and detection of the microstructures within that may be important for microbial interactions (Abed et al. 2012). Another advantage of SEM in studying the plastisphere is its capability to not only visualize the biofilm community but also the surface characteristics of the substrate. This is valuable information since studies have shown the influence of surface topography and roughness on the settlement and adhesion of microbes to plastics surfaces (Abed et al. 2012). Close inspection may reveal ultrastructures that might be responsible or crucial for plastisphere establishment and would have significant implications in drawing insights on the ecology of such associations. SEM has also become the standard method used to demonstrate possible erosion or changes in the surface, such as detection of pits and grooves that may be attributed to bacterial biodegradation (Surman et al. 1996). These pits were observed to closely conform to the shape of the contained cells, which may suggest occurrence of biodegradation (Zettler et al. 2013). SEM also revealed subtle changes over time in plastic surface structure after incubation with potential biodegrading bacteria from different environments (Dela Torre et al. 2018). Although much valuable information may be extracted from SEM, the use of this technique also presents many challenges. SEM is very costly, and preparation of specimens is labor intensive especially for traditional electron microscopes. Samples must first undergo a series of preparation steps which includes fixation with

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aldehydes and osmium tetroxide, dehydration through a series of alcohol, critical point drying, and coating with a thin layer of metal. This chemically complex multistep sample preparation has been repeatedly noted to alter some features of the microbial biofilm (Surman et al. 1996). Specifically, the series of dehydration required in the procedure can destroy or modify some of the cellular features and may cause the biofilm to shrink, resulting in loss in information or inaccurate interpretation of results (Surman et al. 1996). More importantly, the paucity of taxonomic information that can be gathered from morphological analysis alone makes it difficult to discern different groups of microbes, especially bacteria and archaea, to the species level. In addition, unlike other microscopy studies where the surface characterization can be converted to quantifiable indices, such as the PMT function in CLSM, SEM images so far in plastisphere studies have been limited to being descriptive. SEM however will still be continued to be used for plastisphere work since many of its advantages remain unparalleled.

Fluorescence In Situ Hybridization (FISH) Fluorescence in situ hybridization (FISH) compliments the lack of taxonomic resolution of SEM while preserving information on location, distribution, and attachment of plastisphere components. Whole cell FISH technique, for example, allows the simultaneous visualization and phylogenetic identification of the microbial community. In this technique, microbial cells are treated with fixatives and hybridized with fluorescent oligonucleotide probes targeting specific fragments of the ribosomal RNA or DNA. The probes hybridize with its target (e.g., 16S rRNA), which then makes the cells fluoresce when viewed using a fluorescence microscope (Zinder and Salyers 2001). Probes may be designed to include virtually all microbes from a domain (universal probes), all species in a phylum, or only a single species (Zinder and Salyers 2001). Several variations in FISH have been developed, but only two popular FISH techniques have so far been applied in the plastisphere, which will be discussed in the succeeding sections. CARD-FISH Although whole cell FISH has been hailed as a breakthrough for microbial biofilm studies, it still presents difficulties in studying environmental samples. Low levels of FISH signal may be observed in the case of microorganisms with low ribosomal content or communities that are not actively growing (Costa et al. 2017). Because of the weak fluorescent signal, this may overlook some taxa. Background noise possibly from cells or noncellular debris exhibiting autofluorescence may also be observed, complicating visualization. To solve this problem, modifications have been made to amplify the signal obtained in the standard FISH technique, one of which was the use of tyramide signal amplification (TSA), also known as the catalyzed reporter deposition (CARD) method. In this approach, oligonucleotide probes are labeled with horseradish peroxidase (HRP) that used fluorescein-tyramide as the substrate, resulting in amplified signals from the targeted cells. The study of Harrison et al. (2014) was the first to use CARD-FISH to investigate bacterial attachment to LDPE microplastics buried in coastal marine sediments for

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14 days. In their work, they used a universal bacterial oligonucleotide probe (EUB338 I–III) and counterstained the plastic samples with 40 ,6-diamidino-2phenylindole (DAPI) following hybridization to examine the distribution patterns of all microbial cells. Using this approach, they were able to demonstrate that bacteria present in sediments rapidly colonized and established a community on the LDPE surfaces. Furthermore, having identified dominant 16S rRNA gene sequences belonging to the genera Colwellia (Gammaproteobacteria) and Arcobacter (Epsilonproteobacteria) obtained from constructed clone libraries, they then used genus-specific probes PSA184 and ARC94 to detect their presence, respectively. They confirmed the direct attachment of Colwellia spp. to the LDPE MPs but were not able to visually demonstrate colonization by Arcobacter spp. due to the presence of nonspecific fluorescence signals. CLASI-FISH Another disadvantage of conventional whole cell FISH is the limited number of taxa that can be identified in a single sample, also due to limitations on the number of different fluorophores that may be used simultaneously. The use of three or more fluorophores has been reported to result in spectral overlapping during microscopic analysis of the biofilms (Costa et al. 2017). This limitation restrains the comprehensive study of the plastisphere since it is already known that it supports a complex multispecies array of microbial communities. Although, more advanced models of fluorescence or confocal laser scanning microscopes can lessen cross talks by separating spectral emissions by a few units, they could put constraints on resources as they tend to be more expensive. To overcome this problem, another innovation of the FISH method, called combinatorial labeling and spectral imaging (CLASIFISH), was developed to study the highly diverse biofilms (Valm et al. 2012). This method uses two or more probes with different associated fluorophores for each species, creating multiple combinations of colors whose spectral signatures are distinguished using fluorescence spectral imaging. With this approach, the number of microbial taxa that can be targeted and identified in a single sample can be significantly increased. CLASI-FISH may also provide spatial and taxonomic information about early-stage biofilm formation that may have low biomass, which may be challenging for amplicon sequencing (Schlundt et al. 2020). CLASI-FISH was very recently applied in plastisphere research, pioneered by Schlundt et al. (2020). In their study, the authors developed a nested probe set consisting of seven different fluorophores capable of distinguishing seven distinct bacterial types: Rhodobacteraceae; Alphaproteobacteria that were not Rhodobacteraceae; Alteromonadaceae; Vibrionaceae; Gammaproteobacteria that were not Alteromonadaceae or Vibrionaceae; Bacteroidetes; and bacteria that were not members of any of these groups. Using this nested probe set, they were able to determine the taxonomy of up to 90% of the bacteria in their environmental samples when higher taxonomic ranks (e.g., class and family) were considered. Moreover, unlike SEM, the use of CLASI-FISH enabled not just visualization of the intimate association between diatoms and bacteria but also identified the taxonomy of these associated bacteria, namely Bacteroidetes, Rhodobacteraceae, and some

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Gammaproteobacteria. Bacteria attached to eukaryotic organisms such as ciliates (Zettler et al. 2013) and bryozoans (Bryant et al. 2016) have been reported before but were unable to provide identification. Even with all these innovations in FISH techniques, several limitations are still being encountered in their application to biofilm studies. Sample preparation is time consuming, a challenge when multiple samples are considered. Thus, many studies have used this technique to present “sample” cases or evidence in representative samples rather than apply it to all samples for comparative surveys. Further, sample preparation could be destructive since the samples must be fixed with chemicals and washed several times prior to probe hybridization (Costa et al. 2017). An additional limitation of FISH techniques is that a prior molecular knowledge of the communities under investigation is necessary for the design of probes (Malik et al. 2008). In the study of Harrison et al. (2014), they first performed clone library construction and terminal-restriction fragment length polymorphism (T-RFLP) before CARDFISH to first determine the taxonomic affiliation of the microbes. CLASI-FISH, on the other hand, also requires the development of new probe/fluorophore combinations to target different taxa as broadly or finely as desired (Schlundt et al. 2020). However, the design, testing for effectiveness, and optimization of a new probe can also be time consuming and complex (Malik et al. 2008). Nevertheless, FISH still provides a convenient way to combine phylogenetic identification and in situ localization but may have limited applications in terms of research focus. Further research into the use of FISH methods should be evaluated for future applications in plastisphere research.

Molecular Methods Although most, if not all, molecular techniques used for microbiological studies are applicable to plastisphere work, several aspects are still needed to be improved or optimized, especially on the collection and preservation of materials, extraction, PCR, and DNA hybridization. Studying the biofilm has been of great challenge and difficulty even for many of the standard or optimized methods, and further optimization might be needed when applied to the plastisphere. Here, we discussed currently published approaches in extracting information from the genetic material, and the improvements that may further be done.

Extraction Retrieving information from nucleic acids extracted from environmental samples starts with an efficient extraction of high-quality genetic material with sufficient yield. DNA or RNA extraction greatly affects community profiling of the microorganisms since insufficient lysis of cells or excessive treatment leading to DNA shearing (Malik et al. 2008) may result in the underrepresentation of some taxa affecting interpretations. Several approaches including the use of commercially available extraction kits have been optimized for extracting environmental DNA or RNA from different types of media (Lear et al. 2018).

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Fig. 3 DNA extraction methods and kits and their frequency of use in published plastisphere studies

The different types of extraction techniques and the frequency of their use in plastisphere research are summarized in Fig. 3. Several studies performed conventional standard extraction techniques (e.g., CTAB, phenol-chloroform), but a greater number used commercially available DNA extraction kits, with the MoBio Powersoil (now QIAGEN ® DNeasy ® PowerSoil® kit) being the most common. Studies suggest that efficiency of each technique is dependent on the type of sample being processed. Debeljak et al. (2017) evaluated many of the DNA extraction methods typically used in identifying plastic-associated communities by comparing yield, amplification efficiency, costs, and processing time. They tested four extraction kits (i.e., Gentra Puregene Tissue kit – Qiagen, MoBio PowerSoil/DNeasy PowerSoil – Qiagen, MoBio PowerBiofilm/DNeasy PowerBiofilm – Qiagen, MPBio FastDNA – MP Biomedicals) and compared them with the standard phenol–chloroform purification using two mechanical lysis techniques (bead beating and cryogenic grinding with liquid nitrogen). All methods resulted in the successful extraction and amplification of DNA suitable for downstream applications with not much significant differences on the resulting data. However, overall, the Qiagen Puregene Tissue kit yielded the highest DNA concentrations for most sizes and amounts of plastics at relatively low cost and short processing time.

