Current Trends and Future Developments on (Bio-) Membranes: Membrane Technologies in Environmental Protection and Public Health: Challenges and Opportunities 0128241039, 9780128241035

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Current Trends and Future Developments on (Bio-) Membranes

Current Trends and Future Developments on (Bio-) Membranes Membrane Technologies in Environmental Protection and Public Health: Challenges and Opportunities Edited by Angelo Basile Dept. of Engin., Univ. Campus Bio-medical, Rome, Italy

Mario Gensini Institute on Membrane Technology (ITM-CNR), Rende, CS, Italy

Ivo Allegrini ENVINT srl, Montopoli di Sabina, RI, Italy

Alberto Figoli Institute on Membrane Technology, National Research Council of Italy (ITM-CNR), Rende, CS, Italy

List of contributors Nicoletta Ademollo Institute of Polar Sciences (ISP), National Research Council of Italy (CNR), Rome, Italy Ivo Allegrini ENVINT srl, Montopoli di Sabina, RI, Italy Carmine Apollaro Department of Biology, Ecology and Earth Sciences (DIBEST), University of Calabria (UniCAL), Arcavacata di Rende, Calabria, Italy A.H. Avci Department of Environmental Engineering, University of Calabria, Rende, Italy Rau´l Bahamonde Soria Renewable Energy Laboratory, Faculty of Chemical Sciences, Central University of Ecuador, Quito, Ecuador; Materials & Process Engineering (iMMC-IMAP), UCLouvain, Louvain-la-Neuve, Belgium Warren R.L. Cairns Institute of Polar Sciences (ISP), National Research Council of Italy (CNR), Venice-Mestre, Veneto, Italy; Department of Environmental Sciences, Informatics and Statistics (DAIS), Ca’ Foscari University of Venice (UniVE), Venice-Mestre, Veneto, Italy Roberto Castro-Mun˜oz Department of Process Engineering and Chemical Technology, Faculty of Chemistry, Gdansk University of Technology, Gdansk, Poland; Tecnologico de Monterrey, San Antonio Buenavista, Toluca de Lerdo, Mexico; Department of Sanitary Engineering, Faculty of Civil and Environmental Engineering, Gdansk University of Technology, Gdansk, Poland Olga Cavoura Department of Public Health Policy, School of Public Health, University of West Attica, Athens, Greece Gianfranco Di Gennaro Department of Pharmacy, Health and Nutritional Sciences, University of Calabria, Rende, Calabria, Italy Alberto Figoli Institute on Membrane Technology, National Research Council of Italy (ITM-CNR), Rende, CS, Italy Ilaria Fuoco Department of Biology, Ecology and Earth Sciences (DIBEST), University of Calabria (UniCAL), Arcavacata di Rende, Calabria, Italy Francesco Galiano Institute on Membrane Technology, National Research Council of Italy (ITM-CNR), Rende, CS, Italy Antonietta Ianniello CNR, Institute of Atmospheric Pollution Research, Rome, Italy Adolfo Iulianelli Institute on Membrane Technology, National Research Council of Italy (ITM-CNR), Rende, CS, Italy Tianling Li Collaborative Innovation Centre of Atmospheric Environment and Equipment Technology, Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, School of Environmental Science and Engineering, Nanjing University of Information Science & Technology, Nanjing, Jiangsu, P.R. China

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xii List of contributors Francesca Licata Department of Health Sciences, University of Catanzaro “Magna Graecia”, Catanzaro, Calabria, Italy Patricia Luis Materials & Process Engineering (iMMC-IMAP), UCLouvain, Louvain-la-Neuve, Belgium M. Malankowska Institute of Nanoscience and Materials of Aragon (INMA), CSIC-University of Zaragoza, Zaragoza, Spain; Chemical and Environmental Engineering Department, University of Zaragoza, Zaragoza, Spain Matteo Manisco Institute on Membrane Technology, National Research Council of Italy (ITM-CNR), Rende, CS, Italy S. Mondal LAQV/Requimte, Department of Chemistry, Faculty of Science and Technology, NOVA University of Lisbon, Caparica, Portugal Carmelo G.A. Nobile Department of Pharmacy, Health and Nutritional Sciences, University of Calabria, Rende, Calabria, Italy Rosa Papadopoli Department of Health Sciences, University of Catanzaro “Magna Graecia”, Catanzaro, Calabria, Italy Luisa Patrolecco Institute of Polar Sciences (ISP), National Research Council of Italy (CNR), Rome, Italy Sarah Pizzini Institute of Polar Sciences (ISP), National Research Council of Italy (CNR), Venice, Italy; Department of Environmental Sciences, Informatics and Statistics (DAIS), Ca’ Foscari University of Venice (UniVE), Venice, Italy Stefano Polesello Water Research Institute (IRSA), National Research Council of Italy (CNR), Brugherio, Italy Antonio Procopio Department of Health Sciences, University Magna Graecia (UMG), Catanzaro, Calabria, Italy Jasmin Rauseo Institute of Polar Sciences (ISP), National Research Council of Italy (CNR), Rome, Italy Francesca Russo Institute on Membrane Technology, National Research Council of Italy (ITM-CNR), Rende, CS, Italy S. Santoro Department of Environmental Engineering, University of Calabria, Rende, Italy Francesca Spataro Institute of Polar Sciences (ISP), National Research Council of Italy (CNR), Rome, Italy U.T. Syed LAQV/Requimte, Department of Chemistry, Faculty of Science and Technology, NOVA University of Lisbon, Caparica, Portugal L. Upadhyaya King Abdullah University of Science and Technology (KAUST), Biological and Environmental Science and Engineering Division (BESE), Advanced Membranes and Porous Materials Center (AMPM), Thuwal, Saudi Arabia Federica Valentini Department of Chemistry, University of Rome 2 Tor Vergata, Rome, Italy Massimiliano Varde` Institute of Polar Sciences (ISP), National Research Council of Italy (CNR), Venice, Italy; Department of Environmental Sciences, Informatics and Statistics (DAIS), Ca’ Foscari University of Venice (UniVE), Venice, Italy; Institute of Polar Sciences (ISP), National Research Council of Italy (CNR), Venice-Mestre, Veneto, Italy; Department of Environmental Sciences, Informatics and Statistics (DAIS), Ca’ Foscari University of Venice (UniVE), Venice-Mestre, Veneto, Italy

List of contributors xiii Giovanni Vespasiano Department of Biology, Ecology and Earth Sciences (DIBEST), University of Calabria (UniCAL), Arcavacata di Rende, Calabria, Italy Zhengguo Wang Collaborative Innovation Centre of Atmospheric Environment and Equipment Technology, Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, School of Environmental Science and Engineering, Nanjing University of Information Science & Technology, Nanjing, Jiangsu, P.R. China Chao Xing Centre for Clean Environment and Energy, School of Environment and Science, Gold Coast Campus, Griffith University, Gold Coast, QLD, Australia Shanqing Zhang Centre for Clean Environment and Energy, School of Environment and Science, Gold Coast Campus, Griffith University, Gold Coast, QLD, Australia Ming Zhou Centre for Clean Environment and Energy, School of Environment and Science, Gold Coast Campus, Griffith University, Gold Coast, QLD, Australia

Contents List of contributors ................................................................................................ xi Preface................................................................................................................. xv Chapter 1: Environmental air pollution: an anthropogenic or a natural issue? ............ 1 Ivo Allegrini, Antonietta Ianniello and Federica Valentini 1.1 Introduction ........................................................................................................... 1 1.2 Most significant pollutants ..................................................................................... 6 1.2.1 Sulfur dioxide (SO2) ...................................................................................6 1.2.2 Nitrogen oxides (NOx) ................................................................................7 1.2.3 Ammonia (NH3) .........................................................................................8 1.2.4 Volatile organic compounds........................................................................8 1.2.5 Ozone (O3) and photochemical pollution ..................................................14 1.3 The spatial scales of air pollution: emissions ....................................................... 21 1.4 Evolution of pollutants in the atmosphere ............................................................ 25 1.5 Air pollution and polar regions ............................................................................ 27 1.5.1 Renitrification of polar atmosphere ...........................................................28 1.5.2 Role of halogens and mercury ..................................................................31 1.6 Conclusions ......................................................................................................... 34 Acronyms..................................................................................................................... 34 List of symbols ............................................................................................................ 35 References ................................................................................................................... 35

Chapter 2: Environmental air pollution: near-source air pollution............................ 39 Ivo Allegrini, Antonietta Ianniello and Federica Valentini 2.1 2.2 2.3 2.4

Introduction ......................................................................................................... 39 Near-source chemical and physical parameters .................................................... 40 Thermal structure of the troposphere ................................................................... 43 Elevated emission sources ................................................................................... 46 v

vi Contents 2.5 The use of radon in air pollution data interpretation ............................................ 49 2.6 Atmospheric stability and secondary pollutants ................................................... 54 2.7 Advances in air pollution monitoring ................................................................... 60 2.7.1 Saturation monitoring ...............................................................................60 2.7.2 Internet of Things and Information Communication Technologies for sensors ...........................................................................64 2.7.3 A modern monitoring network ..................................................................70 2.8 Conclusions ......................................................................................................... 73 List of acronyms .......................................................................................................... 74 List of symbols ............................................................................................................ 74 References ................................................................................................................... 74

Chapter 3: The environmental pollution’s influence on public health: general principles and case studies ....................................................... 77 Gianfranco Di Gennaro, Rosa Papadopoli, Francesca Licata and Carmelo G.A. Nobile 3.1 Introduction ......................................................................................................... 77 3.2 Air pollution ........................................................................................................ 78 3.3 Water pollution .................................................................................................... 81 3.4 Noise pollution .................................................................................................... 84 3.5 Soil pollution ....................................................................................................... 86 3.6 Other forms of pollution ...................................................................................... 87 3.7 Case studies ......................................................................................................... 88 3.8 Conclusions and future trends .............................................................................. 92 List of acronyms .......................................................................................................... 93 References ................................................................................................................... 93

Chapter 4: Environmental monitoring and membrane technologies: a possible marriage? ..........................................................................101 Tianling Li, Ming Zhou, Zhengguo Wang, Chao Xing and Shanqing Zhang 4.1 Introduction ....................................................................................................... 101 4.2 Membrane-based monitoring methods ............................................................... 104 4.2.1 Direct sampling and detection .................................................................104 4.2.2 Passive sampling and detection ...............................................................107 4.3 Environmental applications ................................................................................ 110 4.3.1 Water environment .................................................................................110 4.3.2 Soil environment .....................................................................................115 4.3.3 Atmospheric environment .......................................................................116 4.4 Conclusions and future trends ............................................................................ 123

Contents vii Acknowledgment ....................................................................................................... 125 Acronyms................................................................................................................... 125 Symbols ..................................................................................................................... 125 References ................................................................................................................. 125

Chapter 5: Potentially toxic elements (As, Cd, Cr, Hg, and Pb), their provenance and removal from potable and wastewaters................137 Warren R.L. Cairns, Carmine Apollaro, Ilaria Fuoco, Giovanni Vespasiano, Antonio Procopio, Olga Cavoura and Massimiliano Varde` 5.1 Introduction ....................................................................................................... 137 5.1.1 General overview ....................................................................................137 5.1.2 Arsenic ...................................................................................................138 5.1.3 Cadmium ................................................................................................139 5.1.4 Chromium ...............................................................................................141 5.1.5 Mercury ..................................................................................................142 5.1.6 Lead ........................................................................................................144 5.2 Toxicity of As, Cd, Cr, Hg, and Pb.................................................................... 146 5.2.1 Arsenic ...................................................................................................147 5.2.2 Cadmium ................................................................................................148 5.2.3 Chromium ...............................................................................................149 5.2.4 Mercury ..................................................................................................150 5.2.5 Lead ........................................................................................................152 5.2.6 Guidelines limit and health risk assessment approach of selected potentially toxic elements ..........................................................153 5.3 Metal removal from water ................................................................................. 157 5.3.1 Metal removal in municipal wastewater treatment works ........................158 5.3.2 Enhanced elemental removal processes ...................................................159 5.3.3 Case studies ............................................................................................160 5.3.4 Effectiveness of current treatment works ................................................165 5.4 Conclusions and future trends ............................................................................ 167 List of acronyms ........................................................................................................ 168 List of symbols .......................................................................................................... 168 References ................................................................................................................. 169

Chapter 6: Some organic compounds in potable water: the PFASs, EDCs and PPCPs issue ......................................................................183 Luisa Patrolecco, Jasmin Rauseo, Nicoletta Ademollo, Stefano Polesello, Massimiliano Varde`, Sarah Pizzini and Francesca Spataro 6.1 Introduction ....................................................................................................... 183

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Contents 6.2 International directives on surface and drinking waters ..................................... 184 6.3 Sources, environmental dynamics, and final fate ............................................... 188 6.3.1 Pharmaceuticals ......................................................................................189 6.3.2 Personal care products ............................................................................192 6.3.3 Alkylphenols and Bisphenol A................................................................194 6.3.4 PAHs, PBDEs, PCBs, and PCDD/Fs .......................................................195 6.3.5 Per- and polyfluoroalkyl substances ........................................................197 6.4 Environmental and ecosystem effects ................................................................ 198 6.5 Drinking water treatment plants ......................................................................... 202 6.6 Conclusions and future trends ............................................................................ 209 Acknowledgments ...................................................................................................... 210 List of acronyms ........................................................................................................ 210 References ................................................................................................................. 211