Targeted Sequencing Sequencing approaches in profiling microbial communities can be classified into targeted or nontargeted approaches. The targeted approach is based on the analysis of target regions of the genome instead of all the genetic material in each sample. In

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this approach, target genes must be carefully selected to serve as appropriate and suitable markers. In the case of taxonomic vis-à-vis phylogenetic analysis, these markers must contain both conserved and variable regions. The former enables the design of primers, which target different taxonomic groups, whereas, the latter allows differentiation and phylogenetic comparisons among microbial communities (Zimmerman et al. 2014). The small subunit rRNA gene has been used extensively as a phylogenetic marker for all domains. For studies on bacterial and archaeal community composition, the 16S rRNA gene remains the most used universal marker gene (Thijs et al. 2017). As for eukaryotes, it is the 18S rRNA gene that is typically used as a marker (Lear et al. 2018). However, these eukaryotic markers have been suggested to not provide species-level discrimination, particularly for fungi, hence the more variable internal transcribed spacer (ITS) region has been preferred in many fungal studies (Leigh et al. 2010). The sequence diversity of these genetic markers can be studied using several approaches depending on the resolution needed, throughput, and cost. These include visual genetic fingerprinting, clone library construction and analysis, or amplicon sequencing. Genetic Fingerprinting Genetic fingerprinting offers rapid, reliable, low-cost, and high-throughput measures of community composition (Leigh et al. 2010). This approach is the method of choice when the sequences present in a sample are not required but can still precisely characterize microbial communities by looking at the diversity of the possible bands (Malik et al. 2008; Zinder and Salyers 2001). This method is also useful when many samples must be processed rapidly to monitor changes in community structure in response to changes in environmental conditions (Malik et al. 2008; Païssé et al. 2010; Zinder and Salyers 2001). To date, two types of genetic fingerprinting technique have been applied to plastisphere research, namely (1) denaturing gradient gel electrophoresis (DGGE) and (2) terminal-restriction fragment length polymorphism (T-RFLP). The principle of DGGE is that amplified rRNA gene fragments are separated by gel electrophoresis containing a linearly increasing gradient of DNA denaturants (Malik et al. 2008). The denaturing agent induces the melting of the DNA and because of sequence variation, different DNA fragments will have different melting behaviors and relative mobility. One advantage of DGGE is that the bands can be excised from the gel, re-amplified, and sequenced for phylogenetic identification (Malik et al. 2008). DGGE was employed by Briand et al. (2012) to assess the development of marine biofilm communities on various surface coatings (i.e., PS, Teflon, and antifouling paints) that were immersed for 2 weeks in two French Mediterranean coastal sites. Oberbeckmann et al. (2014) also applied DGGE to study how different factors influenced microbial composition on PET bottles. They amplified regions of the 16S rRNA gene using the primer pair 341f and 534r and analyzed the PCR products using DGGE. Band patterns were then used to account for diversity and used in community clustering approaches. Their results showed that the abundance of attached microbes and biofilm structure are influenced by polymer composition,

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season, and geographical location. In addition, they excised PCR products from the DGGE gels and re-amplified for sequencing, further revealing members of the phyla Proteobacteria, Bacteroidetes, and Cyanobacteria to be abundant in the plastisphere. Although this approach can be semiquantitative as it can generate counts or numbers of possible species present, the resolution however may obscure and mask the true extent of diversity. Specifically, one band on the gel may not necessarily correspond to only one species since DNA fragments with different sequences can have the same melting point. In addition, multiple bands on the gel that represent only a single species may exist due to the presence of multiple 16S rRNA gene copies (Malik et al. 2008). Terminal restriction fragment length polymorphism (T-RFLP) is another fingerprinting technique which offers a high-resolution and reproducible approach for the rapid analysis of microbial community structure (Païssé et al. 2010). This method uses a fluorescent-labeled primer during amplification such that only the sizes of terminal restriction fragments (T-RFs) of the digested amplicon can be detected and quantified with an automated DNA sequencer (Malik et al. 2008). This has been the method of choice for many microbial ecological researches, such as those assessing the temporal and spatial changes in microbial community patterns in response to environmental perturbations (Païssé et al. 2010). The advantage of T-RFLP over DGGE, other than its ease of use and higher sensitivity, is that the use of automated detection systems and capillary electrophoresis allows higher throughput for analysis and a more objective comparison of community fingerprint patterns (Malik et al. 2008). In a 14-day laboratory microcosm experiment, Harrison et al. (2014) demonstrated that bacteria present in coastal marine sediments rapidly colonized LDPE microplastics. Using T-RFLP analysis, they further found that the structure of the bacterial assemblages on the first week of incubation significantly differed a week after. Clone Library Construction Construction of clone libraries, which allow separation of individual amplified gene fragments suitable for sequencing, is one of the most widely used methods for assessing microbial community composition and diversity (Leigh et al. 2010). Using this technique, PCR-generated amplicons are ligated into a suitable vector (plasmid or phages) and are introduced into a bacterial cell (typically Escherichia coli) either by chemical, heat shock, or electroporation (Leigh et al. 2010). Cells are then grown in plates with antibiotics that only allow growth of cells with successfully inserted gene fragments. Each clone is then isolated, purified, and grown enough for plasmid extraction. The target genes are usually re-amplified and sequenced via complete or partial Sanger sequencing (De Tender et al. 2017). Even though complete sequencing of marker genes provides for superior taxonomic/phylogenetic assignment, this approach is labor intensive and time consuming, thereby limiting the number of sequenced clones obtained from a sample (De Tender et al. 2017; Leigh et al. 2010). Cloning can also be used in tandem with genetic fingerprinting to reduce the number of clones to be processed for sequencing. For example, in one of the early

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studies on the plastisphere, Dang and Lovell (2000) constructed clone libraries from biofilms that evolved on six plastic plates coated with different polymers that had different degrees of hydrophobicity. They incubated these plastic plates a meter below the water surface of a salt marsh estuary tidal creek near Georgetown, South Carolina, for 24 and 72 h with the objective of identifying the primo-colonizers. The generated amplicons were ligated into pGemT and the hybrid vectors were used to transform E. coli to construct the clone libraries. They then screened the 16S rRNA gene clones using a genetic fingerprinting method called amplified rRNA gene restriction analysis (ARDRA) and identified a total of 136 operational taxonomic units (OTUs) from the 12 clone libraries, reflecting the high diversity of microbial assemblages that formed on plastic surfaces after only a few days. They then just selected the clones representing the 26 most common OTUs and amplified and sequenced the V3 and V5 hypervariable regions of the insert DNA. Using these approaches, they further observed that during the early stages of succession, new organisms are constantly recruited while some organisms are lost as indicated by the substantial differences in the representation of different cloned gene sequences after 24 and 72 h of incubation. Using sequencing, they even identified that the majority of these primo-colonizers were from Alphaproteobacteria, specifically affiliated with the Roseobacter subgroup of the Rhodobacter group. A follow-up study (Dang et al. 2008) replicating the methodology of Dang and Lovell (2000) on different surfaces but incubated in the waters in Wheat Island off the Qingdao coast (China) also revealed the abundance of the Alpha-, Gammaproteobacteria, and Bacteroidetes. The Alphaproteobacteria clones dominated the libraries and related OTUs exhibited obvious succession during early stages of bacterial surface colonization for all three surface types as indicated by their increased relative abundance after 72 h. Similar to the findings of Dang and Lovell (2000), they also found that the Rhodobacterales, especially Roseobacter clade members, formed the most common and dominant primo-colonizers. These studies suggest the said method may be useful in doing comparative work on plastisphere. Targeted High-Throughput Sequencing Most studies on the plastisphere have utilized high-throughput sequencing (HTS), which also accelerated our understanding of this new environment (Fig. 2). HTS allowed thousands of organisms to be detected in parallel using DNA signatures without the need for a cloning step. Although sequencing the entire rRNA gene would provide the best resolution for taxonomic identification, current sequencing technologies however are limited by the length of the gene fragments that can be sequenced (De Tender et al. 2017). In this approach, the more hypervariable sections of the marker gene (i.e., rRNA or ITS) are amplified via PCR and tagged with “barcodes,” allowing multiplexing sequencing of amplicons from several samples. The barcodes allow separation of the sequences per sample post-sequencing via bioinformatics, which are then used for ecological analyses. Amplicon sequencing is steadily gaining attention as the method of choice for plastisphere studies (Fig. 2). Zettler et al. (2013) was the first to apply HTS to study the microorganisms attached to microplastics, coining the term “plastisphere.” They provided evidence

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that PE and PP fragments collected from the North Atlantic can harbor high microbial diversity based on OTUs. Consequently, it also served as a catalyst for the exponential rate of plastisphere work. Several following studies applying HTS have also reported the same conclusions (McCormick et al. 2014; De Tender et al. 2015). Moreover, Zettler et al. (2013) confirmed that microbial communities found on these plastics were consistently distinct from communities in the surrounding water, an observation supported by succeeding reports (Amaral-Zettler et al. 2015; De Tender et al. 2015; McCormick et al. 2014). Some studies also compared the plasticassociated communities with sediment-associated communities and reported a marked difference (De Tender et al. 2015; Harrison et al. 2014). Muthukrishnan et al. (2019) also looked at microbial communities that developed on PET and PE and those in steel and wood after being submerged two meters deep at two bay locations in Muscat, Oman. They confirmed earlier studies on the influence of substrate type and their physicochemical properties on the attaching biofilm-forming communities. The use of HTS has also been instrumental in studies related to “dangerous hitchhikers,” revealing the role of plastics as a novel avenue for dispersal and transportation. Zettler et al. (2013) reported that Vibrio spp. constituted nearly 24% of the entire biofilm community on a single PP particle. De Tender et al. (2015) also detected members of the family Vibrionaceae on marine plastics collected from the Belgian North Sea. However, the short rRNA gene sequence data from HTS was not sufficient to assign Vibrio OTUs to species level (Zettler et al. 2013). Because of this limitation, Kirstein et al. (2016) conducted an enrichment experiment to isolate and identify these Vibrio spp. They confirmed the presence of cultivable Vibrio spp. on 13% of all the MP particles (PE, PP, and PS) they collected from the North and Baltic Sea and detected potentially pathogenic Vibrio parahaemolyticus strains on 12 of their collected MP particles. McCormick et al. (2014), through amplicon sequencing, also detected the presence of the family Campylobacteraceae in high abundances on MPs collected from a man-made channel with treated wastewater effluents, associated with human gastrointestinal infections. Furthermore, the detection of hydrocarbon-degrading bacteria associated with plastics also advanced because of HTS. Some of the OTUs on PE and PP microplastics that Zettler et al. (2013) identified were putative hydrocarbon degrading such as the filamentous cyanobacterium Phormidium and members of the family Hyphomonadaceae. McCormick et al. (2014) also reported that the genus Pseudomonas were dominant within the MP biofilm assemblage but was present at very low abundances in water samples and organic material. Strains of Pseudomonas are known to degrade polyvinyl alcohol (PVA) polymers and utilize it as a carbon source (McCormick et al. 2014). Thus, HTS results could be used to identify the present species and design more-focused experiments to study those organisms. Generally, although HTS has been a valuable tool in biodiversity studies, its short-read length provides lower resolution for species-level identification (De Tender et al. 2017). To compensate for its much shorter sequence length than Sanger, the approach has been to use primer pairs that target one or two hypervariable regions of the gene marker. However, experimental studies applying HTS methods on mock communities have shown that the perceived community composition may

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vary significantly depending on the choice of the variable regions. Primer bias may also lead to an uneven amplification of certain species, causing under- or overrepresentation of some taxa (Thijs et al. 2017). Moreover, because different studies have analyzed different variable regions, this may limit synthesis to provide meaningful comparisons and conclusions about the plastisphere. The choice primers or target region to obtain a more accurate profile of the community has been a longstanding debate in the field of microbial ecology. The same problem applies in the field of plastisphere research, especially since the use of HTS technology is only a recent endeavor. The variable regions of the 16S rRNA gene that have been analyzed in this field using HTS include the regions V4, V6, V3/ V4, V4/V5, and V4/V6. For the 18S rRNA gene, the V4, V7, and V9 have been the ones frequently used (Fig. 4). De Tender et al. (2017) suggested the continued use of the V6 hypervariable for studying bacterial/archaeal diversity in plastics. However, to date, the two most common regions targeted by several plastisphere studies are the V4 and the V3/V4.

Fig. 4 Amplified 16S and 18S variable regions in various plastisphere research

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In 2010, to permit comparisons of diversity across samples, the Earth Microbiome Project (EMP) proposed to assign the primer pair 515F and 806R the standard primer (Lear et al. 2018). This may explain why multiple plastisphere studies used the same primer and targeted this region. The primer pair 341F/785R targeting the V3/V4 region has also been shown in silico to produce the highest coverage of the domain bacteria (96.1%) with no obvious bias towards the majority of bacterial species when tested on soil samples (Thijs et al. 2017). Lear et al. (2018) also notes that targeting the V3/V4 region results in fewer chimeras and lower error rates but with potentially lower OTU detection. However, since microbial diversity in the marine environment continues to increase with several reports for new potential species and undescribed clades, further studies verifying the applicability of these primers might still be needed. In the case of eukaryotic diversity studies, the regions V4 and V9 of the 18S rRNA gene are currently the popular targets for HTS-based analyses (Lear et al. 2018). These regions have also been used in several plastisphere studies except for Debroas et al. (2017), which targeted V7. Bradley et al. (2016) tested the use of the V4 and V8-V9 regions on microalgal mock communities as well as eukaryotic communities from freshwater, coastal, and wastewater samples to determine which region provided the most suitable representation of eukaryotic diversity. They concluded that the V4 and V8–V9 showed overall similar community representations using their designed universal primers. However, apart from the differential resolving power of the variable regions, other limitations are associated with various PCR biases, bioinformatics pipelines, and sequencing errors, which may complicate analysis. Finally, amplicon sequencing typically only provides insight into the taxonomic composition of the microbial community and is limited for inferring ecological functions (Sharpton 2014). Nontargeted High-Throughput Sequencing Shotgun sequencing avoids the amplification step, and thus lessens biases associated with primers and PCR (Sharpton 2014). Using this approach, total genomic DNA (metagenomics) extracted from the plastics can be directly sequenced after fragmentation, generating a more holistic overview of the community genetic profile. Further, the same approach can make use of expressed RNA or transcripts (metatranscriptomics) as templates for sequencing, providing another layer of information such as inferring for activity and metabolic functions. More variable gene sequences (i.e., protein coding) can be captured and used, allowing more accurate taxonomic assignment (Ranjan et al. 2016). This method has also been successfully applied across the domains of life. Bryant et al. (2016) was the first to investigate the communities and metabolic activities of microbes in seawater and on plastic samples collected from the North Pacific Subtropical Gyre using shotgun metagenomic sequencing. They found that between 40% and 99% of the gene reads mapped back onto eukaryotic SSU rRNA, with 30–90% identified to be bryozoans. Other eukaryotic groups they observed include the multicellular Hydrozoa, Maxillopoda, and Aphragmophora. Additionally, diatoms were also present as supported by SEM images but were only 25 mm), mesoplastics (all dimensions between 5 and 25 mm), microplastics or simply MPs (0.1–5 mm), and nanoplastics or simply NPs (1–100 nm) (Alimi et al. 2018; Rios Mendoza et al. 2018). For comparison reasons, the smallest objects that can be seen by the naked eye are about 100 μm. It should be noted that there is no agreement in the scientific literature on the exact size definition of MPs and NPs. Today, microplastics have accumulated in the environment on a global scale. This issue is in the focus of scientific research because of its high ecological importance (Frere et al. 2017; Mourgkogiannis et al. 2018). The accumulation of microplastics in the marine environment has both direct and indirect harmful effects on the aquatic ecosystems (Auta et al. 2017; Ogunola and Palanisami 2016). Apart from the aquatic environments, microplastics pollution of soil and atmosphere is of great concern (Nizzetto et al. 2016; Zhang et al. 2020). Microplastics are usually divided into two categories. The plastic items which have manufactured in very small size are called primary microplastics. Secondary microplastics are those resulting from the fragmentation of larger plastic items. Generally, the majority of microplastics in the environment belong to the second category (Cole et al. 2011). In this chapter we focus on the aggregation and deposition of microplastics in the environment giving emphasis in the aquatic environments.

Degradation of Plastics A characteristic property of plastic materials is their high durability against environmental effects. Therefore plastic materials present low degradation rates. Degradation is the conversion of plastics into smaller molecules. The most usual processes

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for the degradation of synthetic polymers can be divided into the following categories (Andrady 2011; Klein et al. 2018): • Physical degradation (abrasive forces, heating/cooling, freezing/thawing, wetting/drying) • Photodegradation (usually by UV light) • Chemical degradation (oxidation or hydrolysis) • Biodegradation by organisms (bacteria, fungi, algae) A remarkable degradation process is the fragmentation of polymers into smaller items. These fragments decompose into increasingly smaller particles including nanoparticles and then may suffer several chemical transformations (Klein et al. 2018). The modeling of degradation and fragmentation and the calculation of the relative rates and the distribution of fragment sizes is a very complicated process. Many such models have developed which focus on chain scission in the polymer backbone through (Lambert and Wagner 2018): (a) random chain scission (all bonds break with equal probability) characterized by oxidative reactions (b) scission at the chain midpoint dominated by mechanical degradation (c) chain-end scission, a monomer-yielding depolymerization reaction found in thermal and photodecomposition processes (d) inhomogeneity (different bonds have different breaking probability and dispersed throughout the system) In first order, the degradation rate of microplastics of any size class j can be assumed proportional to their concentration and therefore it can be modeled through a degradation rate constant, kdegj (Besseling et al. 2017) as: dn j ¼ kdegj n j dt

ð1:1Þ

where nj is the particle number concentration of the size class j, in giga particles per m3 (109 particle m3).

Particle-Particle and Particle-Surface Interactions Particle-particle and particle-surface interactions govern the particle aggregation and deposition respectively. These interactions mainly include van der Waals and electrostatic double layer forces which are described satisfactorily by the wellknown DLVO (Derjaguin-Landau-Verwey-Overbeek) theory. DLVO theory is based on the hypothesis that Van der Waals and electrostatic double layer forces are independent of each other and thus the effect of their action when they are both present is simply the sum of the effect of the action of each force if it acted alone. DLVO theory calculates the resultant net force. The probability of two

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particles sticking together is determined by whether the net force is attractive or repulsive (Hotze et al. 2010).

Van der Waals Forces Van der Waals interactions include three types of interactions (Adair et al. 2001): Keesom interaction between permanent dipoles, Debye interaction between a permanent and an induced dipole, and London dispersion forces between instantaneously induced dipoles caused from the distortion of the electron clouds of the interacting atoms. Van der Waals forces are inversely proportional to the seventh power of the distance between the interacting particles and therefore they are short-range forces. The Van der Waals pair potential is of the form: W ðr Þ ¼ 

C r7

ð1:2Þ

where C is the interaction parameter and r the distance between the interacting particles. The Hamaker constant A is defined by the relation: A ¼ π 2 Cn1 n2

ð1:3Þ

where n1 and n2 are the concentrations of the interacting particles. The magnitude of Hamaker constant reflects the strength of the Van der Waals interaction between two particles or a particle and a surface. For spherical particles of the same radius R, the interaction energy W is given by the relation: W ðD Þ ¼ 

A121 R 12D

ð1:4Þ

where D is the distance between the interacting atoms or molecules of material 1 in the medium 2 and A121 is the associated Hamaker constant. The Hamaker constant A121 for particles of material 1 in a liquid medium 2 can be calculated from the Hamaker constants A11 and A22 for particles of material 1 and 2, respectively, in vacuum as follows: A121 ¼

pffiffiffiffiffiffiffi pffiffiffiffiffiffiffi2 A11  A22

ð1:5Þ

This is the case for the aggregation between two particles of the same material. For the case of the interaction between a particle of material 1 and a particle (or a surface) of material 3 in a medium 2 (i.e., aggregation between particles of different type or deposition), the Hamaker constant A123 can be calculated through the relation:

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Microplastics Aggregation, Deposition, and Enhancement of Contaminants. . .

A123 ¼

pffiffiffiffiffiffiffi pffiffiffiffiffiffiffi pffiffiffiffiffiffiffi pffiffiffiffiffiffiffi A33  A22  A11  A22

509

ð1:6Þ

Additionally, in Lifshitz theory, the Hamaker constant A123 can be calculated by using the frequency dependence of the dielectric function ε at normal and imaginary frequencies through the relation (Takagishi et al. 2019):

A123

1     ð e1 ðiνÞ  e2 ðiνÞ 3 e1  e2 e3  e2 3h ¼ kB T þ 4 4π e1 þ e2 e3 þ e2 e1 ðiνÞ þ e2 ðiνÞ

  e ðiνÞ  e2 ðiνÞ  3 dν e3 ðiνÞ þ e2 ðiνÞ

ν1

ð1:7Þ

where kB is the Boltzmann constant, T is the absolute temperature, h is the Plank’s constant, and ν is the frequency. The first term describes the Keesom and Debye interactions while the second term describes London dispersion forces. The Hamaker constants in vacuum for many materials can be readily found in the literature (Bergstrom 1997; Petosa et al. 2010).

Electrostatic Forces Electrostatic forces are present when two charged particles are interacting through a polar medium such as water. Electrostatic double layer forces act over distances of the order of Debye length. Typical values of the Debye length are on the order of one to a few tenths of nanometers. The first layer corresponds to charged surface and consists of ions absorbed onto the particle. The second layer (diffuse layer) is composed of ions attracted to the surface charge via the Coulomb force. For two similar charged particles, this force is repulsive and decays exponentially with the distance. The electrical potential is decreased by a factor 1/e at a distance equal to the Debye length, κ 1, or double layer thickness. Debye length is given by the relation (Adair et al. 2001): κ

1

rffiffiffiffiffiffiffiffiffiffiffiffiffiffi ee0 kB T ¼ 2e2 I

ð1:8Þ

where e is the elementary charge, ε is the relative dielectric constant of the liquid medium, ε0 is the permittivity of free space, kB is the Boltzmann constant, T is the absolute temperature, and I is the solution ionic strength. The ionic strength is defined as: I¼

1X 2 cz 2 i i i

ð1:9Þ

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D. P. Korfiatis

where ci and zi is the concentration and the valence respectively of the ions in the solution. The ionic strength determines the thickness of the electrical double layer and therefore the range of the electrostatic forces. The electrical double layer force is strongly dependent on the ionic strength while Van der Waals attraction is insensitive to the ionic strength. For high values of ionic strength the electrical double layer is compressed and the repulsive forces are decreased. Therefore, at high ionic strength aggregation and deposition are more favorable. For low values of ionic strength, repulsion forces are dominate and particles need to have high enough kinetic energy to approach one another.

Aggregation Aggregation involves the collision of two items followed by the formation of a larger particle (agglomerate). If the two items are of the same type, the process is known as homoaggregation, while if the two items are of different type the process is known as heteroaggregation. The changes in the size and shape of the particle caused by aggregation can affect significantly the transport of the particle.

Homoaggregation The rate of homoaggregation of microplastic particles in aquatic environments, according to the Smoluchowski model, can be calculated by Besseling et al. (2017): j1 dn j 1 X a K n n ¼ 2 i¼1 i,ji i,ji i dt

ji  n j

1 X

ai,j  K i,j  ni

ð1:10Þ

i¼1

where: nj is the particle number concentration of the size class j, in giga particles per m3 (109 particle m3), ai, j is the attachment efficiency of particle of size class i with particle of size class j, Ki, j is the collision frequency of particle of size class i with particle of size class j, in m3 giga particle1 s1. The attachment efficiency takes values between 0 and 1 and is defined as the ratio of successful collisions to the total collisions, or in other words as the probability of a collision leading to aggregation. If the attraction forces dominate, the attachment efficiency takes values close to 1 (diffusion-limited process). If the repulsive forces are important, the attachment efficiency takes values lower than unity (reactionlimited process) (Alimi et al. 2018). The rate of particle collisions is governed by three transport mechanisms: Brownian motion (peri-kinetic aggregation), fluid motion (ortho-kinetic aggregation), and differential settling. Accordingly, the collision frequency is given by the sum of three terms:

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Microplastics Aggregation, Deposition, and Enhancement of Contaminants. . .

K i,j ¼

511

!  2   3  3   2kB T ai þ a j 4  2πg   109 þ G ai þ a j þ ρp  ρw ai þ a j ai  a j ai a j 3μ 3 9μ

ð1:11Þ where: kB is Boltzmann’s constant, T is the absolute temperature, μ is the dynamic viscosity coefficient of the water, αi, aj is the radius of the particle of the size class i, j, respectively, G is the shear rate, g is the gravitational acceleration, ρp and ρw are the particle and water density, respectively. For nanoparticles, Brownian motion is the dominant aggregation mechanism (Petosa et al. 2010). So, in this case the first term is dominant in the above equation. For nanoparticles of nearly equal size, the collision frequency is resulted to be independent of particle size: K i,i ¼

8kB T 3μ

ð1:12Þ

This result is due to the fact that the diffusion coefficient decreases with increasing particle radius while the active collision cross section increases with increasing particle radius. So, for nanoparticles of nearly equal size these two effects eliminate each other leading to a collision frequency independent of particle size (Petosa et al. 2010). The rate of homoaggregation of microplastic particles is strongly affected by the concentration of particles. In situations where the particle concentration is very low, the homoaggregation is negligible. Also, a remarkable feature of the homoaggregation collision frequency is that for particles of different radii, the collision frequency always takes greater values than for particles of the same size.