Chapter 7: Current nanocomposite membranes as a tool for organic compounds remediation in potable waters ............................................229 Roberto Castro-Mun˜oz 7.1 Introduction ....................................................................................................... 229 7.2 Background of membrane technologies used in water remediation .................... 230 7.3 Recent developments in novel nanocomposite membrane for organic compounds and pollutants removal from water .................................................. 233 7.4 Conclusion and future trends ............................................................................. 243 Acknowledgments ...................................................................................................... 244 List of acronyms ........................................................................................................ 244 References ................................................................................................................. 245 Further reading........................................................................................................... 254

Chapter 8: Membranes for air cleaning ................................................................255 Francesca Russo, Matteo Manisco, Adolfo Iulianelli, Roberto Castro-Mun˜oz, Francesco Galiano and Alberto Figoli 8.1 Introduction ....................................................................................................... 255 8.2 Membranes for air cleaning ............................................................................... 257 8.3 Polymeric membrane preparation for air cleaning.............................................. 260 8.3.1 Phase inversion .......................................................................................260 8.3.2 Electrospinning technique .......................................................................262 8.3.3 Polymeric coating ...................................................................................264 8.4 Membrane materials for air cleaning ................................................................. 265

Contents ix 8.4.1 Polymeric and biopolymeric materials ....................................................265 8.4.2 Additives and advanced materials ...........................................................268 8.5 Membrane technology applications in air cleaning ............................................ 270 8.5.1 Air transport mechanism in membranes ..................................................270 8.5.2 Individual protection devices ..................................................................272 8.5.3 Recovery of vapors of organic substances from the air ...........................277 8.5.4 Air conditioners ......................................................................................281 8.6 Conclusions and future trends ............................................................................ 284 List of acronyms ........................................................................................................ 286 List of symbols .......................................................................................................... 287 References ................................................................................................................. 287

Chapter 9: Antifouling membranes for polluted solvents treatment ........................295 Rau´l Bahamonde Soria and Patricia Luis 9.1 Introduction ....................................................................................................... 295 9.2 Membrane technology for aqueous streams ....................................................... 296 9.2.1 Membrane fouling...................................................................................296 9.2.2 Fouling classification ..............................................................................299 9.2.3 Fouling mechanisms and interpretation ...................................................299 9.2.4 Membrane cleaning strategies .................................................................300 9.2.5 Antifouling membranes ...........................................................................306 9.2.6 Bioadhesion (bioinspired adhesion chemistry) ........................................316 9.2.7 Other methods.........................................................................................320 9.3 Membrane technology for organic solvent ......................................................... 321 9.3.1 Membrane materials................................................................................323 9.3.2 Principal problems ..................................................................................323 9.3.3 Fouling in membrane technology for organic solvents ............................326 9.4 Brief description of techniques for characterizing and understanding mechanisms membrane fouling .......................................................................... 326 9.5 Conclusions and outlook .................................................................................... 327 Acknowledgments ...................................................................................................... 328 List of acronyms ........................................................................................................ 328 List of symbols .......................................................................................................... 329 References ................................................................................................................. 330

Chapter 10: Membrane sensors for pollution problems.........................................335 S. Mondal, M. Malankowska, A.H. Avci, U.T. Syed, L. Upadhyaya and S. Santoro

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Contents 10.1 Introduction ..................................................................................................... 335 10.2 Air pollution .................................................................................................... 336 10.2.1 Membrane-based gas sensors .............................................................. 336 10.2.2 Working principle of membrane-based gas sensor .............................. 336 10.2.3 Categories of membrane-based gas sensors ......................................... 338 10.2.4 Recent breakthrough in membranes for air pollution sensing .............. 340 10.3 Water pollution ................................................................................................ 342 10.3.1 Plastics ................................................................................................ 342 10.3.2 Microplastics removal from wastewater .............................................. 347 10.3.3 Drinking water .................................................................................... 348 10.3.4 Potential membranes for microplastic removal.................................... 348 10.3.5 Microplastic detection ......................................................................... 349 10.4 Pathogens......................................................................................................... 349 10.4.1 Electrochemical methods .................................................................... 351 10.4.2 Optical methods .................................................................................. 351 10.5 Conclusion and future trends ........................................................................... 353 List of acronyms ........................................................................................................ 354 List of symbols .......................................................................................................... 355 References ................................................................................................................. 355

Index ..................................................................................................................363

Preface The issue of pollution is one of the focal points for industrial and social development because it is, perhaps, the most severe problem that man will have to face in the coming decades. A 2016 estimate predicts that in the year 2050 we will count one premature death every 5 s if air pollution is not controlled. This is a particularly serious threat in underdeveloped countries, but, as indicated by the World Health Organization, it remains the greatest risk factor for health in Europe as well. This also means that the treatment of different environmental matrices must become one of the turning points of present and future research and technological development. In this context, we suggest paying great attention, among others, to membrane technology because it covers all the possible engineering approaches for the transport of fluids (liquid, gas, vapors) between two faces (or fractions, named retentate and permeate, respectively) with the help of semipermeable materials known as membranes. Moreover, it is also important to underline that some membrane separation processes operate without heating, and therefore the systems use less energy than conventional thermal separation processes, such as distillation, sublimation, or crystallization. In some cases, the separation process in membranes is purely physical and both fractions can be used. For example, cold separation using membrane technology is widely used in the food technology, biotechnology, and pharmaceutical industries. So, it is the right time to examine the challenges and the future of the membrane technology when applied to reduce the pollution. The challenges are both technical and sociopolitical and provide the drivers for new developments of membrane systems. In this book, the performance of membrane technology in helping to reduce the pollution is deeply and critically discussed in various but specific chapters. In particular, the book provides thorough coverage of all the aspects of pollution, the stateof-the-art of the application of membrane technology in both urban and industrial environments.

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In other words, the book aims to shed light, giving a broad and very detailed view, on the aforementioned issues through a point of view typical of an industrial engineer. Some chapters were written by the editors, whereas others are by well-known expert scientists. Going a bit into the details of the book’s content, Chapter 1 (Allegrini, Ianniello, and Valentini) deals with the nature and emissions, transformations and transport of atmospheric pollutants at the global level. Emissions are anthropogenic or natural emitting species that are then mixing in the far field contributing to local and to background pollution. The estimation of emissions is reported, as well as the evolution of pollutants in terms of formation by the secondary reaction and deposition (wet or dry). Emphasis is given to particulate matter with regard to its size distribution and chemical content. Ozone pollution is an additional issue which is also considered with other pollutants generated by photochemical pollution due to its effects on human health and vegetation. Finally, atmospheric pollution in deposition in remote sites in the Arctic and Antarctica, with chemical reactions occurring in snow or icefields, are also taken in account. This discussion is continued in Chapter 2 by the same authors (Allegrini, Ianniello, and Valentini) by focusing on atmospheric pollution near to the sources, thus emphasizing pollution near the source (local and regional). The process is now described by general equations that can be easily adapted to any location. They contain terms related to emissions, chemical transformations, and deposition. Dilution and removal of pollution are strongly affected by atmospheric turbulence, which are simply described by qualitative aspects. The use of radon data for the interpretation of primary air pollution processes is also described. The approach followed in this chapter results in a simple and immediate understanding of pollution data. Also, the same approach can be effectively used for secondary pollutants such as ozone and nitrogen dioxide. This work also illustrates how to combine the Internet of Things with small low-cost sensors to gain detailed information on the space and time distribution of pollutants. Chapter 3 (Di Gennaro, Papadopoli, Licata, and Nobile) underlines that quantifying the effects of pollution on human health is difficult due to the multitude of confounders. Furthermore, the cause effect links between pollutants and pathologies are often not clear, since the different forms of pollution are interdependent. In this context, the chapter summarizes the mechanisms through which different forms of pollution impact human health, with a particular emphasis on air, water, soil, and noise pollution. Estimates present in the literature that can give an idea of the health impact are also indicated. Finally, famous case studies to show how the problem of pollution is widespread all over the world, from Delhi to Italy, to Hong Kong, are also reported.

Preface xvii Chapter 4 (Li, Zhou, Wang, Xing, and Zhang) starts with an interesting question: “Environmental monitoring and membrane technologies: a possible marriage?” Over decades the incorporation of membrane technologies into modern environmental monitoring technologies has significantly promoted the progress of research and the development of remote sensing, data sciences, artificial intelligence, environmental digitization, and health, offering in situ and high-resolution data support for environmental quality control in water, soil, and the atmosphere. In short, this chapter systematically reviews and discusses two mainstream membrane-based monitoring technologies, that is, direct and indirect methods, and their applications in environmental monitoring, and puts forward the future development trends of these technologies. Chapter 5 (Cairns, Apollaro, Fuoco, Vespasiano, Procopio, Cavoura, and Varde`) illustrates the natural occurrence of potentially toxic elements (As, Cd, Cr, Hg, and Pb) in the environment, particularly geological sources, and their impact on groundwater quality. The toxicity of the main elements, as well as guides to their toxicity and the control limits in drinking water are covered. Finally, the chapter discusses the main methods for the removal of toxic elements from groundwater, drinking water, and wastewater, considering that the overarching goal of each is the protection and health of the hydrosphere. Anthropogenic organic pollutants are continuously entering aquatic ecosystems, principally through urban and industrial discharges, and there is ever more research worldwide about their environmental and ecotoxicological impact. Nevertheless, the release of most of them into water ecosystems is not yet regulated. They are commonly found in surface and groundwaters, threatening the quality and availability of the major renewable resources for the production of drinking water. Starting from the current international directives on the surface and drinking water protection, Chapter 6 (Patrolecco, Rauseo, Ademollo, Polesello, Varde`, Pizzini, and Spataro) focuses on the sources, environmental dynamics, and effects of selected classes of conventional and emerging organic micropollutants, with particular attention to drinking water and the effectiveness of water treatments in their removal. Environmental and toxicological risk implications are also considered. The main conclusion of the authors is that further research efforts are needed for the correct and sustainable management of drinking resources, constituting an important challenge for the protection of water supplies and human health. Another important aspect concerning membrane technology regards the incorporation and coating of nanofillers in polymer phases that result in the manufacture of nanocompositebased membranes. One of the relevant applications of nanocomposite membranes deals with the removal of different organic compounds from potable waters. At this point, nanocomposite membranes are mainly implemented in membrane technologies driven by a pressure gradient, such as microfiltration, ultrafiltration, nanofiltration, and reverse osmosis, which have largely proved their ability in separating various types of organic molecules in

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water treatment applications. Therefore the aim of Chapter 7 (Castro-Mun˜oz and Buenavista) is devoted to compiling the most recent concepts of nanocomposite membranes for the remediation of potable waters. The emphasis has been mainly paid to the key developments and meaningful outcomes in separating such organics components from water. As it is well known, air pollution causes several problems for both human health and the environment. Moreover, membrane air cleaning is a recent technology, still under development, that is able to improve air filtration efficiency through higher performing devices, compared to the traditional ones. In this regard, Chapter 8 (Russo, Manisco, Iulianelli, Castro-Mun˜oz, Galiano, and Figoli) deals with the most useful membrane separation techniques for air cleaning. Furthermore, the growing importance in air cleaning applications of polymeric, mixed matrix, and inorganics membranes, produced by different techniques (e.g., phase inversion, electrospinning) and under different configurations (hollow fibers, flat sheet, and nanofibers), is also deeply discussed. Meanwhile, the materials used for their preparation and related properties have been well identified and illustrated, paying particular attention to the main areas of application, such as protection devices, air conditioners, and vapors of organic substances recovery (from air) units. Considering again membrane technology, fouling is one of the most limiting aspects, being the main obstacle to the widespread use of several membrane-based technologies, because fouling leads to loss of productivity and reduced permeate quality. Therefore the future success of the membrane technology strongly depends to a large extent on how the problem of fouling is solved. In this context, Chapter 9 (Soria and Luis) presents the types of contaminants, fouling mechanisms, cleaning and control processes of membrane fouling. In addition, membrane surface modification, both active and passive, and its influence on membrane fouling is also discussed. Furthermore, the latest advances on membrane modification for organic solvents are shown. Finally, a brief description of the techniques used to understand and characterize membrane fouling is also presented. The in-field detection of pollutants and the assessment of the quality of industrial exhausts and wastewaters are essential activities in environmental management. Thus the modern society continuously demands the development of cost-effective, quick, real-time, and reliable sensors. Membrane technology consists of a solid background also for the development of advanced sensors to detect pollutants. In fact, highly selective membranes responsible for the molecular recognition and/or selective capture of target analyte(s) are the core of highly sensitive sensors. In this context, Chapter 10 (Mondal, Malankowska, Avci, Syed, Upadhyaya, and Santoro) presents a dissertation about the implementation of membranes in sensors aimed at detecting gaseous pollutants, and elucidates the mechanism of detection. The key features of membranes for the detection of nano/microplastics and pathogens, two of the trending emerging questions, is highlighted too.

Preface xix The editors take this opportunity to thank all the authors for their excellent work and also for their continued patience in reviewing, sometimes various times, their chapters following the comments and suggestions of the editors. Special thanks are also dedicated to the great professionalism of the staff of Elsevier, able to help us at each step.