Heteroaggregation Heteroaggregation can be described through a mathematical model similar to that used for the description of homoaggregation. The rate of change of the concentration of microplastics of size class j caused by heteroaggregation of the microplastics and other solid particles immersed in a liquid, is calculated by the relation (Quik et al. 2014; Besseling et al. 2017): m X dn j K ¼ ahet n j dt i¼1

j,SSi nSSi

ð1:13Þ

where ahet is the attachment efficiency between microplastics and other solid particles, nj is the particle number concentration of the size class j, m is the number of the considered in the model size classes of suspended solids, and nSSi the particle density of suspended solids of the i size class which have a radius of aSSi.

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The collision frequency, Kj,SSi, is given from the relation: K

j,SSi

¼

!  2 3  2 2kB T a j þ aSSi 4  þ G a j þ aSSi þ π a j þ aSSi vs,j  vs,SSi  109 a j aSSi 3μ 3

ð1:14Þ Heteroaggregation with natural colloids, clays, and other high-density suspended particles will lead to faster sedimentation of the microplastic particles that are captured in the aggregate (Besseling et al. 2017).

Deposition Deposition is the attachment of a particle to a large solid immobile surface. The solid surface is usually called substrate. Deposition as well as transport of microplastics and nanoplastics is determined from Brownian diffusion with some contributions from gravitational sedimentation (Petosa et al. 2010). For smaller particle sizes, deposition is exclusively governed by diffusion. For larger particles, the contribution from sedimentation becomes important. Therefore, under favorable conditions for aggregation, the sedimentation of aggregates must be taken into account. Particle-collector surface interactions, which are described by DLVO theory of colloidal stability, are crucial in the study of particle deposition. A parameter which is used for the quantitative description of deposition is the particle deposition efficiency ad. It is defined by the relation: ad ¼

n n0

ð1:15Þ

where n, n0 is the deposition rate under unfavorable and under favorable conditions, respectively. If repulsive interactions dominate then the particle has to overcome an energy barrier for the deposition to occur. In this case and if we ignore gravitational sedimentation the deposition rate can be calculated by the relation (Petosa et al. 2010):  1

n ¼ 4:0AS =3

D1 2ac U

2=3 

 β Sð β Þ 1þβ

where: AS ¼ porosity-dependent parameter of Happel’s model D1 ¼ diffusion coefficient in an infinite medium ac ¼ collector radius U ¼ approach velocity S() ¼ special function, introduced by Spielman and Friedlander (1974) The parameter β is calculated by the relation:

ð1:16Þ

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Microplastics Aggregation, Deposition, and Enhancement of Contaminants. . .

 1=     1 1 1 D 1 3 K F ac 1 AS  =3 β ¼ ð2Þ =3 Γ 3 3 Uac D1

513

ð1:17Þ

where Γ() is the gamma function and KF is the pseudo-first order rate constant which is given by the relation:

K F ¼ D1

8δ < ðD

:

0



VT g1 ðH Þ exp kB T



9  =1  1 dy ;

ð1:18Þ

where: δD ¼ diffusion boundary layer thickness g1() ¼ universal hydrodynamic function VT ¼ total interaction energy If attractive interactions dominate then the conditions are favorable for deposition to occur. In this case the deposition rate n0 can be calculated in several ways. A simple approximation which is frequently used is (Tufenkji and Elimelech 2004): n0 ¼ 4:04AS =3 N pe  =3 1

2

ð1:19Þ

where Npe is the Peclet number.

Sedimentation The rate of sedimentation of microplastics of each size class is analogous to the particle concentration of that size class according to the relation: dn j vs,j ¼  nj dt dj where: nj ¼ concentration of the particles of size class j dj ¼ sedimentation length of the particles of size class j vsj ¼ sedimentation velocity of the particles of size class j Sedimentation velocity can be calculated through Stokes’ law:   2a j 2 ρp  ρw g vs,j ¼ 9μ

ð1:20Þ

ð1:21Þ

where: μ is the dynamic viscosity coefficient of the water, aj is the radius of the particle of the size class j, ρp and ρw are the particle and water density respectively and g is the gravitational acceleration. Certainly, the sedimentation rate is dependent on the size of the particle. As the particle size is increasing the sedimentation rate is also increasing. In this case a correction factor which is determined by the particle diameter (Arvidsson et al. 2011) has to be added in the Eq. (1.20).

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Transport The transport of microplastics in the marine environment can be described through the advection-diffusion model. If we consider transport in one dimension ignoring lateral diffusion and consider only one size class of particles, the advection-diffusion is governed by the partial differential equation, expressed by Eq. (1.22): @n @n @2n þv ¼ D 2  Kn @t @x @x

ð1:22Þ

where the last term in the right-hand side represent the removal rate of microplastics from the water phase. If we ignore homoaggregation, which is a valid assumption in most cases (Korfiatis 2019), the total rate of loss of particles is analogous to the particle density. The overall proportion factor, K, is dependent on the concentrations of suspended solids. If one takes into account the homoaggregation process, it is also dependent on the concentrations of microplastic particles of other size classes. In Eq. (1.22) n is the microplastics concentration, D is the diffusion coefficient of microplastics in the marine environment, and v is the velocity of microplastic particles at the position x.

Microplastics as Sources of Contamination Most plastics contain a number of additives. These substances are added to the polymer during the manufacturing process in order to the final product has the desirable properties. Some of these additives, especially certain plasticizers, are suspected to be endocrine disrupting chemicals for humans and animals. They have been associated with conditions such as breast cancer, obesity, and DNA damage in human sperm (Suhrhoff and Scholz-Böttcher 2016). The leaching of additives from plastics to the marine environment is a very important issue. Suhrhoff and Scholz-Böttcher (2016) in a recent experimental study showed that generally the leaching of additives increases with turbulence. Also, salinity and UV radiation affect the leaching in a different way depending on the specific additive. Another important issue is the interaction of microplastics with contaminants already present in the marine environment. It has been found that microplastics can absorb several contaminants such as POPs (Persistent organic pollutants) and heavy metals such as cadmium, zinc, nickel, and lead (Lee et al. 2014; Wright and Kelly 2017). It should be noted that the fragmentation of microplastics in the marine environment results to an increase of the surface area increasing their sorption capacity. The sorption behavior of microplastics in the marine environment is affected by several parameters such as the type of plastic and the contaminant, the temperature, and the salinity (Alimi et al. 2018). However, the way of action of all these parameters is not yet clear.

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Finally, it is generally believed that the accumulation of microplastics in the marine environment can facilitate the transport of these contaminants. This conclusion is supported from experiments and mathematical models (Jaradat et al. 2009; Johari et al. 2010) but more research is needed to fully understand this issue.

References Adair JH, Suvaci E, Sindel J (2001) Surface and colloid chemistry. In: Encyclopedia of materials: science and technology. Elsevier Science Ltd Alimi OS, Budarz JF, Hernandez LM et al (2018) Microplastics and nanoplastics in aquatic environments: aggregation, deposition, and enhanced contaminant transport. Environ Sci Technol 52:1704–1724 Andrady AL (2011) Microplastics in the marine environment. Mar Pollut Bull 62:1596–1605 Arvidsson R, Molander S, Sandén BA et al (2011) Challenges in exposure modeling of nanoparticles in aquatic environments. Hum Ecol Risk Assess 17:245–262 Auta HS, Emenike CU, Fauziah SH (2017) Distribution and importance of microplastics in themarine environment: a review of the sources, fate, effects, and potential solutions. Environ Int 102:165–176 Bergstrom L (1997) Hamaker constants of inorganic materials. Adv Colloid Interf Sci 70:125–169 Besseling E, Quik JTK, Sun M et al (2017) Fate of nano- and microplastic in freshwater systems: a modeling study. Environ Pollut 220:540–548 Cole M, Lindeque P, Halsband C et al (2011) Microplastics as contaminants in the marine environment: a review. Mar Pollut Bull 62:2588–2597 Frere L, Paul-Pont I, Rinnert E et al (2017) Influence of environmental and anthropogenic factors on the composition, concentration and spatial distribution of microplastics: a case study of the Bay of Brest (Brittany, France). Environ Pollut 225:211–222 Horton AA, Dixon SJ (2018) Microplastics: an introduction to environmental transport processes. WIREs Water 5:e1268 Hotze EM, Phenrat T, Lowry GV (2010) Nanoparticle aggregation: challenges to understanding transport and reactivity in the environment. J Environ Qual 39:1909–1924 Jaradat AQ, Fowler K, Grimberg SJ, Holsen TM (2009) Transport of colloids and associated hydrophobic organic chemicals through a natural media filter. J Environ Eng 135:36–45 Johari WLW, Diamessis PJ, Lion LW (2010) Mass transfer model of nanoparticle-facilitated contaminant transport in saturated porous media. Water Res 44:1028–1037 Klein S, Dimzon IK, Eubeler J et al (2018) Analysis, occurrence, and degradation of microplastics in the aqueous environment. In: Wagner M, Lambert S (eds) Freshwater microplastics. Emerging enviromental contaminants? Springer, pp 51–67 Korfiatis DP (2019) Modeling microplastics transport and fate in the marine environment around a wastewater effluent discharge pipe. In: Karapanagioti HK, Kalavrouziotis K (eds) Microplastics in water and wastewater. IWA publishing, London, pp 101–108 Lambert S, Wagner M (2018) Microplastics are contaminants of emerging concern in freshwater environments: an overview. In: Wagner M, Lambert S (eds) Freshwater microplastics. Emerging enviromental contaminants? Springer, Cham, pp 1–23 Lee H, Shim WJ, Kwon JH (2014) Sorption capacity of plastic debris for hydrophobic organic chemicals. Sci Total Environ 470471:1545–1552 Mourgkogiannis N, Kalavrouziotis IK, Karapanagioti HK (2018) Questionnaire-based survey to managers of 101 wastewater treatment plants in Greece confirms their potential as plastic marine litter sources. Mar Pollut Bull 133:822–827 Nizzetto L, Futter M, Langaas S (2016) Are agricultural soils dumps for microplastics of urban origin? Environ Sci Technol 50:10777–10779

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Ogunola OS, Palanisami T (2016) Microplastics in the marine environment: current status, assessment methodologies, impacts and solutions. J Pollut Eff Control 4:161 Petosa AR, Jaisi DP, Quevedo IR et al (2010) Aggregation and deposition of engineered Nanomaterials in aquatic environments: role of physicochemical interactions. Environ Sci Technol 44:6532–6549 Quik JTK, Van de Meent D, Koelmans AA (2014) Simplifying modeling of nanoparticle aggregation-sedimentation behavior in environmental systems: a theoretical analysis. Water Res 62:193–201 Rios Mendoza LM, Karapanagioti H, Ramirez Alvarez N (2018) Micro(nanoplastics) in the marine environment: current knowledge and gaps. Curr Opin Environ Sci Health 1:47–51 Spielman LA, Friedlander SK (1974) Role of the electrical double layer in particle deposition by convective diffusion. J Colloid Interface Sci 46:22–31 Suhrhoff TJ, Scholz-Böttcher BM (2016) Qualitative impact of salinity, UV radiation and turbulence on leaching of organic plastic additives from four common plastics – a lab experiment. Mar Pollut Bull 102:84–94 Takagishi H, Masuda T, Shimoda T et al (2019) Method for the calculation of the Hamaker constants of organic materials by the Lifshitz macroscopic approach with density functional theory. J Phys Chem A 123:8726–8733 Tufenkji N, Elimelech M (2004) Correlation equation for predicting single-collector efficiency in physicochemical filtration in saturated porous media. Environ Sci Technol 38:529–536 Wright SL, Kelly FJ (2017) Plastic and human health: a micro issue? Environ Sci Technol 51:6634– 6647 Zhang Y, Kang S, Allen S et al (2020) Atmospheric microplastics: a review on current status and perspectives. Earth-Sci Rev 203:103118

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Contents Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Sorption Processes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Sorption Equilibrium . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Sorption Kinetics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Historical Perspectives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Sorption on MPs and Its Challenges . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MP Sizes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MP Morphologies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MP Fingerprinting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Conclusions and Future Challenges Studying Sorption on MPs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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This chapter presents the different aspects involved in the study of pollutant sorption on microplastics (MPs). Introductory descriptions of the sorption processes are presented. The study of sorption capacity at equilibrium and kinetics is important to better understand the process. Early studies recognized the presence of chemicals on the MPs, and there are several of them performed throughout the world. These studies demonstrated that the presence of many chemicals found on MPs is due to sorption while in contact with polluted seawater. Later studies performed laboratory experiments and field studies to better understand sorption processes. In the case of polyethylene (PE), which is the major polymer of MPs found at sea, hydrophobic linear sorption is the main mechanism. However, polar H. K. Karapanagioti (*) Department of Chemistry, University of Patras, Patras, Greece e-mail: [email protected] L. M. Rios-Mendoza Department of Natural Sciences/Chemistry and Physics Program, University of Wisconsin-Superior, Superior, WI, USA e-mail: [email protected] © Springer Nature Switzerland AG 2022 T. Rocha-Santos et al. (eds.), Handbook of Microplastics in the Environment, https://doi.org/10.1007/978-3-030-39041-9_9

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compounds seem to sorb more on PE once it has polar functional groups on its surface that can be formed due to degradation or the development of biofilm. There are many studies that focus on these different aspects of sorption, but there are still several challenges related to studying sorption on MPs. These challenges are related to the existing analytical techniques that limit the size of MPs to be observed and handled during experiments. These create difficulties in order to perform highly relevant studies. Keywords

Sorption of toxic compounds · Adsorption · Desorption · Microplastics · Emerging contaminants · Aging microplastics

Introduction The study of microplastic debris as a contaminant is increasing every year because it can be found in all environmental compartments (air, water, soils, sediments, and organisms, including humans). The research focuses on sources, transportation, fate, ecotoxicology, and the potential risk of their capacity to sorb and leach organic and inorganic toxic chemicals (Petersen and Hubbart 2021). The macroplastic debris degradation in the environment produces small particles called microplastics (MPs) (Tziourrou et al. 2021). There is an agreement among the scientists about the size in their limit superior (5 mm), but not in the limit inferior to separate these MPs with the nanoplastics (Rios Mendoza et al. 2018). However, there has been a discrepancy among the studies of MPs in different sizes, and an example is the proposition of Frias et al. in the redefinition of MP size (Frias and Nash 2019). It has been reported that in natural environments, MPs photodegrade by ultraviolet radiation, mechanical abrasion, and chemical oxidation, all these processes aging plastic particles; this aging process changes the surface properties in plastic particles, increasing their ability of binding interactions with pollutants and promoting the release of their additives (Luo et al. 2020), because MPs have a large surface area-volume ratio, and they are hydrophobic with a high capacity to sorb hydrophobic toxic compounds. However, the photodegradation of macro- and microplastic debris induces surface oxidation that suggests the adsorption of hydrophilic compounds is another way to sorption of toxic compounds (Liu et al. 2019). Due to this adsorption capacity of the MPs to toxic compounds from the environment, it is essential to understand the adsorption and desorption mechanisms of these toxic organic and inorganic compounds on MPs. Studies are showing this sorption potential of MPs, but still, it is poor understanding of the factors that influence these processes of adsorption/ desorption. This chapter aims to provide accepted knowledge and established information on the field of sorption of pollutants onto MPs. Initially, the theoretical information necessary to understand the description of the phenomena will be presented. Then, a historical perspective on how the scientific community has approached the topic over the years will be provided.

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Sorption Processes The term adsorption describes the accumulation of a substance in an interface (solid/ liquid, liquid/gas, solid/gas, and liquid/liquid). In contrast, the term absorption describes the passage of the interface and the accumulation inside the second phase. The term sorption describes both concepts. The inverse process is called desorption. A sorbent is a substance that absorbs the substance. This is a phase change distribution between solid and water: A water➔A solid Generally, there are two types of motives that lead to sorption: (a) the sorbent attraction, that is, the sorbent has strong attracting forces (e.g., ion exchange), and (b) solvent repulsion (e.g., hydrophobicity). The sorption mechanisms are as follows: (a) distribution in organic matter, correlated with octanol-water partition coefficient (Kow) that is a common chemical property used as a measure of hydrophobicity and the percentage of organic carbon in the solid, (b) sorption on bare mineral surfaces correlates with the intermolecular forces of the organic on the mineral surface, (c) ion exchange, for polar organics and element species, and (d) specific binding, only for organics that form strong bonds and for element species. The bonds that develop between the solid and the sorbed chemical can be due to: (a) natural forces, e.g., Van der Waals 1–2 kcal/mol; (b) ion exchange – 50 kcal/mol. Sorption due to natural forces is a reversible process, whereas sorption due to chemical forces is not freely reversible. To study the kinetics of sorption, there are three steps from the water to the sorption position on or inside the solid that should be defined: (i) Passage from the outer stagnant layer of water (ii) Inter-particle diffusion (iii) Sorption (I) and (ii) are usually the limiting factors for the sorption kinetic rate.

Sorption Equilibrium The equilibrium (steady-state) of sorption is rare but nonetheless gives us some useful information on sorbent potential and sorption mechanisms. It is described by the following relationships: qe ¼ Kd Ce where,

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Kd is the sorption distribution coefficient ¼ qe / Ce (units in volume of solution/mass of sorbent) Ce is the concentration of the component in water at equilibrium (units in mass of chemical/volume of water solution) qe is the mass of the sorbed component to the mass of the sorbent (units in mass of chemical/mass of sorbent) Details on sorption equilibrium of hydrophobic organic compounds to plastics in the marine environment have been previously presented in Endo and Koelmans (2016). Adsorption kinetic mechanisms of pollutants on MPs have been reported by Li and collaborators (Li et al. 2021). Fu et al. (2021) summarized kinetics isotherm models and mechanisms of adsorption of organic pollutants on MPs. There are two ways to study the sorption capacity of MP items. One way is to employ sorption batch studies using glass vials for the sorption of hydrophobic organic compounds and plastic vials for the sorption of metals. The batch vials have certain mass of MPs and solutions of various concentrations of the component to be studied. Blank samples contain only the solutions of various concentrations but not the MPs. After a certain time-period, the concentration in solution is measured in both sets of vials (samples and blanks). The mass sorbed on the MP is determined through the mass balance if the concentration in the blank vial is considered as the initial concentration (Co) and the concentration in the sample vial is considered as Ce. qe in this case is calculated as qe ¼ ðCo  CeÞ V=m where, V is the volume of the solution in the sample vial, and m is the mass of the MP in the sample vial. At equilibrium, Ce is stable over time. Graphs showing qe versus Ce for batch studies are called isotherms. If isotherms are linear, then their slope is Kd. With this experimental way, the behavior over a chemical concentration range can be studied. The other way to study the capacity of the MP is to deploy the MP particle in the sea that is known to contain the specific component to be studied. After a certain time-period, the concentration of the component on the MP (qe) is measured directly through solid-liquid extraction (Rios Mendoza et al. 2017). In this case, if the concentration of the component in the seawater (Ce) can be measured, then, Kd can also be calculated. However, the sorption behavior of the MP can only be tested for one certain chemical concentration. On the other hand, this study and the magnitude of the concentration of the chemical in seawater are more relevant than the previous experimental way that the concentration range might be irrelevant to environmental conditions. MPs acting as carriers of toxic compounds in the aquatic environment is a debate topic because it is still unknown if these particles can cause ecological risks (Mei et al. 2020).

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MPs are photodegraded and form carbon double bond oxygen, and this is an aging process in the environment. It was presented that this aging allows the sorption of toxic compounds (Petersen and Hubbart 2021).

Sorption Kinetics Details on sorption and desorption kinetics of hydrophobic organic compounds to plastics in the marine environment have been previously presented in Karapanagioti and Werner (2018). Sorption kinetic experiments can be performed using the same experimental ways described above to study sorption capacity (Karapanagioti and Klontza 2008; Rochman et al. 2013). However, if one wants to emphasize on the sorption kinetics, measurements of the solution concentration (Ce) or the concentration in the MP (qe) should be performed at regular sampling times until they are stabilized, and equilibrium is reached. The sorption kinetic results for spherical MPs can be simulated and explained using Fick’s 2nd law in spherical coordinates (Grathwohl 1998). The rate of sorption depends on different parameters. It is dependent on the concentration of the component in the solution, the diffusion coefficient of the component in the solution, the surface area of the MP, the radius or the thickness of the MP, the diffusion coefficient of the component within the polymer, the thickness of the water layer on the MP, etc. It is easy to assume that the finer the particle, the faster the sorption will reach equilibrium. However, it is not that easy to predict desorption if sorption has occurred long ago, and since then, MPs have been standing on the beach or they have degraded due to their exposure to the sunlight. Desorption kinetics can also change if the MPs are found surrounded by a hydrophobic solvent, e.g., in the body or the stomach of an organism. In one study under conditions simulating warm-blooded organisms, desorption rates were faster when gut surfactant was present in the solution rather than seawater alone (Bakir et al. 2014). More specifically, phenanthrene with PE demonstrated a 1st order desorption rate 8.5 times faster in the surfactant solution at 38  C than in seawater demonstrating a high potential for transport from plastic to the organisms. Fish oil or stomach oil also causes increasing desorption when in contact with plastic. In cases that only trace amounts were leached into distilled water, seawater, and acidic pepsin solution, over 20 times as much component was leached into stomach oil by day 15, and over 50 times as much into fish oil (a major component of stomach oil) by day 2 (Tanaka et al. 2015). Fu et al. (2021) summarized studies on kinetics and isotherms models in the adsorption of organic pollutants on MPs from 2018 to 2021. These models estimated the efficacy of the adsorption of pollutants and reported their possible mechanisms during the adsorption of the compounds. The main kinetic models reported herein are the pseudofirst order, pseudosecond order, intraparticle diffusion, and film diffusion. The isotherm models described the equilibrium between the organic compounds, solution, and MPs at constant temperature. It is assumed that MP surfaces are uniform where adsorption occurred (Langmuir model), and when the

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surfaces are not uniform with chemical and van der Waals adsorption (Freundlich model). The mechanisms of the adsorption of organic compounds by MPs are explained by hydrophobic interactions, partition effect, electrostatic interactions, and noncovalent interactions.