Angelo Basile Mario Gensini Alberto Figoli Ivo Allegrini

CHAPTER 1

Environmental air pollution: an anthropogenic or a natural issue? Ivo Allegrini1, Antonietta Ianniello2 and Federica Valentini3 1

ENVINT srl, Montopoli di Sabina, RI, Italy, 2CNR, Institute of Atmospheric Pollution Research, Rome, Italy, 3Department of Chemistry, University of Rome 2 Tor Vergata, Rome, Italy

1.1 Introduction Air pollution is an issue that is thought to be related to the development of human activities related to industrial and social development. However, we know that air pollution has developed in parallel with human history since it started with fire controls by humans. This means that between 1.5 and 0.5 million years, humans started to control domestic fires, and unaware caused the first anthropogenic air pollution events. Therefore, the discovery of fire also meant the discovery of air pollution. There is much evidence that humans in caves were exposed to air pollution caused by fires used for heating, food cooking, or to keep away dangerous beasts. After prehistoric pollution, there are several pieces of evidence of people complaining because of pollution caused by various reasons. Smell, fumes, dust, and other nuisances are known in ancient civilizations such as in Egypt, Mesopotamia, and Israel (Mamane, 1987). In 1542 Juan Rodriquez Cabrillo sailed into Los Angeles Bay. After noticing how the smoke from Native American fires on the shore rose and spread after reaching an elevated inversion, he named it “The Bay of Smokes,” reporting pollution events caused by biomass burning. Ancient residents in Romes referred to their city’s smoke cloud as gravioris caeli (“heavy heaven”) and infamis aer (“infamous air”), and several complaints about its effects can be found in classical writings. The poet Horace (65 BCE
CE 8), for instance, lamented the blackening of Rome’s marble buildings by countless wood-burning fires, while the political leader and philosopher Seneca (4 BCE
CE 65) wrote a letter to a friend complaining of biomass burning (Moseley, 2014). Therefore, the use of wood for domestic use was causing severe degradation of air quality in Rome, probably worse than that experienced today due to heavy automotive traffic. Chemical analysis of a 9000-foot core taken from Greenland’s ice sheet has now uncovered unequivocal evidence of large-scale atmospheric lead pollution in the Northern Hemisphere dating up to 300 BCE. The source has been traced to ancient Carthaginian and Roman mines in Spain (Rosman et al., 1997). Current Trends and Future Developments on (Bio-) Membranes. DOI: https://doi.org/10.1016/B978-0-12-824103-5.00007-3 © 2023 Elsevier Inc. All rights reserved.

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2

Chapter 1

In the Medieval age, interesting documents related to air pollution can be found, especially in London, where the use of “soft coal” caused heavy pollution and for this reason its use was prohibited in 1273. Surprisingly, in 1670, Honoratus Fabri described damage on fruits by acid rain drops “. . .Due to their great capacity, the fruit is burned, desiccated or undergoes spot lesions or other damage”; a long time before acid rains developed in industrialized countries (Camuffo, 1992). In recent times, the evolution of air pollution was clearly related to industry, traffic, and other sources, including natural sources. Nevertheless, the lessons to be learned from the past by historical review are that air pollution is not new for humans and that air quality has been a problem for many thousands of years. No definition of air pollutant is simple as it could appear. In fact, an “air pollutant” is any airborne substance that has the capacity to adversely impact human health and ownership or to impact other environmental components of the Earth’s biosphere. However, often, we do not exactly know the nature of pollutants, nor the amounts of that pollutants that are dispersed in the atmosphere. Air pollution is also a complex issue that sometimes is much simplified using models that include emissions, transport, and effects on several targets. Emissions of pollutants are not a unique feature by human activities, but also include a series of sources of nonanthropogenic origin that inject pollutants into the atmosphere. This can be defined as “natural pollution,” which, very often, is as dangerous as the anthropogenic one. Moreover, a clean atmosphere contains species that react with both anthropogenic and natural emitted chemical compounds, degrading some of them to harmless species. With the same mechanisms, new species are formed that may be characterized by definite harmful effects on environmental targets. Therefore, natural and anthropogenic emitted species become indistinguishable and become mixed together, causing damage in several environmental compartments. This means that both anthropogenic and natural emitted species change their chemical and physical properties during transport in the atmosphere. At the end of those processes, the structure and chemical nature of pollutants are modified and the original natural or anthropogenic characters are, in most cases, completely lost. The balance between human and natural influence on atmospheric constituents is the real target of our discussion. A good example of how nature and anthropogenic sources are mixed up is given by the heavy pollution experienced in the Po Valley, e.g., the northern part of Italy, depicted by satellite in Fig. 1.1. Frequent ground-based thermal inversions and intense emissions caused by traffic, industry, and other human activities, cause air pollution events with many exceedances of limits and standards related to nitrogen dioxide (NO2) and particulate matter (PM). The figure shows a picture where snowy mountains surround the Po Valley, while the flat is covered by a curtain of fog containing high concentrations of PM and other polluting species.

Environmental air pollution: an anthropogenic or a natural issue? 3 The purpose of this chapter is to put in evidence the complexity of the emission, transport, and removal processes from the atmosphere and to describe, through several examples, how nature interacts with man-made pollution and how, depending upon the chemical species, pollutants cause negative interactions with environment, materials, and human. In order to give an idea about the relative emissions of pollutants, it is interesting to look at the estimation of emissions of the most significant pollutants, as reported by Seinfeld and Pandis (1998), condensed in Table 1.1.

Figure 1.1 Air pollution in Po Valley: How SeaWiFS satellite saws the air over the Plain of Lombardy in northern Italy on January 2020 (NASA copyright). Table 1.1: Estimated emissions of most significant air pollutants. Species

Anthropogenic

Natural

Units

SO2

160

35

Tg (S) yr-1

NOx

100

56

Tg (N) yr-1

NH3

30

15

Tg yr-1

NMHC

150

1200

Tg yr-1

PM

650

3000

Tg yr-1

Note: NH3, Ammonia; NMHC, nonmethane hydrocarbons; NOx, nitrogen oxides; PM, particulate matter; SO2, sulfur dioxide.

4

Chapter 1

Table 1.1 shows that most SO2 is emitted by industry and power generation, while most NOx is from industry, power generation, and transportation. NH3 mainly comes from agriculture, while biomass burning is responsible for most black carbon (BC) and organic carbon (OC) emissions. It also shows that, at a global level, natural emissions are by far higher than anthropogenic emissions. However, while natural emissions are widespread, anthropogenic emissions are concentrated in relatively few locations (cities, industries, etc.), where local concentrations become higher. Anthropogenic emissions are distributed among several types of sources, such as industry, traffic, and agriculture, which are responsible for the emissions of most criteria pollutants, that is, pollutants for which limits and standards are defined by most legislations. However, air pollution also has been including chemical species that are causing cancer and for which limits do not exist, since a minimum concentration, below which no effect is observed, cannot be defined. For these species, some target values or recommendations are available to protect, to a large extent, the general population. Table 1.2 shows some information for the limits of most important pollutants, or their classification related to cancer (European Commission, 2008; IARC Working Group on the Evaluation of Carcinogenic Risks to Humans, 2016; IARC Scientific Publication, 2016), where carcinogenic species are in red background and noncarcinogenic are in blue. For carcinogenic species, classification by IARC is also given. Sources include the most relevant ones. Limits in atmosphere are given in units μg/m3 (micrograms per cubic meter) and the range is considering different integration periods (e.g., hourly, daily, year, etc.). For carcinogenic species, Group 1 means carcinogenic to humans; Group 2A, probably carcinogenic to humans; Group 2B, possibly carcinogenic to humans; Group 3, not classifiable as to its carcinogenicity to humans; Group 4, probably not carcinogenic to humans. It is also interesting to look at the time evolution of anthropogenic emissions extended in the future. Several authors in several studies have attempted such an estimation. Table 1.3 reports the estimation from Pozzer et al. (2012). Estimations in the above table are very much affected by the development of the global economy and by unexpected achievements in technologies. However, it is possible to predict that the emissions of most pollutants will increase at global levels. This is mainly due to the contribution of developing countries, while in developed countries a decrease in emission burdens is expected (see, for instance, Amman et al., 2012). Another aspect to take into consideration is the mean lifetime of the pollutants in atmosphere. In fact, species with a high time residence affect the environment more than species with a low lifetime. Table 1.4 shows some typical lifetimes for the most important air pollutants (Garrels et al., 1973). They range from few hours to several years, while highly reactive radicals have lifetimes as short as a few seconds.

Environmental air pollution: an anthropogenic or a natural issue? 5 Table 1.2: Limits and cancer classification for some important pollutants. Species

Typical limits (µg/m3) or

Sources

IARC classification

Sulphur Dioxide

Industry, energy, space heating

Nitrogen Dioxide

Transportation, industry, energy 40–200

Benzene

Transportation, industry

5

Carbon Monoxide

Transportation, industry

10

Lead

Transportation, industry

0.5

Particulate Matter PM10

Industry, transportation

40–50

Particulate Matter PM2.5

Industry, transportation

20

Ozone

Reactions in atmosphere

125

Polycyclic Aromatic Hydrocarbons Transportation, industry

40–350

Group 2A/2B/3

Nitro-Polyciclic HC

Industry, reactions in atmosphere Group 3

Bitumen

Industry

Group 2B/3

Benzene

Transportation, industry

Group 1

Asbestos

Industry

Group 1

Radon

Soil natural emission

Group 1

Diesel engine exhaust

Transportation

Group 2B

Titanium Dioxide

Industry

Group 3

Sulphur Dioxide

Industry, energy, space heating

Group 3

Thrichloroethylene

Industry

Group 2A

Carbon Black

Transportation, combustion

Group 2B

1-3 Butadiene

Transportation, industry

Group 2A

Vitreous fibers

Industry

Group 2B/3

Styrene

Industry

Group 2B

Involuntary (Passive) smoking

Indoor pollution

Group 1

Formaldehyde

Industry, reactions in atmosphere Group 1

Table 1.3: Emission of some anthropogenic air pollutants in the years 2005
2050 at global level (Tg/year). Years Species 2005

2010

2025

2050

NOx

92.3

99.1

126.2

167.2

SO2

132.0

157.0

192.2

263.9

CO

587.0

615.8

746.8

849.7

BC

6.0

6.0

6.9

7.6

PM

18.6

18.8

21.7

26.6

BC, Black carbon; CO, carbon monoxide.

6

Chapter 1 Table 1.4: Concentration and estimated resident time of atmospheric trace gases and elements. Species

Concentration

Residence time

Ammonia (NH3)

5 ppb

3–4 months

Nitrous Oxide (N2O)

250 ppb

12–14 years

Nitrogen Dioxide (NO2)

2 ppb

1–2 months

Nitric Acid (HNO3)

PM2.5

Mobile Sources

Ultrafine PM

NO

NO3-

Health

NO2

Biomass Burning

Material Damage

SO2

Reduced Sulphur

SO42-

VOC

Staonary Source

Vegetaon

CO

NH3

Biogenic Sources

CO2

NH4+

Climate

GHGs

Other effects Heavy Metals

Figure 1.7 Scheme for multisource and multiple adverse effects of air pollution.

ground to the free troposphere where most of the targets are present and where the totality of human emissions is present, mixed up with the major natural sources of pollution. To comment on the sources of pollution, as we said before, they are conventionally divided into natural and anthropogenic sources. Among these, is worth studying Table 1.6, which shows the type of emission and the primary emitted species. Table 1.6 shows that most pollutants are emitted by several sources, either natural or anthropogenic. For instance SO2 is a typical species emitted by industry, volcanic activity, and burning of biomass or waste. Combustion processes, occurring in cars and trucks motors emit NOx. Some pollutants that have definite health effects are multisource, that is,

24

Chapter 1 Table 1.6: Type and sources of natural and anthropogenic emissions. Sources

Type

Primary Pollutants

Industry-plants, landfills, mining, diffuse, fugitive dust

SO2, NOx, PM, HCl, VOCs; PAH, Metals, PCB, CO

Cars, ground transportation, ships, aircraft

NOx, CO, VOCs, PAH

Burning

Open burning, incinerators, biomass

SO2, NOx, PM, HCl, VOCs; PAH, Metals, PCB, CO

Volcanic

Volcanoes, fumaroles, geological

SO2, PM, Radon, Metals

Ocean

White caps, gases from bio activity

Sulphur compounds, PM

Vegetation

Leaves and roots emissions, forest burning

NOx, VOCs, PAH, PM

Dust storms

Desert storm, dry terrains

PM

Fires

Grass fires, forest fires

NOx, VOCs, PAH, PM

Stationary Anthropogenic Mobile

Natural

Emissions

emitted by several sources. This is the case of PAH (poly aromatic hydrocarbons), a family of substances including some carcinogenic species, or metals, emitted by volcanoes and by industrial activities. To have a sufficiently complete idea about the sources of pollutants, it is useful to make reference to Fig. 1.8, which shows the time evolution of pollutant emission by anthropogenic sources, according to the main source sectors and in world regions during the three decades between 1990 and 2010 (Amman et al., 2013). For those individuals interested in a better space and time definition of sources of air pollutants, it is recommended to refer to EDGAR from the European Commission (2011). As expected, while CO 2 shows an important increase during the time under consideration, the major pollutants in combustion sources (SO 2) substantially decrease, mainly thanks to Western countries where efficient control systems have been adopted. The decrease of SO 2 in Western countries, is partly compensated by its increase in Asia (mainly in China and India). Most NOx is emitted by transport and energy production in Western and Asian countries. Globally, the emission of NO x remains almost stable. Carbon-containing PM (BC and OC) was mainly emitted by residential combustion (e.g., wood) and most of it is assigned to Asian sources. Very interesting is the trend of ammonia that is mainly due to due to Asian emissions in the agricultural sector. The database is, at present, available in sufficient detail, accuracy,

Environmental air pollution: an anthropogenic or a natural issue? 25 CO2 [Pg CO2]

NOx [Tg NO2]

SO2 [Tg SO2]

35

120

120

30 25 20

100

100

80

80

60

60

40

40

20

20

15 10 5 0 1990

2000

2010

0 1990

2000

4.00 3.00

0 2010 1990

2000

Rest of the world

35

120

120

30 25 20

100

100

80

80

60

60

40

40

20

20

15 10 5 0 1990

2000

2010

0 1990

2000

Other

2.00 1.00 0.00 2010 1990

2000

Asia & Pacific

5 4 3 2

0 2010 1990

2000

Transport

60 50 40 30 20 10 2000

0 2010 1990

2000

2010

N. America, Europe, Russia

7 6

1 0 2010 1990

NH3 [Tg NO3]

OC [Tg] 16 14 12 10 8 6 4 2 0 2010 1990

OC [Tg]

BC [Tg]

NOx [Tg NO2]

SO2 [Tg SO2]

CO2 [Pg CO2]

BC [Tg] 7.00 6.00 5.00

2000

Residential combustion

16 14 12 10 8 6 4 2 0 2010 1990

Industry

NH3 [Tg NO3] 60 50 40 30 20 10

2000

0 2010 1990

2000

2010

Energy

Figure 1.8 Time evolution of anthropogenic emissions by source sector and world regions in the period 1990
2010.

and precision to be used for air pollution climate and modeling. Also, this information is available for all sources emission sectors.