Historical Perspectives As early as the 1970s, marine plastic pellets were reported to contain polychlorinated biphenyls (PCBs). These early observations did not adequately determine the origin of PCBs in plastic pellets but hypothesized that they were either adsorbed from ambient seawater or came from plasticizers (Carpenter et al. 1972; Gregory 1978). However, the first study that presented evidence related to hazardous chemicals sorbed onto MPs was performed by the group of Prof. Takada, Tokyo, Japan (Mato et al. 2001). PCBs, and DDE, were detected in polypropylene (PP) plastic pellets collected from four Japanese coastal sampling sites with varying concentrations. At the same study, a field sorption experiment using PP virgin pellets demonstrated a significant and steady increase of chemical concentration on the pellets. This suggested that the source of PCBs and DDE on the pellets was seawater and that chemical sorption to pellet surfaces is possible. A later study by the same laboratory (Endo et al. 2005) showed not only regional differences in PCBs concentrations in plastic pellets that were consistent with those in mussels, but also correlation of pellet discoloration with PCBs concentration and about one order of magnitude higher PCBs concentration for PE compared to PP. This last observation suggests that different polymers sorb chemicals with varying affinities and possibly different mechanisms. The outcome of Endo et al. (2005) was the initiation of International Plastic Pellet Watch that prompted researchers throughout the world to send pellets to Prof. Takada’s Laboratory of Organic Geochemistry to monitor persistent organic pollutants throughout the world using plastic pellets as passive samplers. The most massive outcome of this program was the publication by Ogata et al. (2009) which included plastic pellet samples from throughout the whole globe. Details on this program and on hazardous chemicals in plastics in the marine environment have been previously presented in Yamashita et al. (2018). To better understand the distribution of plastic pellets with sorbed chemicals, a piece by piece analysis was performed for samples from urban and remote areas and the open sea (Hirai et al. 2011). Concentrations varied considerably among plastic pellet pieces. However, the samples from urban beaches did contain higher chemical concentrations. These observations prompted the group to perform sampling in remote island in three oceans to determine the background concentration levels of sorbed chemicals on plastic pellets (Heskett et al. 2012). In these islands, chemical concentrations in plastic pellets were 2–3 orders of magnitude lower than in the urban and industrialized beaches. In other parts of the world, several other researchers have used extraction methods to determine the chemical loading on plastic pellets and MPs. In Pacific Gyre,

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California, and Hawaii (the United States) as well as in Guadalupe island (Mexico), Rios Mendoza et al. (2007; Rios Mendoza and Jones 2015) measured Persistent Organic Pollutants (POPs) such as DDTs, PCBs, and PAHs in marine MPs. More studies were performed in Portugal, Greece, Belgium, South Africa, Brazil, China, and California, USA (Frias et al. 2010; Karapanagioti et al. 2010, 2011; Gauquie et al. 2015; Ryan et al. 2012; Fisner et al. 2013a, b; Zhang et al. 2015; Van et al. 2012). In the meantime, some of the research questions posed by Endo et al. (2005) have been addressed by other researchers performing laboratory and field experiments focused to target these questions. Karapanagioti and Klontza (2008) performed sorption experiments with virgin PE and PP pellets and phenanthrene (a three-ring polycyclic aromatic hydrocarbon). They found that indeed PP sorbs about one order of magnitude less phenanthrene than PE under the same conditions. At the same time, phenanthrene sorption kinetics were faster for PP than for PE suggesting a different sorption mechanism for the two polymers. Fotopoulou and Karapanagioti (2012) found a correlation between aging and pellet discoloration. The higher the FTIR peak representing oxidation of the pellet surface is, the stronger is the yellow color of the pellet. Thus, sampling pellets of the same yellowness would result in more homogeneous chemical component measurements due to similar exposure times at the same environment. A unique study, on this topic, is performed by Ahn et al. (2005) that used an almost unique instrument called microprobe laser desorption laser-ionization mass spectroscopy (μL2MS) developed in Stanford University. This instrument was able to analyze for polyaromatic hydrocarbons on solids. The experiment performed included a kinetic study of sorption for phenanthrene or pyrene on polyoxymethylene pellets. After a certain contact time, the pellets were sliced into half and the inner surface of the pellet could undergo analysis for its content of phenanthrene or pyrene. This way, it was possible to study the diffusion of each chemical inside the pellet with time. During the early sampling times of the experiment, chemical concentration was higher at or close to the surface of the pellet and zero in the center of the pellet. At the end of the experiment (sorption equilibrium), chemical concentration was almost the same throughout the pellet diameter. This suggest that chemicals such as polyaromatic hydrocarbons found dissolved in water can indeed penetrate polyoxymethylene and diffuse throughout its volume. This study receives much attention by the scientific community, but since the instrument is unique, it was not possible to repeat the study for other more commonly used plastics. More researchers studied sorption into MPs using several different chemicals and different polymers. For example, Hüffer and Hofmann (2016) studied the influence on sorption both due to sorbent and sorbate chemical properties. More specifically, sorption of hydrophobic compounds increased following the order polyamide (PA) < PE < polyvinyl chloride (PVC) < polystyrene (PS). The strong sorption by aromatic phenyl groups of PS compared to nonaromatic PE and PVC could be interpreted to result from strong interactions between PS and aromatic organic compounds. Also, sorption isotherms were linear for PE but not for PS suggesting stronger bonds and adsorption mechanisms are taking place for PS. Sorbate hydrophobicity was found to be very important for sorption into PE, and the sorptive

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behavior could be predicted based on component octanol-water partition coefficient (Kow). This correlation was not that strong for the other polymers studied. Nevertheless, hydrophobicity is the main property governing sorption, but the ability to interact with the polymer may also be important. The next research question to be answered is related to sorbate chemicals that are not highly hydrophobic. More specifically, Li et al. (2018) performed sorption studies with several polymers and 5 antibiotics. Antibiotics are ionizable compounds and thus, hydrophilic, demonstrating higher affinity for polar polymer PA. Also, their sorption seems to be affected by pH and ionic strength. Under certain conditions, they do not sorb into the hydrophobic MPs demonstrating a totally different behavior that the POPs that are commonly found sorbed into PE MPs are commonly found in the marine environment. The properties of MPs may change because of environmental factors and therefore influence their sorptive behavior. Polar functional groups, such as carbonyl, ester, and ketone groups, have been identified in beached plastic samples (Fotopoulou and Karapanagioti 2015). The presence of polar functional groups may contribute to the formation of H-bonding and may favor the sorption of antibiotics. The same is true on the effect of biofilm on the MP surface (Tziourrou et al. 2020a) that is the formation of functional groups. A study performed isotherms with PE MPs both in the absence and the presence of biofilm and an antibiotic (Wang et al. 2020). It seems that the presence of biofilm increased the sorption of the antibiotic, and even the presence of positive copper ions bonded on the biofilm showed a positive effect. In this case, complexation between the biofilm functional groups and the antibiotic is possibly the sorption mechanism. Then, desorption is more difficult to occur in such cases and depends on the pH and solution-ionic strength. Based on the studies of sorption of organic compounds on MP surfaces, the factors affecting sorption can be summarized in physicochemical properties of MPs and of toxic organic compounds, and environmental factors.

Sorption on MPs and Its Challenges The previous studies showed that organic toxic compounds can be adsorbed onto the MP surfaces through hydrophobic, electrostatic, and noncovalent interactions (Fu et al. 2021). The comparison of adsorption of hydrophilic organic pollutant between pristine and artificially aged MPs was investigated, and the main factors were hydrogen bonding and electrostatic mechanisms (Liu et al. 2019). MPs in the environment can be found in different sizes, shapes, and polymer materials. All these factors affect sorption capacity and sorption kinetics (Rodriguez et al. 2019).

MP Sizes It is known that the smaller the MPs particles, the larger their specific surface area, therefore the more the possible sites for adsorption of organic toxic compounds. MPs

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in sizes that are visible with naked-eye are easy to work with during experiments. However, MPs that are not visible are more abundant in the environment and are more relevant for human health or the health of other organisms that ingest them. Besides the smaller the particles the larger the specific surface area; however, it is hard to work in the laboratory with particles that are not visible, especially in low concentrations. It is difficult to make them since polymers cannot be crushed due to their flexibility, and it is expensive to buy them from the market. Also, in the market it is hard to buy the relevant ones since the market produces them for other purpose. PE powder is not homogenous in terms of particle size or shape, and powder particles also create aggregates (Tziourrou et al. 2020b) that have a totally different behavior than the single particles. MPs are considered biologically inert but can be a toxic compounds vector to organisms by ingestion; Cormier and collaborators (2021) reported the sorption and desorption kinetics of perfluorooctanesulfonate (PFOS), compounds considered chemical stables and used in a great number of products (waxes, cleaning, firefighting foams, textiles, and papers, among others). Cormier et al. used PFOS and virgin PE MPs under simulated digestive conditions to observe the sorption/desorption kinetics. Hydrophobic interactions were the main factor influencing sorption processes, and the equilibrium dissociation constant was bigger when MP sizes decrease. Instead, desorption was explained by molecular properties and chemical interactions; in that study, the maximum desorption (80%) was reached in a 4-days period (Cormier et al. 2021).

MP Morphologies MPs can be found as perfect sphere shapes if they are microbeads from some cosmetics or industrial pellets. Pellets can be found in the shape of sphere, cylinder, or disc. MP fragments from larger plastics are usually irregular in shape. Films are usually much thinner in one dimension, and fibers are thinner in two dimensions. Beads, pellets, and fragments can be modeled as spheres, but films and fibers require other approach and reach equilibrium much faster. Also, foams can be spheres or fragments but may also contain air in their pores. Another factor is the aging of the MP that has the possibility to change their surface area. Plastic debris is photodegraded by the ultraviolet radiation, then their surfaces are oxidated and formed microcracks that favor the adsorption of organic contaminants (Fu et al. 2021).

MP Fingerprinting One of the main synthetic polymers of MPs is PE; it is found floating on water surface. However, since sediments contain much higher concentrations of chemicals than water, sunk MPs are rather relevant. Sunk MPs may be from PE with biofilm or sediment attached to it but can also be from polymers denser than PE such as PET. If sedimentation rate is high, then these MPs maybe covered with sediment and later be incorporated to the geosphere. However, if MPs are in proximity with the sediment,

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they will sorb any chemicals leached in the sediment pore water and may create a high mass transfer rate since the MP sorption kinetics maybe faster than sediment sorption. Also, they are in proximity with benthic organisms that may feed with sediment-containing MPs. The benthic organisms may break down the MPs in smaller particles creating a faster chemical desorbing MP that may release the chemical in the environment or within the body of the organism. Adsorption mechanisms have been studied lately to find explanation of these mechanisms; Wu and collaborators (Wu et al. 2019) used PVC MPs to study the adsorption of five biphenols. Their results showed that besides the hydrophobic, and electrostatic, repulsions, the main mechanism is related to hydrogen-halogen bond. Liu and collaborators (Liu et al. 2019) used PS and PVC MPs in pristine and aged conditions to study the adsorption of organic compounds and found significant difference in their capacity to adsorb the compounds, but the hydrogen bond and electrostatic interactions were the main mechanisms for the adsorption showing that hydrogen bonding was the main mechanism for aged MPs.

Conclusions and Future Challenges Studying Sorption on MPs The main challenge related to studying sorption on MPs is the use of experimental conditions that are representative of physical conditions. It is necessary to know the median value of the size of the MPs found in the environment, the environmental chemical concentration in seawater, freshwater, or in the sediment, the environmental MP concentration in the aquatic system, and the environmental conditions such as salinity, pH, dissolved or suspended organic matter concentration, etc. So far, we do not know all the above information since it is difficult for most scientists performing monitoring to analyze for MPs that are below the visual range, which are below 10 μm which is currently the limit for micro-FTIR or micro-Raman analysis. Also, micropollutant concentrations are difficult to monitor in the sea or generally in water. Thus, only hypothetical situations can be tested in the laboratory, and for this reason, the physical meaning of their results is currently questionable.

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Patricia L. Corcoran

Contents Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Mechanical Degradation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Chemical Degradation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Biological Degradation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

Microplastic debris in the environment degrades mechanically, chemically, and biologically. Degradation rates depend on polymer characteristics, such as structure, additives, and chemical composition, as well as environmental characteristics, such as temperature and humidity, depositional matrix (e.g., water, soil, sand, terrestrial versus aquatic), and depositional environment. The latter factor plays an integral role in determining whether microplastic particles are exposed to sunlight or buried beneath the water column or in the benthos, and in the amount of mechanical abrasion that occurs in settings such as beaches versus landfills. Although mechanical, chemical, and biological degradation can each break down microplastics into nanoplastics or oligomers and monomers, the combination of two or all three weathering processes normally interact to lead to microplastics degradation. In this chapter, the three types of degradation are summarized and examples are provided in which microplastics have been broken down in the environment and under simulated environmental conditions.