1.4 Evolution of pollutants in the atmosphere In this section we will go into some detail about the cycle of air pollutants (emission, transformation, transport, and deposition). Generally speaking, the air pollution cycle can be simply and schematically represented by Fig. 1.8, which includes emission sources, chemical transformations in the atmosphere, transport over short or long distances and, finally, deposition to ground. The latter includes the development of health or environmental effects (Fig. 1.9). The scheme described in the Fig. 1.9 is general. However, it can be adapted from the local to global scale by changing the details of the individual processes. For instance, air masses dominate hemispherical transport of air pollutants transported over the hemisphere. Emissions caused by desert storms (in this case PM is generated) are transported for several thousand kilometers, as well as plumes related to ozone and precursors. Since air masses transported over long range distances also contain species relevant for their environmental

26

Chapter 1

effects, transport and deposition cause pollution in locations very far from the emitting sources., such as the case, for instance, of mercury contamination or pollution by POPs (persistent organics pollutants such as dioxins) (see National Research Council, 2010). Fig. 1.10 shows a simplified mechanism for the intercontinental transport in the Northern Hemisphere, explaining how pollutants released, for instance, in Asia affect the

PRIMARY & SECONDARY POLLUTION

Emissions

Deposion

Deposion

Deposion

Emissions

Transport

GROUND ENVIRONMENT (SOIL & WATERS)

Figure 1.9 General scheme of air pollution evolution.

H

L

H

L

Figure 1.10 Mechanisms and dominant processes for long range transport of air pollutants (Green: lifting processes in troposphere; yellow: advection in troposphere; red: Westerly winds in free troposphere). Background picture by Gerd Altmann (Pixaby).

Environmental air pollution: an anthropogenic or a natural issue? 27 environment in North America and even in Europe. The dominant processes are related to westerly winds coupled to lifting processes occurring on low pressure (L) systems and subsidence occurring on high pressure (H). Most of the lifting and subsidence are occurring within the boundary layer extending from the ground to about 3 km in elevation. Even in this case, air masses can be enriched by local emissions or impoverished by deposition, so that the final effects of the air masses on a given site will depend upon many and, sometimes, unpredictable variables. In this example, we have neglected the troposphere
stratosphere exchanges. The processes governing the diffusion and transport of pollutants are thus complex, depending upon chemistry, meteorology, and type of target. Thus no complete description and analysis of such processes is easy and details of the evolution of air pollution in the vicinity of the sources will be given.

1.5 Air pollution and polar regions Our considerations on air pollution and its effects on the environment bring us to an important question related to the fate of pollutants when transported at long distance. To provide an answer to the questions, it was decided to give a brief description of air pollution in the two most remote sites of planet Earth, that is, the Arctic and Antarctica. Polar regions are considered unique natural laboratories and significant indicators of global change, particularly, the climate change. Climate change and the increase in air pollutant emissions have led to considerable impact on the Arctic and Antarctic environments because of the extremely low levels of pollutants. Polar climate records reveal pronounced warming trends and human and environmental implications and climate feedbacks in the Arctic and Antarctic regions, warrant urgent attention (Meredith et al., 2019). The consequences of an increase in global temperatures and local changes in precipitation and snow cover are not yet fully understood, but lead to the melting of polar ice, permafrost, and glaciers, the retreat of sea ice, and sea-level rise, resulting in increases in the emissions of greenhouse gases such as methane (CH4) and carbon dioxide (CO2) to the atmosphere and changes to the radiation balance. The warming of both the polar environments is also expected to result in further changes in surface
atmosphere exchange of chemical gaseous and particulate compounds and atmospheric composition. Therefore, transport of atmospheric pollutants in polar sites is expected to play an important role in global changes. Recent studies have produced increasing evidence that chemical interactions between the atmosphere and falling snow, deposed snow, and snowpack are far more abundant in polar regions (Domine´ & Shepson, 2002), and lead to the accumulation of snow contaminants on the surface. Solar irradiance can consequently trigger photochemical reactions of these trace constituents in the snow. These processes result in the formation of gases, including

28

Chapter 1

nitrogen oxides (NOx), nitrous acid (HONO), halogen species (e.g., BrO and Br), organic compounds (e.g., formaldehyde, HCHO), and hydrogen peroxide (H2O2), which subsequently are released into the overlying atmosphere altering the overall budgets of radical HOx (OH 1 HO2), NOx, and ozone (O3) with important implications for climate processes. These include atmospheric oxidation and aerosol formation in polar regions, where anthropogenic pollution is considered small (e.g., Beine et al., 2006; Dibb et al., 2002; Ianniello et al., 2002, 2016; Spataro et al., 2017). Due to the role of nitrogen oxides in determining the oxidation capacity of the troposphere, being linked to reactions involving ozone, hydrocarbons, and halogens, knowledge of their natural background concentration is pivotal in determining their influence on the polar boundary layer photochemistry and in judging the impact of human activity on the oxidizing capacity of the Earth’s atmosphere. In particular, the main sources of NOx to the troposphere are fossil fuel combustion, biomass burning, microbial activity in the soil, and lightning, with a small contribution from downward transport from the stratosphere and high-flying aircraft (Fowler et al., 2013). The sources of nitrogen oxides in the polar regions are different from those in other regions, because the Arctic and Antarctica are sparsely populated and are the farthest places from human activities. Air pollution in the Arctic originates primarily from mid-latitude anthropogenic emission regions in Asia, Europe, and North America or from boreal or agricultural fires. Sources of local anthropogenic pollution (e.g., vehicle emissions, domestic heating, shipping, oil, gas, and petroleum extraction, metal smelting, and mineral extracting) (Schmale et al., 2018) are also important, but they are poorly quantified. Local natural emissions from boreal forest fires, vegetation (tundra and forests), ocean, volcanic eruptions, resuspended dust from volcanic ash sediments, and glacial deposits are also important sources of air pollutants. Conversely, the levels of pollutants in Antarctica are, in general, lower than elsewhere in the world. Antarctica is a cold continent; it has little precipitation, no industry, and only a few human settlements. The pollutants present in Antarctica are therefore mainly transported from far away (in the atmosphere from South America or by ocean currents) and partly originated from local sources due to research station activities, cruise ships, and aircraft (Ahn et al., 2019).

1.5.1 Renitrification of polar atmosphere Furthermore, a new significant local and natural source of reactive nitrogen species (NOx and HONO) that can dominate atmospheric photochemistry in polar regions from anthropogenic influence (Grannas et al., 2007) is attributed to nitrate (NO32) photolysis in the snowpack under sunlight conditions (Fig. 1.11). The effects of NO32 photolysis have

Environmental air pollution: an anthropogenic or a natural issue? 29

Figure 1.11 Simplified mechanism of reactive nitrogen species in polar regions.

been observed particularly strongly in Antarctica, where the shallow boundary layer leads to concentrations of NO as high as 500 ppt (Davis et al., 2001). Photochemical production of NOx and HONO depends on the NO32 concentration in the snowpack, on the snowpack properties, and on the intensity of solar radiation within the snowpack. The following simplified mechanism proceeds via these pathways (Grannas et al., 2007): 2 NO2 3 1 hν ðλ . 295 nmÞ-NO2 1 O
2 3 NO2 3 1 hν-NO2 1 O P

(R1.21)

2 NO2 2 1 hν-NO 1 O

(R1.22)

2 NO2 2 1 OH-NO2 1 OH

(R1.23)

(R1.20)

30

Chapter 1 1 NO2 2 1 H -HONO ðpKa 5 2:8Þ

(R1.24)

O2 1 H1 -OH

(R1.25)

It appears from laboratory studies that the (R1.20) exceeds (R1.21) since NO2 is the principal product of NO32 photolysis. The (R1.21) is followed by nitrite (NO22) photolysis (R1.22) producing nitrogen oxide (NO). Alternatively, NO22 can react with oxidants such as O3 or OH (R1.23), regenerating NO2. Considering the significant role of HONO in the atmospheric processes as a major and, sometimes, the dominant source of hydroxyl radicals (OH), several mechanisms have been proposed for its formation in polar sites. Under acid conditions, NO22 in the snow can be protonated to produce HONO (Beine et al., 2006), which is released into the gas phase (R1.24). Alternatively, HONO can be formed by the recombination of NO (R3) and OH, resulting from the protonation of O2 (R1.25) produced from (R1.20) and (R1.22): NO 1 OH-HONO

(R1.26)

However, these pathways (R1.26) are unlikely to occur because the concentrations of OH and NO are insignificant in polar regions. OH, as is well-known, is a key oxidant in the troposphere, causing the removal and formation of harmful photooxidant pollutants such as O3 and PAN. PAN is the major reactive nitrogen reservoir species. Other nitrogen-containing species are included in NOy, that is, NOy 5 NO 1 NO2 1 PAN 1 other organic nitrates 1 HNO3 1 HONO 1 N2O5 1 particulate nitrate, etc. PAN in polar region accounts for up to 80%
90% of the total NOy budget (Beine & Krognes, 2000). Long-range transport is the main source of PAN in polar troposphere is due to its long lifetimes at cold temperatures. The thermal and photolytic decomposition of PAN during spring can be an important NOx source in the Arctic due to increased warming and solar radiation, and thus may have an important effect on NOx budget and on ozone production and destruction in the polar troposphere. In addition to its role in tropospheric photochemistry, PAN (and organic nitrates) can contribute directly to snowfall nitrate, and thus it can be an important source of NO32 on the snow surface. However, inorganic nitrogen compounds, such as nitric acid (HNO3), and NO32 particles are likely the predominant precursors of snow NO32 because they can return to the snow surface by dry or wet deposition and continue to participate in the photochemical cycles. Those processes are schematized in Fig. 1.10, which shows the main paths and reactions occurring in polar atmospheres with the mediation of snow. Long-range transport provides NOx and NOy that are deposed on the ground. Here, liquid or quasiliquid phase reactions generate nitric and nitrous acid in addition to NOx. These species leave the soil to continue the reaction chain in the atmosphere leading to the formation of ozone and the formation of OH radicals.

Environmental air pollution: an anthropogenic or a natural issue? 31 Similarly, OH radicals produced by NO32 photolysis in the snowpack (R1.20 and R1.25) can oxidize OM (e.g., humic material, particles) producing oxidized organic species such as formaldehyde (HCHO) and other carbonyl compounds (e.g., acetaldehyde, CH3CHO; acetone, CH3COCH3): OM 1 OH-HCHO

(R1.27)

HCHO is the most abundant carbonyl compound in the troposphere produced by the oxidation of hydrocarbons. In remote troposphere, methane oxidation is the major HCHO source. Several studies in polar regions have shown that the methane oxidation and snow emissions dominate the HCHO budget. In addition, HCHO is also an important precursor of radical species (HOx, RO2) because of its photolysis, contributing to the oxidant capacity of the atmosphere, especially in polar regions. Although HCHO is believed to be formed photochemically within the snowpack (Hamer et al., 2014), the mechanism is currently unclear. In conclusion, it was thought that the conversion of nitrogen oxides into nitrate ion (NO32) would simply mean irreversible nitrogen deposition. The studies above demonstrate that the processes previously shown are significant for a “renitrification” of the atmosphere. The same processes are also significant in other latitudes when snow fields are formed in wintertime. Such a process may change the oxidation processes occurring in the atmosphere, leading to the formation of OH radicals, that is, the true vacuum cleaner of the atmosphere (Wang et al., 2011). According to this mechanism, snow fields in high elevation mountains may generate OH radicals, which rapidly remove most pollutants from the atmosphere, making it very clean.

1.5.2 Role of halogens and mercury Elevated levels of molecular halogens, such as Br2, Cl2, and BrCl, have also been found in polar regions. Recent laboratory and field studies have shown that snowpack photochemistry leads to their production during spring, but the formation mechanism remains uncertain (Peterson et al., 2019; Pratt et al., 2013). The possible sources of reactive halogen species are from sea salts either in the aerosol particles or on the ice/snow surface, and the decomposition of organohalogen species. Reactive halogen species, especially bromine species (Br and BrO) contribute to tropospheric ozone depletion events, which significantly change the OHx budget, and thus the oxidizing conditions of the polar boundary layer. The major reactions involved in polar halogen cycling, are summarized as follows (where X 5 halogen): X2 1 hν-2X

(R1.28)

X1O3 -XO1O2

(R1.29)

XO 1 XO-X1X1O2 or X 2 1O2

(R1.30)

32

Chapter 1

The final effect is a destruction of tropospheric ozone. In particular, in polar regions, high levels of bromine species could also lead to a considerable oxidation of HCHO or other carbonyls: Br 1 HCHO-HBr 1 CHO

(R1.31)

BrO 1 HCHO-HOBr 1 CHO

(R1.32)

The HBr (and similarly HOBr) is readily solubilized in PM yielding bromide (Br2) ions in solution. In acidic aerosols, HOBr reacts with Br2 to produce Br2, which escapes into the gas phase and is photolyzed: Br2 1HOBr1H1 -Br2 1H2 O

(R1.33)

Br2 1 hν-2Br

(R1.34)

In this manner, the bromine atom (Br) is regenerated, sustaining the O3 loss cycle (R1.28
R1.30). Furthermore, halogen species can deplete atmospheric gaseous elemental mercury (GEM or Hg0) accelerating the accumulation of mercury in polar regions. Mercury (Hg) is a global toxic pollutant for humans and for the environment. It is emitted from both natural (wildfires, volcanoes and geothermal activities, weathering of rocks and soils, and emissions from oceans) and anthropogenic sources (AMAP/UNEP, 2013). Most mercury in the air is in the form of GEM, which can be globally transported to polar regions because of its long residence time (about 1 year) (Selin, 2009). Hg(0) is then oxidized to reactive and water-soluble gaseous and particulate phase divalent species (RGM or Hg(II) and reactive particulate mercury (RPM or Hg(p)), respectively that are quickly deposited or scavenged from air within hours or days (Lindberg & Stratton, 1998). Once deposited on environmental surfaces as snowpack in polar regions, mercury species can be reemitted to the atmosphere through volatilization and (photo)reduction processes (Ferrari et al., 2005) or converted to highly toxic methylmercury (CH3Hg) species in snowpack where they are preserved until entering the surface waters via snowmelt, and thus bio accumulating in the aquatic food chain (Driscoll et al., 2013). However, these atmospheric processes (oxidation pathways, chemical composition of oxidized mercury species, associated oxidation kinetics, and subsequent scavenging and deposition, reemission and accumulation) are still only partially understood (Angot et al., 2016). Several studies have shown that the oxidation of Hg(0) occurs at a large scale in polar regions, contributing to both high atmospheric concentration and significant deposition of RGM and RPM species during the springtime (Kamp et al., 2018). These phenomena are the so-called “atmospheric mercury depletion events (AMDEs)” and can lead to an estimated deposition of about 100 tons of mercury per year to the Arctic (Durnford & Dastoor, 2011).

Environmental air pollution: an anthropogenic or a natural issue? 33 In addition, during these events tropospheric concentrations of both GEM and ozone are significantly and simultaneously reduced because of the photochemical formation of bromine atoms in polar regions (Kamp et al., 2018). As said before, after the photochemical production from snowpack, gas-phase Br2 photolysis produces Br atoms (R1.28) that react with O3 producing BrO (R1.29) and involving O3 destruction. Recently, it was shown that these produced Br atoms dominate the oxidation mechanism in the destruction of GEM (Wang et al., 2019), as follows: Hgð0Þ 1 Br 1 M-HgðIÞBr 1 M

(R1.35)

HgðIÞBr 1 M-Hgð0Þ 1 Br

(R1.36)

HgðIÞBr 1 Br-Hgð0Þ1Br2

(R1.37)

HgðIÞBr 1 Br-HgðIIÞBr2

(R1.38)

Hg(I)Br is unstable, and thus it can produce Hg(0) by thermal decomposition (R1.36) or by reaction with Br atoms (R1.37), but it can also be oxidized into Hg(II)Br2 (R1.38). Consecutively, these oxidized Hg(II) species (RGM) can directly either deposit to snow/ice surfaces or convert into particles (Hg(p)) that subsequently undergo deposition into polar environments. Glaciers, firn, and snow in the polar regions also provide unique records of past climate and composition of the atmosphere and give insight into the past atmospheric oxidative capacity (Wolff et al., 2008). Ice core records for various reactive atmospheric species of photochemical interest, such as CO, NOx (using NO32 as proxy), CH4, HCHO, and H2O2, have been developed for assessing changes in the oxidation capacity of the atmosphere and analyzing the past climatic and environmental changes, including the impact by human activities. In particular, recent lead measurements in basal ice from Greenland (McConnell et al., 2018) in the Arctic and the Mont Blanc glacier (Cold Du Dome, French Alps) (Preunkert et al., 2019) indicated significant metal pollution during the Roman Republic and the Imperial periods due to lead mining and smelting operations during European antiquity. Furthermore, these measurements with atmospheric transport modeling showed that European lead emissions varied with historic events, including imperial expansion and wars, reaching a maximum under the Roman Empire. Thus ice records used to track global climate change reveal lead emissions generated by mining operations in Northern Europe. In fact, these emissions can reach remote areas such as the Arctic and accumulate on the snow’s surface. Then, this accumulated snow can turn into ice and preserve the ice record that stretches back thousands of years. The increase in human activities and the increase in air emissions from local and long-range transport sources are the most important factors affecting the Antarctic. In particular, polar sites act as sinks for various contaminants originating from more temperate latitudes. These contaminants include persistent organic pollutants (POPs), heavy metals, radioactive and

34

Chapter 1

acidifying substances causing environmental risks due to accumulation in soil, ice/snow, sediments, and food (Grannas et al., 2013). Especially, scavenging and remobilization of POPs by snow deposition and melting under the global climate change condition may enhance the pivotal impact on driving POP exchange between environmental media. In fact, due to its large surface area, snow is an efficient scavenger for POPs in the atmosphere, particularly at temperatures below 210 C and can adsorb a significant quantity of these high boiling compounds. While aging, the snowpack may release scavenged pollutants through snow melt causing bioaccumulation in the polar organisms or emission of contaminants in the lower layers of the atmosphere. Wind speed has also been identified as a key factor influencing the extent of the potential emission from aging snowpack (Kallenborn et al., 2012; Potapowicz et al., 2019). Accordingly, quantitation of the snow
air exchange is deemed important to better understand the environmental fate of POPs in polar regions.

1.6 Conclusions The occurrence of atmospheric pollution in remote and presumed unpolluted sites as result of worldwide processes is the best demonstration on how primary and secondary pollution of both natural and anthropogenic origin mix together and affect locations where air pollution is rarely considered to be a problem. While several species are responsible for climatic changes, many others are changing the chemical properties of the atmosphere, generating acid deposition, PM, and oxidized species that are capable of interacting with locally emitted pollutants. This further demonstrates that immediate action to control the adverse impacts of expanding human activities on remote environments is needed, so much attention to pollution should be addressed also in locations where air pollution is supposed to be low. However, most people exposed and affected by air pollution are living near the sources, so our attention will move on to air pollution in urban or industrial sites.

Acronyms BC EEA EU GEM IARC IPCC NMHC, NMVOC OC OM PAH PAN

Black Carbon European Environmental Agency European Union Gaseous Elementary Mercury International Agency for Research on Cancer Integrated Pollution Prevention and Control Nonmethane Hydrocarbons Organic Carbon Organic Matter Poly Aromatic Hydrocarbons Peroxy Acetyl Nitrate

Environmental air pollution: an anthropogenic or a natural issue? 35 PM POPC POP RGM RPM SOA VOC WHO

Particulate Matter Photochemical ozone creation potential Persistent Organic Pollutant Reactive Gas Phase Mercury Reactive Particulate Mercury Secondary Organic Aerosol Volatile Organic Compounds World Health Organization

List of symbols J Ki λ

Photolysis rate Reaction rate for reaction i Wavelength

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3855.

CHAPTER 2

Environmental air pollution: near-source air pollution Ivo Allegrini1, Antonietta Ianniello2 and Federica Valentini3 1

ENVINT srl, Montopoli di Sabina, RI, Italy, 2CNR, Institute of Atmospheric Pollution Research, Rome, Italy, 3Department of Chemistry, University of Rome 2 Tor Vergata, Rome, Italy

2.1 Introduction Processes involving atmospheric pollutants are causing several problems. Climatic change is just one of the most considered. However, other effects such as acid deposition, ozone transport, and formation of harmful particulate matter are equally important. In addition to these effects, air pollution is the major problem for people living near emission sites. This is because concentrations of air pollutants in these locations may be so high as to cause important health problems to the general population. Near-source pollution is typical of locations where several emissions are located such as urban sites, industrial settlements, and so on. The intensity of those emissions often causes high concentrations of one or more pollutants, resulting in a health risk to the population. However, people living in polluted areas are not affected only by locally emitted pollutants, but also by species transported from long distances. Fig. 2.1 shows a typical near-source pollution in an urban or an industrial environment. The concentration levels of a given pollutant are the result of a combination of “regional pollution,” which is caused by transport and diffusion from other locations, including the remote ones. This value is usually quantitatively low compared to the level caused by local sources. Then, industrial or urban emissions, when diffusing over the territory contribute to the “city increment,” which means pollution that is evenly space distributed; also called “city background pollution.” In addition, near emission sites such as heavy traffic roads or industrial settlements, there is a further increment in concentration which is referenced as “street increment” in the case of urban pollution and, generically, defined as a “hot spot.” The simple scheme reported in Fig. 2.1 shows that the evaluation of expected concentrations (and expected effects) of pollution in a given site requires extensive and complex instrumental monitoring or the adoption of mathematical models, which, in turn, require a detailed knowledge of the chemical and physical parameters affecting the emission, dispersion, and transformation of pollutants. Therefore, it is essential to introduce, Current Trends and Future Developments on (Bio-) Membranes. DOI: https://doi.org/10.1016/B978-0-12-824103-5.00002-4 © 2023 Elsevier Inc. All rights reserved.

39

40

Chapter 2

Figure 2.1 Contribution of different scales of pollution to local pollution.

at least summarily, a brief discussion about the variables that define the evolution of a pollutant in the atmosphere.

2.2 Near-source chemical and physical parameters In order to describe these variables in qualitative and semiquantitative or empirical terms, we may introduce a generic function: Ci ðtÞ 5 f ðEi ; ω; Pi ; Qi Þ 1 Adv

(2.1)

with Ci(t) the time-dependent concentration of the i-th pollutant. Ei, is a parameter which depends upon emission intensity (mass of pollutants emitted per unit area). The parameter ω describes the dispersion capacity of the atmosphere, thus it is related to meteorological evolution. The terms Pi and Qi consider the formation and the removal of the pollutant through chemical reactions or by deposition. Adv includes advection of pollutants by medium-long range transport. Eq. (2.1) explains very well why in polluted cities two diurnal peaks are observed for most primary pollutants, especially for those emitted at ground level, like CO (and many other primary pollutants). In fact, in this particular case, the term Adv can be neglected and the equation reduces to: @C 5 αEðtÞ 2 βC @t Where α and β are parameters related to meteorological situation. The morning peak is caused by intense emissions due to local traffic during rush hours, so the emission term

(2.2)

Environmental air pollution: near-source air pollution 41 αEðtÞ is higher than the term βC; thus it is dominant, giving a positive derivative, hence an increase in concentration. The evening peak is due to the same reason. In the afternoons, the reverse is true, thus the concentration decreases because of the higher value of the term βC: Therefore, the modulation of air pollution depends on emissions, but also upon a parameter strictly dependent upon the meteorological conditions. To understand the physical significance of the terms α and β, it is sufficient to zero the emissions. In this case (Eq. 2.2) becomes: @C 5 2 βC @t

(2.3)

C 5 C0 exp ð2 βtÞ:

(2.3a)

which can be easily integrated giving

Then, the physical significance of β is the rate at which air concentration is reduced by clean air intrusion. This process is caused by turbulence and results in a clean injection from aloft to the ground diluting the emitted pollutants. This is the process that occurs in the afternoon when the mixed layer rises up to several hundred meters. Unfortunately, air pollution management does not follow these simple rules and often improperly acts. For instance, several municipalities, on political pressure because of the high pollution values detected in their sites, have decided to stop traffic during the day, for instance, between about 10:00 to about 18:00. This means that emissions are regulated when natural turbulence is naturally reducing concentrations. This is the reason why the final effects of these measures are poor. If the concentration of primary pollutants needs to be decreased, emissions should be controlled during atmospheric stable conditions, that is, when turbulence is low. This means that the control should be effected in the early morning and in the late afternoon. The above simple model equation becomes complex when involving chemical reactions depleting the concentration of a pollutant or increasing its concentration through the formation of new species (secondary pollutants). In these cases, Eq. (2.2) becomes: X X @C Li 1 Adv 5 αEðtÞ 2 βC 1 Pi 2 @t

(2.4)

P P Li are the rate of formation and removal respectively of the species of where Pi and interest. It would be interesting to describe some of these terms for the reactions involving nitrogen oxides: X   (2.5) Pi 5 P1 1 P2 1 P3 5 k1 ½NO½O3  1 k2 ½NO RO2 1 k3 ½NO2 ½O2  X Li 5 L4 1 L5 5 k4 ½NO2 ½OH  1 k5 ½NO2 [uv (2.5a)

42

Chapter 2

Chemical terms in the two above equations are the chemical formation of nitrogen dioxide according to the reactions: NO 1 O3 -NO2 -k1

(R2.1)

NO 1 RO2  -NO2 1 RO -k2

(R2.2)

2NO 1 O2 -NO2 -k3

(R2.3)

and the chemical removal of NO2 according to the reactions: NO2 1 OH -HNO3 -k4 (R2.4)   NO2 1 hυ-NO 1 O 3 P -k5 (R2.5) P Writing Eq. (2.5), we neglected the contribution to Pi due to deposition of NO2 on the ground (later on we will see how NO2 deposition is very important for the formation of nitrous acid). In addition, we also neglected the contribution of Eq. (R2.3) (direct oxidation of nitrogen monoxide to dioxide by oxygen) since the reaction rate at ambient conditions is very low. [uv in Eq. (2.5a) is the intensity of solar irradiation useful for the photodissociation of nitrogen dioxide. Eq. (R2.4) is active under intense solar irradiation during the formation of radical OH•. Eq. (R2.2) is active only in atmospheric stability conditions. In fact, under turbulence, the dilution of the atmosphere decreases the concentrations of radical RO2•, therefore decreasing the reaction rate for NO2 formation. Eq. (R2.1) is important only during unstable conditions because during atmospheric stability, primary pollutants deplete ozone. Finally, Eq. (R2.5) is not active when solar irradiation is low, that is, during nighttime or in the early morning. Eq. (2.3), although complex, is useful for the interpretation of air pollution processes. However, it is still incomplete since it lacks the term related to the removal of pollutants caused by deposition. Most air pollutants, either in gas or particulate phase, tend to react on real surfaces where they are usually absorbed. The process is normally irreversible and causes a decrease of the pollutants concentration C. For this reason, it can be described by a simplified reaction according to which the pollutant A in the gas phase is changed into an irreversible absorbed species A . A 1 M-A

(R2.6)

For similar reactions, we can write: S 5 Vd C

(2.6)

S is the mass flow rate of pollutants from the atmosphere to ground, which linearly depends upon the concentration C. Vd has dimension [LT21], i.e., the dimensions of a velocity. This is the reason why the term Vd is called deposition velocity. Its value depends upon the nature of the pollutant and the nature of the surface. It shows numerical values ranging from 20 to 1023 cm/s. High values are typical of reactive pollutants such as HNO3, while low values are typical of inert

Environmental air pollution: near-source air pollution 43 pollutants like CO or particulate matter in the micron or submicron size. The introduction of deposition velocity completes (Eq. 2.3) into a more general equation: X X @C Li 2 Vd C 1 Adv 5 αEðtÞ 2 βC 1 Pi 2 @t

(2.7)

This equation is useful because it introduces the possibility of explaining and predicting semiquantitatively the evolution of pollutants, especially those emitted at ground level. The chemical terms have been described before; only the terms α and β require more attention. As we have shown above, the term β is related to the dilution process in the atmosphere due to turbulence, that is, the dilution with aloft air, while the term α is less obvious to perceive. This term is clearly related to the dilution of emissions; hence, it is, like β, related to atmospheric turbulence.