P. L. Corcoran (*) Department of Earth Sciences, University of Western Ontario, London, ON, Canada e-mail: [email protected] © Springer Nature Switzerland AG 2022 T. Rocha-Santos et al. (eds.), Handbook of Microplastics in the Environment, https://doi.org/10.1007/978-3-030-39041-9_10

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Introduction The breakdown of industrial plastic products has been investigated by many researchers to determine the long-term behavioral characteristics of polymers in key industrial sectors such as construction, insulation, and automotive (e.g., Henshaw et al. 1999; Zhou et al. 2014, 2020). The majority of these studies are experimental, focus on the degradability of the product, and/or are designed to determine the most weathering-stable products for each industrial application. In contrast, studying the degradation of plastic debris items in the environment or under simulated environmental conditions is aimed at determining the length of time it will take for microplastics to develop during chemical, mechanical, and biological degradation (e.g., Weinstein et al. 2016; Kalogerakis et al. 2017; Naik et al. 2020). Breakdown of macroplastic debris into microplastic particles results in an increased supply of plastic to organisms in the natural environment, thereby increasing the risk of food chain disruption (Besseling et al. 2019; Provencher et al. 2019). In addition, the production of a greater number of individual particles in the water column can reduce water transparency, thereby decreasing light infiltration to organisms at different depths. In benthic and beach sediment, addition of microplastics can affect the feeding behavior and fitness of bioturbators that normally contribute to oxygenation of the sediment (Wright et al. 2013). An abundance of microplastics on beaches may also increase the surface temperature of the sand, which in turn could affect the nesting behavior of certain species (Beckwith and Fuentes 2018). Microplastics degrade through the same processes that break down macroplastic debris items, albeit more quickly because of their higher surface to volume ratio. Microplastic particles will become even smaller versions of their originals and eventually become nanoplastics (e.g., Enfrin et al. 2020). Weathered microplastic particles have a variety of distinct surface textures, such as grooves, pits, and fractures (cracks) (Cooper and Corcoran 2010; Zbyszewski and Corcoran 2011; Gniadek and Dąbrowska 2019; Zhou et al. 2020), which can: (1) enhance release and uptake of pollutants to and from the environment (Wang et al. 2018; Guo and Wang 2019; Liu et al. 2020), (2) promote leaching of hydrocarbons (Royer et al. 2018), and (3) provide a greater surface area for colonization by microorganisms (McCormick et al. 2014; Reiser et al. 2014; Wang et al. 2017) that could become invasive if transported great distances from their natural habitats. The aim of this chapter is to provide a review of the scientific literature concerning the ways in which microplastics degrade in the environment and under simulated environmental conditions. The three main types of degradation considered are mechanical (abiotic), chemical (abiotic), and biological (biotic), and in most cases, extensive degradation of particles takes place when these processes are interrelated (Chamas et al. 2020).

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Mechanical Degradation Mechanical degradation of microplastic debris mainly occurs through abrasion whereby the particles come into contact with natural and other anthropogenic items in aqueous and terrestrial settings. The natural items may include grains of sediment, shells, and woody debris, whereas anthropogenic items may include other plastic particles and littered trash, human-made barriers (e.g., seawalls, groynes), and transportation vehicles (e.g., boats, automobiles). Other considered methods of mechanical degradation include responses to temperature changes and wet/dry cycles (Klein et al. 2018). Mechanical abrasion of microplastics produces particles that are rounded (low sharpness of particle edges), similar to the morphology of natural sediment grains exposed to long transport distances or repeated abrasion in high energy environments (Fig. 1a). Investigations utilizing Scanning electron microscopy (SEM) have shown that mechanical weathering is also indicated by surface textures that include conchoidal fractures and grooves (Zbyszewski and Corcoran 2011; Cooper and Corcoran 2010; Wang et al. 2017; Zhou et al. 2018; Liu et al. 2020) (Fig. 1b). These textures are common on natural sedimentary quartz grains in littoral (shoreline) zones where grain-to-grain collisions are common (Vos et al. 2014). Beaches are therefore the premier natural sites for abrasion of microplastic particles to occur (Corcoran et al. 2009). In an experimental investigation of polyethylene (PE) films in simulated beach and offshore conditions, Kalogerakis et al. (2017) showed that the degree of weathering was enhanced in sunlight and under conditions of mechanical stress. The latter involved placing plastic strips into bottles with sand and rotating the bottles at a constant speed for 24 h. The weight loss of the plastic was approximately 14%, which was represented by generated microplastics that were invisible to the naked eye. This experiment shows that mechanical abrasion alone can result in some degree of polymer degradation. Song et al. (2017) investigated the effects of mechanical abrasion and UV exposure on microplastics in a simulated beach environment. The authors showed that the degree of mechanical degradation varied with polymer type. Particles of polypropylene (PP) and PE were found to have a low likelihood of degrading via mechanical weathering alone, but expanded polystyrene (EPS) fragmented into numerous smaller pieces via frictional forces alone. Mechanical weathering of microplastics can also occur in the water column when particles are exposed to shear stress forces. In an experimental study by Enfrin et al. (2020), PE microbeads from a facial cleanser were released into water and were subjected to shear stress conditions using mechanical stirring, pumping, and ultrasonic irradiation. The results show that microplastics are broken down into nanoplastics under low shear stress, thereby introducing a greater number of plastic particles to the environment.

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Fig. 1 Examples of the types of microplastics degradation. (a) Six microplastic particles displaying various degrees of roundness including angular (An), subangular (SAn), subrounded (SRo), and rounded (Ro). (b) SEM image of a groove (Gr) on the surface of a microplastic particle formed by mechanical abrasion. (c) Crazing on a microplastic particle formed by chemical weathering. (d) Discoloration (yellowing) formed by chemical weathering. The upper and lower left particles have experienced more photooxidation than the two relatively fresh particles on the right. Note the surface cracks on the lower left fragment. (e) Bryozoan colonizing the surface of a microplastic particle. (f) Surface of a plastic particle following removal of a biofilm. Note how the exposed surface (lower) is more weathered. (Figure 1b, c, e, and f are modified from Cooper (2012))

Although mechanical weathering can work to fragment microplastics, the process is enhanced, and in some cases, initiated by chemical degradation in the form of photooxidation, thermal oxidation, hydrolysis, and salinity and alkalinity differences.

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Chemical Degradation The chemical degradation of microplastics takes place at varying degrees depending on polymer type and presence of additives (UV stabilizers), but also on depositional setting and medium (Gewert et al. 2015; Brandon et al. 2016; Song et al. 2017). For example, microplastics on beach surfaces are expected to adsorb a greater amount of UV radiation than particles buried in benthic sediment or floating at depth in the water column (Leonas and Gorden 1993). In addition, chemical degradation in seawater or simulated seawater has been shown to progress at a higher rate than in freshwater owing to differences in salinity, alkalinity, and biological colonization of the two media (Weinstein et al. 2016; Da Costa et al. 2018). The multiple processes that occur during chemical degradation have been reviewed in detail by several authors (e.g., Allen and Edge 1992; Kulshreshtha 1992; Rabek 1996; Gijsman et al. 1999). Min et al. (2020) provide a thorough, data-driven review of microplastic degradation trends in the environment using the hydrophobicity, crystallinity, temperature, and molecular weight of different polymers from multiple studies in the literature. The reader is directed to this work and other reviews (e.g., Gewert et al. 2015) for details. Generally, photodegradation is initiated by exposure to UV radiation and oxygen, which results in molecules with shorter chain lengths than those of the original. The C–C bonds of PE, PP, polystyrene (PS), and polyvinyl chloride (PVC) do not promote photooxidation, which means that without additives or impurities in these polymers, degradation will proceed much more slowly than in a polymer like polyethylene terephthalate (PET) (Chamas et al. 2020). With impurities or structural abnormalities, the most common polymers in the environment, PE and PP, can undergo photooxidative degradation when UV light breaks C–H bonds in the polymer, or thermal degradation in which the bonds are heated to the point of rupture and undergo random scission and side-group elimination. The resultant free radicals react with oxygen, which may eventually lead to chain scission or crosslinking, the development of inert products, and reduction in the molecular weight of the polymer (Gewert et al. 2015). This reduction in weight produces a more brittle polymer prone to degradation by mechanical abrasion and/or biodegradation. In settings in which photooxidation, thermal oxidation, abrasion, and biodegradation are not enabled, such as in landfills or on the ocean floor, aromatic polyesters, such as PET may undergo hydrolysis, a process that produces shorter chains and leads to terephthalic acid and ethylene glycol (Chamas et al. 2020). The indications that chemical weathering processes have occurred are both surficial and chemical. Changes in physical properties of microplastics result in color changes (fading, yellowing), loss of mechanical properties that lead to surface cracks, embrittlement, and variations in molecular weight. Cracks, also known as crazing, as well as discoloration are visible microscopically and often with the naked eye (Fig. 1c–d) (Yakimets et al. 2004; ter Halle et al. 2017; Song et al. 2017; Naik et al. 2020). Crazing is associated with a decrease in tensile strength, with wider cracks creating a more brittle polymer. Yellowing or discoloration results from over-

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oxidation of phenolic compounds that are in the polymer. Both of these features develop more quickly in microplastics lacking UV stabilizers and in particles from terrestrial rather than aqueous settings. Compositional changes in a polymer caused by chemical weathering are best indicated in spectra produced by Fourier transform infrared (FTIR) spectroscopy (e.g., Zbyszewski and Corcoran 2011; Jelle and Nilsen 2011; Da Costa et al. 2018; Hepsø 2018). This technique is useful in identifying functional groups like carbonyls and hydroperoxides, which are important degradation pathways during oxidative weathering. For PE and PP, absorption bands in the wavenumber regions between 1850 and 1700 cm
1 indicate carbonyl groups such as carboxylic acids, aldehydes, esters and ketones, which are associated with oxidative degradation (Fig. 2a–b). In a study of microplastics sampled from Xiangshan Bay, China, Chen et al. (2018) used FTIR to show that particles in the surface water were chemically comparable to the composition of plastic gear used in mariculture activities. Both the microplastics and source plastics produced an oxidation signature at wavenumbers between 1010 and 1050 cm
1, which was interpreted as a CO stretching vibration band that would be related to the ether, ester, and alcohol functional groups. Naik et al. (2020) used FTIR to study the effects of accelerated photodegradation on high density polyethylene (HDPE), nylon 6, PP, and high impact PS pellets in simulated seawater. Following artificial weathering, the spectra were compared with those of nonweathered pellets. Evidence of photooxidative changes were indicated by C–H stretching and C–H bending in HDPE, C–H stretching and methyl carbon

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Fig. 2 FTIR spectra of two PE pellets sampled from beaches. Note the characteristic PE absorbance bands at 2914 cm
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1. The upper spectrum represents a more weathered pellet than the lower spectrum, as evidenced by absorbance peaks at around 3310 cm
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stretching in nylon, C¼C stretching, C¼O stretching and O–H stretching in PP, and C–H stretching and O–H stretching in high impact PS. Although all polymer types showed evidence of photooxidation, Naik et al. (2020) stress that subsequent fragment or fiber generation from any microplastic particle depends on factors such as particle structure, manufacturing processes (i.e., addition of stabilizers, dyes, and fillers), environmental setting and degree of exposure, and the composition of the water (fresh versus saline). In a recent article by Dong et al. (2020), micro-Raman spectroscopy was employed to detect changes in microplastic composition brought about by chemical weathering. As this method has not been used extensively in the past because of the fluorescence interference when analyzing microplastics with weathered surfaces, organic coatings, and dark pigments, the authors compare Raman peaks from weathered and nonweathered standards. The results show that for PE, the identifying compositional peaks at wavenumbers 2846 and 2881 cm
1 are more subdued in weathered samples and that a broad band at wavenumbers between 2100 and 2200 cm
1 becomes more prominent. Other changes were noted for PP, PET, and PVC, which enabled Dong et al. (2020) to develop a preliminary Raman database for weathered microplastics. Although microplastics degradation can occur with a combination of chemical and physical weathering, biological degradation is often also involved in the breakdown of polymers in the environment.