2.3 Thermal structure of the troposphere Wind shears remove pollutants from the sites of emissions. However, in addition to horizontally directed winds, pollutants can be removed by vertical winds caused by turbulence. This is a complex phenomenon which may be described in a simple form. It sometimes happens, in particular meteorological conditions, that the temperature aloft is higher than that on the ground. This phenomenon, in which the vertical thermal gradient is positive, is called thermal inversion. This is because, normally, the temperature aloft is lower than that at ground level, as shown in the Fig. 2.2, which approximately represents the temperature of air masses at different elevations.

Figure 2.2 Typical thermal structure of the troposphere. The blue line is the adiabat, usually occurring in the late morning. The red line shows instability, while yellow and violet lines represent a situation in which ground inversion is occurring.

44

Chapter 2

Temperature vs. elevation is normally characterized by the so-called dry adiabat in which the gradient @T=@h is, on the average, 6.5 K/Km corresponding to a decrease in temperature of 0.6 C/100 m. The red line is a thermal structure typical of an unstable situation, while the yellow and violet lines represent stable conditions in which the temperature increases with height, hence making stable the troposphere and causing high pollution concentrations. Thus, by knowing the vertical structure of the atmosphere, it could be possible to understand if we are in stable or unstable conditions. Thermal inversion events occur with more frequency and greater intensity during the winter and with periods of atmospheric stability, and can originate both on the ground and at high altitude. In the first case (radiation inversion), during the winter days, the sun irradiates the Earth’s surface for a few hours and radiation arrives at a lower angle than in the summer. The Earth therefore does not accumulate large quantities of heat starting from sunset, it is quickly released by radiative emission to the outer space, with consequent fast cooling of the Earth’s surface. The mass of air that is in contact with the ground also cools rapidly, reaching temperatures lower than that of the upper layers. Therefore, a situation is created in which the temperatures in the plains are lower than those measured in the hills or mountains. The phenomenon tends to persist during the night and reaches its peak in the hours around dawn (violet line). The clear sky conditions and the absence of wind, which, by stirring the air, could even out the temperatures, favor the stabilization of the event. Clear sky and low winds are typical of high-pressure systems. In fact, pollution episodes are mostly occurring in wintertime during high-pressure conditions since these are the best conditions for causing atmospheric stability. Daytime insolation can usually “break” the thermal inversion layer (and reestablish the negative thermal gradient), which, however, may be formed again in the following night hours. In the presence of intense phenomena, it is possible that the thermal inversion persists for several consecutive days, especially during the anticyclonic conditions of the winter period, bringing the accumulation of pollutants, humidity, and a consequent very poor air quality. Thermal inversion is also generated in the presence of snow: due to its high albedo, the snow strongly reflects the incident solar radiation, making it impossible for the sun’s radiation to heat the ground. At sunset, the irradiation of the Earth’s surface is extremely low and the layer of air in contact with it cools quickly, assuming a lower temperature than that present at higher altitudes. The thermal inversion that originates at high elevations (subsidence inversion) is caused by atmospheric subsidence, which means the descending movement of air masses typical of anticyclonic conditions (high pressure), linked to mesoscale atmospheric circulation. Here, the air descends in the central area of the anticyclone and, as the altitude decreases, it heats up because it is subjected to adiabatic (without heat exchanges) compression (Fig. 2.3).

Environmental air pollution: near-source air pollution 45

Figure 2.3 Development of an inversion layer by subsidence.

This layer is stable compared to the classic upward convection motion and does not allow vertical mixing. In the lower layer, that is, the colder one, often fogs and mists originate and, in the vicinity of large urban areas, the lack of mixing of the air does not favor the dispersion of pollutants that remain “trapped” in the lower layer, worsening the quality of the air. A similar phenomenon of thermal inversion occurs in the mountain valleys: the slopes, at sunset, cool down quicker than in the valley. Cold air, denser and heavier, descends along the slope and “undermines” the warmer air, which, in turn rises in altitude. In this way, the thermal inversion originates and in the valley the temperatures are lower than at the top of the slopes. The effect is very remarkable considering that the temperature gradient between the air aloft and the flat sometimes is larger than 10 C instead of a negative gradient of a few degrees (C6.5  K/Km) for the dry adiabat. The effect of thermal inversion at high elevation on air pollution is determined by the development of a mixed layer extending from the ground to several hundred meters. In this layer, pollutants are trapped and diluted in a large volume of air, then the resulting pollutant concentrations rarely reach alert values. In contrast, when the inversion layer is based on the ground (ground-based inversion) air pollutants are trapped in a small volume of air and the resulting concentrations may largely exceed the air quality standards. Summing up the above discussion, we can conclude that the radiation and subsidence inversions are responsible for the thermal structure of the atmosphere which can be efficiently generalized and depicted according to Fig. 2.4. During the day, heating of the surface develops a mixed layer that extends to several hundred meters in elevation (from 1 to more than 3 km). At sunset, the rapid cooling of the surface determines the development of a stable layer, which extends from ground to a few hundred meters and, sometimes, even less. In this stable layer, pollutants are not dispersed and their concentration becomes high. The mixed layer developed in the afternoon becomes a residual layer in which pollutants continue their chemical evolution. After sunrise, the

46

Chapter 2 Free Atmosphere Entrainment Zone

Capping Inversion Entrainment Zone

Mixed Layer

Residual Layer

Mixed Layer

Stable Boundary Layer Surface Layer

Noon

Surface Layer

Surface Layer

Sunset

Midnight

Sunrise

Noon

Figure 2.4 Structure of planetary boundary layer. Adapted from Stull, R. B. (1988). An introduction to boundary layer meteorology (pp. 666). San Diego, CA: Academic (Stull, 1988).

stable layer breaks up and turbulence dilutes pollutants in the mixed layer. Then, the pollutant concentration decreases to relatively low values.

2.4 Elevated emission sources In the previous chapter, a brief description of air pollution modulation in a typical day has been given. Strong atmospheric stability is resulting in air pollution episodes, while an unstable atmosphere causes an efficient dilution of pollutants released from sources on the ground. However, such a simple concept cannot be adapted for elevated sources. This is the case of industrial stacks for which pollutants can be released at elevations higher than 200 m. This elevation is, in most cases, higher than the mixed height observed in night-time stability conditions. The effects of a pollution plume released by an elevated source are therefore affected by the emission strength and the thermal structure of the atmosphere differently from that described for ground emissions. Fig. 2.5 schematically shows some typical behavior of stack plumes according to the variation of temperature with height, which are sketched on the left of the Figure and according to different temperatures along the day.

Environmental air pollution: near-source air pollution 47

Figure 2.5 Smoke plumes emitted by elevated sources along the day (Un 5 Unstable; St 5 Stable; Neu 5 Neutral). Blue lines show adiabatic lapse rate and red lines simulates environmental lapse rates).

48

Chapter 2

Starting from the top, the first case (04:00) shows the injection of a plume into a strong stable layer, as indicated by the thermal structure characterized by a ground inversion. This is the worst situation for pollutants emitted at ground level, but not for those emitted ad high elevation. Here, stability prevents diffusion up and down, so that the plume is spreading only sideways and therefore not affecting people living on the ground. Thus the plume is opening horizontally like a folding fan causing a shape called “fanning.” At 10:00, there is a stable layer aloft that cannot be penetrated by the plume. This situation arises when there is ground inversion at the ground. At sunrise, heating from solar radiation generates a progressively thicker layer until the plume is reached. At this point, the plume enters a mixed layer where it can easily reach the ground causing exposure to people. This effect is called “fumigation” and causes high levels of pollution by emissions from the stack that reach the ground in undiluted conditions. When the atmosphere is unstable at 14:00, “looping” is developed. In this case a strong atmospheric instability is experienced, and the dynamics of air parcels affect the plume. (these parcels go up and down according to turbulence). When the turbulence is particularly strong, the plume is affected in two ways: dilution, since turbulence dilutes pollutants emitted by the stack. However, the plume can be directly pushed in the ground where, for a short time, high pollution can be measured. In these conditions, the average pollution is relatively low, but short-term values may cause problems for pollutants having definite short-time health effects (For instance sulfur dioxide). In the last figure at 21:00, the plume is injected at the top of an inversion layer. It is not mixed vertically, but it spreads upward. “Lofting” is just the term indicating the plume shape, as it is confined aloft without affecting the ground environment. At 18_00, or later afternoon, the atmosphere is neutral, being the temperature structure similar to the dry adiabat. Here, the plume spreads in the horizontal and vertical directions at the same time. As a consequence, the plume assumes a conical form and the effect is called “coning.” In this condition, the plume does not affect people living near the stack. However, those living at higher distances may be strongly affected by the plume that is diluted only by lateral diffusion. In conclusion, the effects of high elevation sources depend on the relative height at which the plume is released into the atmosphere. The effective plume height does not coincide with the stack height. In fact, when the pollutants exit the stack, they are at a temperature higher than that of the surrounding air, causing an upward lifting of the plume. According to the temperature gradient and to the wind speed, the plume rise is developed and should be added to the stack height to obtain the effective plume height (see for instance Leelossy et al., 2014). Models for stack emissions are, in most cases, quite reliable, at least for flat sites and where no disturbing obstacles are present (tall buildings, etc.). In addition, the emission flow rates are well-known since the mass flow rate of pollutants and the mass flow rate of emissions can be calculated by knowing the type of plant and by measuring emissions with dedicated in-stack instrumentation. The same simple approach, unfortunately, cannot be adopted for ground-based

Environmental air pollution: near-source air pollution 49 emissions. In fact, they are mainly related to traffic and space heating, typical of diffuse emissions in cities and conurbations. Although models are available to estimate emissions from those sources, their uncertainty, added to uncertainty on changes in meteorological condition, make urban pollution modeling very complex. For this reason, we will give some information on how to interpret air pollution data gathered from ground-based networks in sites where pollution sources are diffused and emitting at ground or near ground level.

2.5 The use of radon in air pollution data interpretation We can now represent physically the significance of the meteorological related terms α and β in Eq. (2.7) because they are essentially related to the thermal profile of the atmosphere (elevation vs temperature). The problem resides on the fact that that measurement is not simple nor adapted to a simple model like the one described in Eq. (2.7). Therefore, some effort has been spent in the past to develop a relatively simpler approach to the evaluation of meteorological terms. From the above discussion, atmospheric turbulence due to thermal atmospheric evolution shows distinct features, being high in the morningafternoon period and low during nighttime. The term “atmospheric stability”—sometime used synonymously with mixing depth—has been closely linked to pollution exceedance episodes in many urban cities. Numerous metrics of atmospheric stability have been devised and applied with varying degrees of efficacy. However, “a precise definition of turbulence is difficult, if not impossible to give” (Plate, 1982), thus several physically sound approaches were used to provide useful data for air pollution management. The most accurate of these measures are based on the values of, or ratios between, the near-surface temperature and wind speed gradients or their turbulent flux counterparts (Richardson number, Obukhov length, turbulence kinetic energy etc.) (Wyngaard, 1992). However, since these approaches are complex, expensive, and labor intensive, they are also the least common, and are restricted to the duration of specific research campaigns and not for routine management of air quality. In addition, they are not flexible to be used by people responsible for air quality management in urban or industrial settlements. More widely used are measures such as the PasquillGifford radiation and turbulencebased stability classification schemes (Pasquill, 1961). Furthermore, the interpretation of micrometeorological or climatological observations necessary for all of these techniques is obfuscated by variability due to the effects of various mesoscale motions operating in the nocturnal boundary layer, including local drainage flows, nocturnal jets, and intermittent turbulence. This is the reason why several efforts are now addressed to evaluate practices for a direct and simpler interpretation of pollution episodes.

50

Chapter 2

Turbulence-related parameters show minima at nighttime and maxima at midday. This means that turbulence is low at night and high during the day. This in turn means that pollutants released on the ground will increase in concentration in the late afternoon to early morning, while those emitted in late morning to afternoon will be rapidly dispersed by atmospheric turbulence. Depending on the meteorological conditions at the synoptic scale, ground turbulence can also develop overnight. In contrast, atmospheric stability and low turbulence may also develop during the day. This is the worse situation for air pollution since pollutants emitted at ground level are not diluted, thus high values of concentration may be expected. This is the case for foggy locations where fog prevents the heating of the ground and atmospheric stability will remain high. In any case, the interpretation of air pollution events is still a difficult task. A useful method for the indirect evaluation of the degree of mixing of the lower atmosphere consists in determining the natural radioactivity due to products of short-lived decay of radon associated with suspended particulate matter (Allegrini et al., 1994). In fact, radon is an unreactive, poorly soluble, radioactive gas (τ0.5 5 3.82d) that is emitted naturally from the soil surface at a rate that varies slowly both geographically and temporally. The half-life of radon is sufficiently long that it can be assumed to be an approximately conservative tracer over the course of a single night, while being short enough that it does not accumulate in the atmosphere, typically exhibiting an order of magnitude gradient between the atmospheric boundary layer and the lower troposphere. This makes radon a quantitative proxy for near-surface vertical mixing, and becomes independent of micrometeorological or climatological observations. Radon itself is a naturally emitted air pollutant. In fact, this species causes a high number of casualties. According to the US Environmental Protection Agency, radon is the main cause responsible for lung cancer among nonsmokers. Overall, according to EPA (https://www.epa. gov/radon/health-risk-radon) radon is the second leading cause of lung cancer, causing about 21,000 lung cancer deaths every year. Radon is a decay product from uranium (238U), thus it is emitted mostly by materials of volcanic origin (tuff, granite, etc.). Most people are exposed to radon in their homes since this element infiltrates basements and spreads through the living spaces. In locations characterized by a high content of volcanic rocks and sediments, air concentrations may be high (WHO, 2002). As for most air pollutants, the main determining factors controlling the atmospheric concentration of radon, are the emission and the dilution factors. This is just to rewrite Eq. (6.7) as follows: @CR =@t 5 αER ðtÞ 2 βCR 1 Adv

(2.8)

Since the radon is emitted from the subsoil with an emission rate that can be considered to be constant in the space-time scale of a few kilometers, and since it does not suffer from other transformations besides radioactive decay, the atmospheric concentration essentially

Environmental air pollution: near-source air pollution 51 depends on the dilution factors α and β. This means that radon and its decay products can be considered excellent natural tracers of the mixing properties of the boundary layer. Natural radioactivity remains at constantly low values in the events of advection or convective mixing and strongly increases when the atmospheric stability allows the accumulation of radon near the ground. In particular, positive derivatives of natural radioactivity indicate rapid stabilization of the lower layers of the atmosphere, while negative derivatives indicate an increase in mixing properties in the boundary layer. Radon daughters can be easily detected with a dedicated instrument (Perrino et al., 2000). The validity of natural radioactivity as an index of property mixing of the lower atmosphere is exemplified from the time trends shown in Fig. 2.6, which refers to the months of August and December 2001 in the city of Rome (Perrino et al., 2003). From the graphs of Fig. 2.6, it is evident that August, as in general all the summer months, is characterized by an alternation of nocturnal maxima and diurnal minima of natural radioactivity, with a well-distinct modulation between one day and another. This corresponds to alternate nocturnal atmospheric stability and diurnal mixing of convective type. As we said before, this is typical of periods of persistent synoptic high pressure. The conditions of atmospheric stability at night generate the accumulation of radon (positive derivative of natural radioactivity immediately after sunset), while convective diurnal mixing causes its dispersion (negative derivative shortly after sunrise). This condition reflects the dominant situation in the Mediterranean area in summertime. During December, as well as in general during winter periods, high pressure episodes are rare and advection episodes are frequent because of horizontal winds. Advective conditions last several days. During these episodes, natural radioactivity assumes a poorly modulated structure and remains constantly low. Another important difference in the radioactivity trend between summer and winter months consists of different widths of the time window of atmospheric mixing. In the first case (month of August), it goes from 8:00 in the morning to 22:00 or even 24:00, while in the second case (December) it is limited to the period between 12:00 and 18:00. It should also be noted how the values assumed by natural radioactivity in daytime periods are extremely low in the case of August for several hours during the day. This indicates excellent mixing of the lower atmospheric layers. Radon measurements provide just a proxy variable related to atmospheric stability, therefore, according to Eq. (2.1), they provide a useful tool for interpreting data and trends related to atmospheric pollution. This is important for pollutants emitted at ground level, thus important for pollutants representing a serious risk of the population in cities. For instance, Fig. 2.7 shows the concentrations of PM10 in a background station in Rome and the radon trend in November 2004. Radon trend, based on daily average, shows two strong stability periods in the first and last week. Data on PM10 show the same trend, with low values around and below 10 μg/m3. High values are, in contrast, typical of periods with high radon

52

Chapter 2

2500

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1500

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4

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8

9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31

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9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31

DECEMBER

Figure 2.6 Daily trend of natural radioactivity in summertime and wintertime 2001.

concentration. This, and other similar data, allowed the development of atmospheric stability indices, based on natural radioactivity measurements, specifically aimed at the interpretation of pollution episodes related to primary pollutants (Perrino et al., 2001).

Environmental air pollution: near-source air pollution 53

Figure 2.7 Comparison of radon measurements with the daily concentration of PM10 in a urban background monitoring site in Rome.

These indices (ASI) can characterize the atmosphere in terms of its meteorological predisposition at the onset of a pollution event. They are computed according to the absolute values of radon concentration and its time derivatives during particularly significant periods of the day. The comparison of the ASI values with the concentration of a nonreactive primary pollutant (benzene), even for a long time (e.g., year) provides correlation values close to 0.9, showing excellent potential for natural radioactivity in the interpretation of primary pollution events.

54

Chapter 2

Note that no perfect correlation between stability indices values and concentrations of primary pollutants should to be expected. The reason is that the concentration values are not only due to the meteorological factors described by the indices (variations of height of the mixed layer) but also to variations in emission flow, due, for instance, to traffic intensity. A perfect correlation would be observable only in the case of constant emissive flux, just like radon. Reversely, the deviations of the concentration values of primary pollutants from those provided on the basis of the indexes indicate changes in emission flows. This issue is important when interpreting data for the planning of control measures. To present a useful example, the values of benzene in August were lower than those assumed on the basis of the index, because of the lower emission flow that characterizes this period of the year in the city of Rome. While the use of stability indexes for benzene is useful; for particulate matter, the situation is remarkably more complex since the primary component, which has a behavior similar to that of primary pollutants in the gas phase, is added to a secondary component. For this reason, during the summer periods and especially during spring, in which the events of photochemical pollution have an important role in defining the concentration of particulate matter, the Primary Indexes are inadequate to provide a good characterization of the air quality in relation to particle pollution. Nevertheless, the index is useful even in these unideal conditions. For instance Fig. 2.8 shows a plot of air pollution index and the concentrations of particulate matter PM10 in December 2004. The coincidence between the two variables is good, except the first 4 days of the month. That situation is typical of an added source of pollution which is not present during the rest of the month. It was easy to demonstrate that this source was due to the advection of particulate matter from the Sahara Desert. Satellite data confirmed this hypothesis. With a similar technique it is possible to characterize “nontraffic” pollution episodes such as those caused by fireworks or those caused by sea spray. In conclusion, the interpretation of concentration changes with the modulation of radon may allow easy differentiation between anthropogenic and natural events related to air pollution.

2.6 Atmospheric stability and secondary pollutants For secondary pollutants, Eq. (2.4) cannot be reduced to a simple form since the terms Pi and Li cannot be set to zero, as it was done in the case of primary pollutants. Among secondary pollution, ozone and nitrogen dioxide are of primary importance due to their health effects. Moreover, nitrogen dioxide is a precursor of particulate nitrate and nitric acid, while ozone provides OH radicals, which, in turn, degrade VOCs to secondary particulate matter. According to Eq. (2.4), we can write an equation for NO2 as follows: X X @C PNO2 2 LNO2 2 Vd CNO2 1 Adv 5 αENO2 ðtÞ 2 βCNO2 1 @t

(2.9)

Environmental air pollution: near-source air pollution 55

PM10

Rome - Villa Ada

100 90

experimental

80

expected ISA

Pg/m3

70 60 50 40 30 20 10 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 DECEMBER 2004

Figure 2.8 Comparison of index ISA (ASI) and experimental values of PM10 (μg/m3) in Rome, 1994.

This relationship is complex since many variables are present, so we have to spend some effort to simplify it. To start with formation term PNO2 , it is useful to recall the reaction NO 1 O3 -NO2

(R2.7)

The amount of NO2 in the atmosphere depends upon the amount of ozone and nitrogen monoxide. However, in urban areas where high atmospheric stability may occur, this reaction causes strong spatial gradients and, after sunset, even strong vertical gradients. Additional reactions, causing the formation of NO2 are those with peroxides radicals: NO 1 RO2 -NO2 1 RO

(R2.8)

NO 1 HO2 -NO2 1 HO

(R2.9)

In this context, we can neglect the direct reaction between NO and oxygen since it is too slow. Eq. (2.9) shows that the direct emission ENO2 of NO2 merits additional comments. In fact, NO2 shows many exceedances in many cities in Europe and around the world (Faustini et al., 2014). Its origin is mostly secondary, that is, derived by chemical transformation of NO; however some fraction can be directly emitted by combustion sources.

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Chapter 2

Normally, emission inventories report the total nitrogen oxides (NOx), expressed as NO2. The fraction f 5 NO2/NOx changes with the type of source, especially with the type of vehicle since NOx emissions are due to driving conditions, fuel, and other variables. Most models applied to air pollution consider that the amount of NO2 emitted by cars is lower than 5% of the total NOx. However, when this fraction becomes larger, a definite contribution of primary emitted NO2 may change the strategies addressing the control of this pollutant. The development of new engines, as well as of new abatement systems, posed a revision of the composition of NOx according to experimental data. For instance, Carslaw and Bevers (2005) reported an average value of 10.6% of NO2, while recent evidence shows that new diesel passenger cars, both new engine technology and new exhausts after treatments (e.g., catalytic converters) affect the level of NO2 emissions and the NO2 to NOx ratio can vary from 12% to 70% (Pastorello & Mellios, 2016). In conclusion, we may accept that the average direct emission of NO2 is around 10%. This means that the concentration time derivative depends on both emissions and oxidation of NO to NO2. We can simulate the evolution of NO2 concentration considering that a small fraction is coming from direct emission, followed by a drastic increase due to oxidation by ozone and by radical reactions. The latter require photodissociation of ozone or of other species able to provide OH radicals. However, as long as the atmospheric stability during morning hours is maintained, the amount of ozone is low, since it is rapidly consumed by reactions with VOCs emitted by traffic sources or deposed on surfaces. As soon as the atmosphere becomes unstable, ozone starts to mix with pollutants in the stable layer, hence it starts to oxidize NO to NO2 and starts to generate OH radicals if solar irradiation is intense enough. Therefore, while primary pollutants follow the time emission sources and the atmospheric stability, NO2 time evolution is a little more complex, as is shown in Fig. 2.9. Fig. 2.9 shows that NO starts to increase at about 6:00 a.m. as the results of traffic and space heating emissions. However, the increase of NO2 is shifted by at least 2 h. This means that nitrogen dioxide is not emitted as primary pollutants, but it results from the oxidation of nitrogen oxide. However, when NO2 starts to increase, ozone concentration is at the minimum value. Hence, an important question can be raised: which is the oxidant responsible for the formation of NO2 from NO?. The answer to this question may be found in the presence of nitrous acid (HONO) in a polluted atmosphere (Spataro & Ianniello, 2014). HONO may play a key role in tropospheric chemistry due to its role as a source of OH radicals through its photolysis. In fact, photolysis of HONO occurs at wavelengths (300 , λ , 405 nm) higher than those needed for the ozone photolysis. Thus, in the morning hours, HONO provides the OH radicals needed to start oxidation of NO into NO2 through reactions Eqs. (R2.7) and (R2.9). Fig. 2.9 also shows that after reaching a peak in the late morning, NO starts to decrease because of vertical mixing which, in turn, causes an increase in ozone transported to the

Environmental air pollution: near-source air pollution 57 200 180 160 140 120

O3

100

NO

80 NO2x2

60 40 20 0 1 2 3 4 5 6 7 8 9 101112131415161718192021222324

Figure 2.9 Time trend for the concentration of NO, NO2, and O3 on the average day in January 2020 in Milan. Courtesy G. Lanzani, ARPA Lombardia.

ground from the free troposphere. The effect of vertical mixing is also responsible for the afternoon decrease of NO2. When the atmosphere becomes stable in the late afternoon, then NO starts to increase again and ozone drops to very low values. The role of HONO in air pollution is very important since it has been proposed as a toxic and harmful pollutant since it may damage the respiratory system and because it is able to generate mutagenic and carcinogenic nitroso-amines (Sleiman et al., 2010). These are the reasons why HONO has recently gained attention in the management of air quality. The sources of HONO in the atmosphere are various and include direct emissions, although HONO appears to be just a small fraction of total NOx emitted from stationary or mobile combustion sources. Another source of HONO could be the oxidation of NO by OH radicals: NO 1 OH -HONO

(R2.10)

This reaction occurs during the daytime, when OH radicals are high in concentration. However, the reaction is in competition with photolysis and, certainly, it does not occur overnight. The most probable reaction for the formation of HONO in a city like Milan is the heterogeneous conversion of NO2 on real surfaces caused by water yelding nitrous and nitric acids: 2NO2 1 H2 O-HNO2 1 HNO3