Biological Degradation The key processes involved in biological degradation are outlined in various reviews (e.g., Shah et al. 2008; Pathak and Navneet 2017; Danso et al. 2019; Glaser 2019). Pathak and Navneet (2017) describe biodegradation as the process whereby plastic debris is broken down into smaller products by microbial digestion. This process proceeds in the following ways: conditional film formation, colonization, bio-fragmentation, assimilation, and mineralization. In order for biofilms to develop, the surface of a microplastic particle comes into contact with ambient water, which creates a conditioning film over the fragment. The types of organisms that sorb onto the film are primarily determined by the chemistry of the film itself (Rummel et al. 2017). Subsequent colonization often begins along surface cracks, pits, and other indentations that were created by mechanical and chemical weathering processes (Harrison et al. 2018). For example, in a study of agricultural soils from cotton fields in Northwest China, Zhang et al. (2019) identified numerous bacterial communities on PE microplastic particles that were weathered with pits, grooves, and flakes. The authors propose that the rough surfaces and altered chemistry produced by weathering supply an ideal substrate on which bacteria colonize the particles. Once colonization of the microplastic surface has taken place, organisms release exoenzymes, which break down the polymer to form oligomers, dimers, or monomers (Shah et al. 2008). The term given to the colonized surface portion of microplastics is the “plastisphere” (Zettler et al. 2013), which is generally described

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as a microbial community growing in a biofilm. The plastisphere contains a rich diversity of microbiota, such as bacteria, algae, fungi, and bryozoa (Andrady 2011; Zettler et al. 2013; Paço et al. 2017; Amaral-Zettler et al. 2020; Krause et al. 2020) (Fig. 1e). For example, Aspergillus sp. have been shown to biodegrade LDPE (Pramila and Ramesh 2011; Esmaeili et al. 2013), Rhodococcus sp. can degrade LDPE and PP (Sivan et al. 2006; Auta et al. 2018), Paço et al. (2017) demonstrated that Zalerion maritimum degrades PE, polyester polyurethane has been biodegraded by Bacillus subtilis (Shah et al. 2013), PS has been shown to degrade by colonization of Exiguobacterium sp., Thermus sp., Bacillus sp., and Geobacillus sp. (Yang et al. 2015; Chen et al. 2020), and periphytic biofilms and bacterial whole-cell biocatalysts can break down PET (Gong et al. 2018; Shabbir et al. 2020). The next stage – assimilation, may only proceed if the original plastic particle has been fragmented down to sizes that enable passage of the molecules through the cell walls of microorganisms. Once assimilation takes place, the molecules can be used as carbon and energy sources. Carbon dioxide, H2O, and CH4 are produced in this final step known as mineralization. This latter step also closes the carbon biogeochemical cycle. The speed at which breakdown takes place depends on several characteristics of the plastic material, such as molecular weight, crystallinity, functional groups, and additives (Shah et al. 2008). Biodegradation can occur aerobically and produce CO2 and H2O, or anaerobically and produce CO2, H2O, and CH4. Natural anaerobic conditions may be found in landfill settings, and Quecholac-Piña et al. (2020) have explained how degradation follows a five-stage process in such locations. Through their review of published investigations, the authors show that biodegradation rates of the most common polymers in the environment (polyolefins; e.g. PE, PP, PET, PS) are very low in landfill settings compared to their biodegradable counterparts. Consequently, aerobic biodegradation is more efficient. Under aerobic conditions, environmental controls, such as climate, salinity, light exposure, and atmospheric pollutants may affect biodegradation (Urbanek et al. 2018; Glaser 2019). For example, pollutants adsorbed to the surfaces of microplastics may aid in microbial colonization. Although biological activity can assist in degrading microplastics in the environment, colonization can also hinder the breakdown of microplastic debris. Colonizing microorganisms can increase the density of a microplastic particle thereby causing it to sink through the water column, and/or change its vertical position (Long et al. 2015; Rummel et al. 2017). Particles at greater depths or buried in benthic sediment, and those smothered by biofilms will be protected from UV radiation, which will in turn decrease the amount of degradation that occurs through photoxidation (Barnes et al. 2009; Corcoran 2015) (Fig. 1f).

Conclusion This review has shown that the degradation of microplastic debris in the environment is dependent on key parameters, such as: (1) physicochemical properties, which include the type of polymer, whether additives/fillers are in the particle, the

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presence or absence of chemicals sorbed onto particle surfaces, and the shape and surface area to volume ratio of the particle; (2) biological interactions, which may include breakdown of the particle due to colonization and digestion by microorganisms, or reduced degradation as a result of smothering by biofilms that block UV radiation; and (3) environmental factors, which include temperature, humidity, and related exposure to sunlight, as well as depositional setting in which microplastics can be mechanically abraded, buried in sediment, or floating in the water column at depths with poor sunlight penetration. The intensity of degradation is increased where microplastics are affected by all three degradation pathways: mechanical, chemical, and biological.

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Contents Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Heavy Metal . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Flame Retardant . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Polycyclic Aromatic Hydrocarbons . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Polychlorinated Biphenyls . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Pesticides . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Antibiotic . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Dioxin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

Microplastics (MPs) have become one of the most pervasive emerging pollutants in the environment because of their wide occurrence and high sorption ability for contaminants. Sorption and desorption by microplastics may play important roles in the fate of contaminants in aquatic ecosystems. The releasing of these contaminants from plastics into the environment and food chain may pose a greater risk to ecosystem health than the sorption and desorption processes of these contaminants from microplastics after ingestion. To better understand the environmental and ecological impacts of microplastics, there is an urgent need to study the adsorption and desorption behaviors of contaminants and microplastics in the environment. The absorption study of contaminants with microplastics is increasingly being studied. However, there is less knowledge about the release and the impact on the environment of compounds originating from the microplastics themselves. The previously released studies on inorganic and organic contaminants with MPs were reviewed. The contaminants include heavy metals, flame T. Lan (*) China National Institute of Standardization, Beijing, PR China e-mail: [email protected] © Springer Nature Switzerland AG 2022 T. Rocha-Santos et al. (eds.), Handbook of Microplastics in the Environment, https://doi.org/10.1007/978-3-030-39041-9_11

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retardant, pesticides, antibiotics, polycyclic aromatic hydrocarbons, polychlorinated biphenyls, dioxin, etc. For heavy metals, it can be released from MPs under higher ionic strength biological fluids such as gut saline, especially for aged MPs. It indicates that the presence of MPs enhanced the bioavailability and toxicity of heavy metals on marine animals. More comprehensive risk assessment is required to study. For other organic contaminants, as the hydrophobic partitioning leads to adsorption between pesticides and MPs. Organic contaminants can therefore be released from MPs through leaching and emission because of lack of chemically bound to the MPs matrix. The research on the interaction between MPs and organic contaminants has been just started. More comprehensive risk assessment is required to study. More attention should be paid to the release and bioavailability study of organic contaminants with MPs. And as closer to our living environment, the combined pollution of soil MPs with contaminants should be paid more attention.

Introduction Under the sunlight radiation, wind and current flushing, waste plastic particles are easily embrittled, leading to cracking and fragmentation. Over time, these particles are decomposed to form a size of less than 5 mm microplastics (MPs) (Lönnstedt and Eklöv 2016) which increase the difficulty of cleaning and recycling. In order to improve the performance of plastics, various materials need to be added to plastics. For example, glass fiber, diatomite, asbestos, carbon black, CaCO3, and TiO2 are commonly used as fillers in plastics production to improve the mechanical strength (Carroll et al. 2017). Plasticizers are added to plastics to enhance their plasticity and softness, reduce their brittleness, and make them easy to process and shape. Most commonly used are phthalate esters. To prolong the service life, stabilizer such as stearate of zinc and calcium should be added to the plastic (Sánchez and Collinson 2011). Some organic and inorganic pigments were commonly used as colorants (Garrigós et al. 2002). Flame retardants such as bisphenol A and foaming agents are also used in plastics too (Bledzki and Faruk 2006). These kinds of additives may release to environment during the aging process of plastics. Aging process of MPs particles may alter the available fraction, making these MPs have a rougher surface, more cracks and even some oxygen-containing functional groups (C¼O, C–O, and OH) (Zbyszewski and Corcoran 2011), makes them can be a good vector for hydrophobic substance, such as pesticides, polychlorinated biphenyls, polycyclic aromatic hydrocarbons, heavy metals, and other pollutants (Anbumani and Kakkar 2018), which makes pollution more easily persistent and transmitted in the ecosystem (Wang et al. 2020a). And the contaminants that exist in plastics and absorbed on plastics may release from MPs through the action of water flow, migration and diffusion; more serious complex pollution will be formed (Jiang et al. 2018). The absorption study of chemicals with microplastics is increasingly being investigated. However, there is less knowledge about the release and the impact on

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Fig. 1 The release behavior and mechanisms of heavy metal, organophosphorus flame retardant, pesticides, antibiotics, polycyclic aromatic hydrocarbons (PAHs), polychlorinated biphenyls (PCBs), and dioxin with MPs need to be deeply investigated

the environment of compounds originating from the microplastics themselves (Bandow et al. 2017). It is expected that aged MPs release more contaminants than bulk plastics, owing to the shorter diffusion path length from the bulk material to the surface. Usually, hydrophilicity compounds show high concentrations in the aqueous phase at the beginning of leaching experiments, followed by a steep decrease of concentration due to exhaustion of the bulk phase. The release of hydrophobic contaminants may be diffusion controlled, resulting in long-term release of low concentrations. But the release behavior and mechanisms of contaminants with MPs need to be deeply investigated, which is shown in Fig. 1. In this study, the previously released studies on inorganic and organic contaminants with MPs were reviewed. The review will be described according to the types of contaminants involved, such as heavy metal, organophosphorus flame retardant, pesticides, antibiotics, polycyclic aromatic hydrocarbons (PAHs), polychlorinated biphenyls (PCBs), dioxin.

Heavy Metal Heavy metal has threats to human health. Heavy metal can be brought in by plastic additives, and released into environment, so does the heavy metal absorb on MPs? The synthesis of polyvinyl chloride (PVC) requires lead (Pb), barium (Ba), and tin

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(Sn) thermal stabilizers (Hahladakis et al. 2018). These metal ions are leachable in aqueous solution, and harmful to the aquatic animals. CaCO3 and TiO2 are commonly added in plastic fillers. So, calcium (Ca) and titanium (Ti) are frequently detected in plastics. Bandow and collaborators (Bandow et al. 2017) found Ca and Ti with high content in plastics. The results are listed in Table 1. They studied the release of these elements from MPs after 2000 h of UV aging process. The results are listed in Table 2. The cumulative release of chlorine (Cl), Ca, copper (Cu) and zinc (Zn) is mostly less than 3% of the total content.

Lead Many studies on bioavailability of MPs involve the release of heavy metals from MPs. It mainly studies the release of heavy metals and the corresponding biological toxicity under gastric conditions. Boyle (Boyle et al. 2020) analyzed the release of metals from PVC, and the role of lead additives in the aqueous toxicity of PVC MPs was studied in early-life stage zebrafish (Danio rerio) by assessment of changes in expression of biomarkers. They used 2% HNO3 to liberate Pb ions in initial PVC MPs and the concentrations of Pb were detected by Inductively coupled plasma mass spectrometer (ICP-MS). The concentrations of Pb were calculated at 6691  388 ngmg1 of PVC which equated to 0.67  0.04% of the PVC on a per mass basis. Zebrafish in water were exposed with PVC MPs for 24 h, and some of the Pb was released from the PVC. The released Pb was measured to be 20.2  2.7, 46.0  4.7, and 84.3  8.7 mg L1 for 125, 250, and 500 mg L1 PVC MPs, respectively. At the highest concentration of PVC used, 500 mg L1, the concentration of Pb released in water equates to 2.52%

Table 1 Total content of certain elements in plastic samples. Cl and Ti were analyzed by X-ray fluorescence analysis (XRF), the other metals with inductively coupled plasma optical emission spectroscopy (ICP-OES). 10 μg L1) exerted significant inhibitory influence ( p < 0.005) on cell photosynthesis of Microcystis aeruginosa. More inhibiting effects on cell growth and photosynthesis using the leachates of aged MPs were observed. Longer aging time leads to more release of Cr and Pb, rendering higher toxicity to microalgae. These findings are benefits for assessing the leaching behavior of additives in MPs and their toxicological risks to aquatic organisms.

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