(R2.11)

while nitric acid is irreversibly adsorbed on surfaces, nitrous acid is weakly bound and can be easily released and found in the atmosphere. The extension of the reaction of NO2 with

58

Chapter 2

water depends much on the nature of the surface and on the surface-to-volume ratio (S/V), then it is very efficiently developed in shallow ground-based inversions such as in the case of Milan (Febo, Perrino, Giliberti, et al., 1996, Febo, Perrino, Allegrini, et al., 1996). In conclusion, heterogeneous conversion of NO2 into HONO explains very well the main process of air pollution by NO2 found in Milan and in many other city environments. To complete the discussion on pollution by NO2 in urban sites, it is worth considering what happens in the late afternoon when atmospheric stability is prevailing again. NO starts to increase because of the combination of intense emissions and of the increased atmospheric stability. Also, NO2 is increasing due to the oxidation processes continuing in the residual layer. In the late afternoon, ozone concentration drops because of the increased atmospheric stability and the titration of NO into NO2, in addition to ground depletion. For ozone, we may write an equation similar to that developed for NO2. Considering that the direct emission of ozone is zero, and that the reaction with NO (R2.7) is the main removal process for ozone, comparing this equation with that developed for NO2 (Eq. 2.9), and adding up the two equations, we can obtain the time trend of the sum S of ozone and NO2: @S 0 0 5 2 βS 1 2 LNight 2 LS 1 Adv @t

(2.10)

The above equation is still complex to solve. However, in strong advective conditions it is possible to derive some interesting conclusions. In fact, in the case of strong advective conditions, ozone concentration coincides with ozone available in the planetary boundary layer. Here, ozone is spatially homogeneous at a concentration of about 4060 ppb (in southern European regions). In such a condition, the most relevant mass exchange is within the surface mixed layer and the layer aloft causing term Adv to be the dominant one. Consequently, the time derivative @S @t 5 0. This means that the sum NO2 1 O3 5 K is a constant and the value of K coincides with the background value of ozone. A consequence of this discussion is that when the atmosphere is turbulent, total oxidants concentrations approach the value of background ozone. The reverse is also true, that is, when the sum of NO2 and O3 equals the background concentration of ozone, then the atmosphere is turbulent and vertical exchanges are very effective. (Febo, Perrino, Giliberti, et al., 1996, Febo, Perrino, Allegrini, et al., 1996). We can now easily explain some feature of the pollutants trend in urban areas, such as that described in Fig. 2.10, which reports the monitoring of ozone and NO2 in an background station in Rome on May 2526, 1996. The first hours of May 25 are characterized by moderate stability. Here, ground level ozone is consumed and its concentration drops to zero. Also, NO2 is slowly dropping overnight because of nighttime chemical reactions and because of ground deposition. In the morning

Environmental air pollution: near-source air pollution 59

VILLA ADA (ROME) DOAS JUNE 1996 100

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26/05/96

Figure 2.10 The trend of oxidants in a background station in Rome (Spring 1998).

of May 25, NO2 starts to increase, followed by the increase of ozone when atmospheric stability is low. However, the increase in NO2 is occurring some time before the increase of ozone and this means that other species, rather than ozone, are providing the oxidation of NO to NO2 in the afternoon. Radioactivity shows a low value because of turbulence, thus NO2 drops to low values, while ozone reaches a maximum. After sunset, the atmosphere becomes again stable and ozone drops to zero, while NO2 reaches relatively high values. However, during the night, the atmosphere becomes unstable for several hours. During this

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Chapter 2

event, radioactivity is dropping down, the concentration of NO2 decreases because of turbulence, and ozone is transported from aloft. Then, the atmosphere becomes stable again, NO2 increases again while ozone drops to low values. Afterward, the atmosphere becomes mostly unstable and, as a result, the sum of NO2 and ozone is stable. These results demonstrate the high potential of the technique that is based on the measurement of natural radioactivity for the evaluation of the mixing of the lower layers of the atmosphere, and the concrete possibility of obtaining interpretative tools in the short term that are simple and accurate to help the administrations understand the phenomena that regulate pollution in urban areas, for control management and for the evaluation of the effectiveness of the measures.

2.7 Advances in air pollution monitoring 2.7.1 Saturation monitoring Monitoring of atmospheric pollution is challenging for modern technologies. This is because air pollution management requires the accurate and precise knowledge of the function: f 5 Ci ðx; y; z; tÞ and the value assumed at any x,y,z, or t, where Ci is the pollutant concentration; x,y,z the coordinates of the site; and t the time. Function f should be known in sufficient spatialtemporal resolution in order to allow, eventually, proper actions on polluting sources to limit excessive exposure to the population and to the environment. In fact, spatial resolution is in the order of a few meters up, while time resolution is from a few minutes to a few hours. However, as we observed before, this function is very complex as it depends upon the meteorological conditions, upon the emissions and advected pollutants, and upon many other variables. The need for accurate, precise, and sufficiently timespace resolved monitoring can be met by a large number of sensors. Unfortunately, the cost of monitoring is an inherent limit to the number of sensors deployed for monitoring, therefore the concentrations Ci is normally recorded only in a few selected places. The function f is then reconstructed by appropriate spatial interpolation or by integrating monitoring data with results obtained by models. It is quite clear that this procedure cannot represent the function f with enough precision and accuracy in the spatial domain of interest. The most important limitation of an air monitoring system is the cost of the equipment required for the measurement of pollutants concentration, both in investment and in maintenance. This is the reason why the number of monitoring sites (stations) are kept to a reasonably low number. For instance, according to EU legislation, the minimum number of

Environmental air pollution: near-source air pollution 61 monitoring sites for a city like Rome (about 2.9 million people and 1280 km2), is seven for gaseous pollutants and ten for the sum of stations measuring PM10 and PM2,5. (European Union, 2008). This means a spatial resolution of 180 km2 for gaseous pollutants and 120 km2 for particulate matter. Although the Directive fixes the minimum number on monitoring sites, there is a strong need, as said before, to gather data with a sufficiently high resolution, both in space and time. This concept is known as “saturation monitoring” in which a large portion of territory such as a conurbation or an industrial settlement is served by a few standard monitoring stations and a sufficiently high number of low-cost stations dedicated to fill the spatial gaps of the conventional stations. Providing that the low-cost stations are accurate and precise enough, a complete space distribution of pollution can be obtained. The idea was in the past used through the use of passive samplers. As is known, these devices may provide the concentration of several pollutants with a sufficiently high space resolution since their cost is limited. While the standard stations provide accurate measurement at high time resolution (one minute or so), passive samplers provide concentration data averaged over a few weeks (see, for instance, Costabile et al., 2010). The saturation approach enables a detailed knowledge of air pollution evolution in space and also in time, assuming that the time evolution of air pollution from standard stations is adapted to saturation stations. In such a way, monitoring resources are optimized in terms of cost and in terms of efficiency. Monitoring with passive samplers has a time frame of 1530 days and provides the average concentration of several species. Among these, NO, NO2, SO2, and BTX are the most common. Over several months of monitoring, it is possible to derive some statistics about the time dispersion of concentrations, gaining additional useful info about the type of monitoring site (urban, industrial, rural, etc.) and the prevalent sources ( De Santis et al., 2004). Although the use of passive samplers has been shown to be very useful, it is still suffering by definite drawbacks mainly due to the different time response with respect to the standard monitoring method (integrated data vs short-term data). In this case, sensors may offer a great advantage to provide data with a time resolution comparable to that generated by standard instruments. Of course, in order to obtain reliable and useful results, sensors should meet several basic requirements, which are summarized below: 1. Low cost: sensors should be deployed in a high number of sites, thus cost of purchase, installation, and maintenance should be relatively low and consistent with the expected number of sites to be served. 2. Low energy consumption: sites where sensors needs to be operated are not usually served by electric power. Therefore, solar cells and batteries in combination may provide the required energy.

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3. Quality of data: measurement should be accurate and precise in order to provide a homogeneous quality for all sensors involved in. This means that long time drift and other instabilities should be kept to a minimum. 4. Analytical requirements: sensors should be able to operate in a working range compatible with that of standard sensors. For instance, this range can be set between 10% of the enforced limit and two times (200%) the limit itself. 5. Calibration: sensors should be calibrated at least over two levels. The first one should be possibly integrated into the system, while the second one operated externally. 6. Wireless: this is the main feature of sensors intended for integrating a standard monitoring network. Data are needed to be transmitted into a central acquisition system in order to check the quality and to provide further elaboration. Nowadays, there is a huge amount of scientific and technical research toward the ideal “sensor” to be included into existing monitoring networks. Advances in microelectromechanical systems (MEMS) have become a fundamental enabler of miniature, low-cost gas sensors. As MEMS technology improves so do the sensors’ accuracy and reliability. Along with fast response time, these are vital characteristics that determine a gas sensor’s ability to monitor the environment. Analytical performances of a sensor are key parameters for field use since they should be able to cover useful concentration ranges. In order to give a rough estimation of this kind of performance, it would be useful to make reference to the Table 2.1 which shows the European Union limits and standards for some pollutants with the recommended guidelines values from the WHO. Useful sensors should be able to monitor pollutants at least between 10% and 200% of the suggested limits.

Table 2.1: Comparison between EU Limits and standards with WHO guidelines (μg/m3).

Air Pollutant

WHO Guidelines

EU Limits

PM2.5

10 (y), 25 (d)

25 (y)

PM10

20 (y)

40 (y), 50 (h)

Ozone

100 (8h)

120 (8h)

Nitrogen Dioxide

40 (y), 200 (h)

40 (y), 200 (h)

Sulfur Dioxide

20 (d), 500 (h)

125 (d), 500 (h)

In parenthesis the time average: y 5 year, d 5 24 h, h 5 hour.

Environmental air pollution: near-source air pollution 63 Unfortunately, as shown in the table, limits and standards are in the order of few tens of μg/ m3, therefore the required analytical performances for sensors are very strict. In addition, as said before, such strict requirements should be maintained during the sensor life span. For example the IDT’s ZMOD4510IA1R gas sensor module can quantify concentrations as low as 20 parts per billion (ppb). It is optimized for the detection of trace atmospheric gases such as nitrogen oxides (NOx) and ozone (O3). However, according to the previous table, analytical performances are not so good. The digital gas sensor is designed to monitor outdoor air quality according to the Air Quality Index of the US EPA. The sensing element consists of a heater element on a silicon-based MEMS structure and a metal-oxide (MOx) chemiresistor. The signal conditioning IC controls the sensor temperature and measures the MOx conductivity, which is a function of the gas concentration. A microcontroller-based module controls the I2 C communication interface to show the measured output of ozone and nitrogen oxides. Although advanced sensor technology is important, it is not the only thing to determine the final performance of an environmental monitoring system. Improvements in calibration capabilities are another interesting field, and specific designs with regard to the gas type, concentration range, and cost can be the starting point for future development. The firmware improvements also go hand-in-hand with calibration features to help designers to quickly integrate gas sensors into a variety of IoT (Internet of Things) applications. Also, gas sensors on a single chip can be easily integrated into air quality monitoring IoT designs using precalibrated sensing devices with precompiled firmware. These compact sensors are electrically calibrated with standard gas to ensure consistency from lot to lot. Unfortunately, very few sensors show positive features such as those explained before. Especially analytical performances are not yet sufficiently developed to allow candidate sensors to be completely integrated into a modern network. Sensors are only one important part of the complex architecture suggested for a modern monitoring network. In fact, a huge number of sensors would also mean a complex system of acquisition, transmission, and storing of data. This also includes the possibility of extracting environmental information from a complex numerical database. For that, a successful approach would be given by Internet-based algorithms, such as the IoT (Internet of Things). In addition, the development of techniques based on IoT could limit, to some extent, negative features of the sensors since this approach is able to manage a huge amount of information in order that possible corrections to sensor signals can be applied. Finally, monitoring networks are now one technical base to allow citizens to know in real time the degree of exposure to the different pollutants. In the future, people will be less interested in the air pollution of their cities and very much attracted by the possibility of knowing the concentrations of pollutants endangering themselves and their relatives in

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indoor and outdoor. Possibly, this information should be provided by simple tools, such as mobile phones. The development of appropriate sensors connected to mobile phones and the relative applications is the first step toward this goal. The second one is the development of a “cloud” of information in which the user may find data to assist his mobile phone in deriving an accurate and precise pollution measurement. This goal can be achieved through the IoT.

2.7.2 Internet of Things and Information Communication Technologies for sensors Many connected devices are approaching the new Information Communication Technologies due to their networks and services approaches as for their limits and available resources. The new communication technologies provide seamless connectivity, which is the first requirement of IoT. Communication technologies applied in IoT are characterized by low power consumption, low bandwidth used, low computation power, and seamless communication with devices in the environment due to the basic concept of IoT, that is, computing for everyone, anywhere, any network and any service. These technologies are now very much penetrating e-health, e-traffic management, e-environmental pollution management/pollution control, and in the endless e-world. IoT is one of the important new concepts that provides the connectivity of sensors and devices to the Internet, providing connectivity to everyone, anywhere, and anytime. The applications of IoT toward home appliances, vehicles, and the environment are based upon the availability of smart objects that are capable of sensing other objects and are able to communicate and interact with each other, without the intervention or involvement of humans. Here we want to stress and highlight the importance of IoT in terms of different and updated communication technologies, providing IoT techniques as suitable tools for different applications in terms of various challenges in different field applications, especially for environmental monitoring and Air Quality Control. The IoT term was first used by Ashton in 1991. As the technology and implementation ideas are moving forward, the definition of term is evolving (Mihaita, 2019). As a consequence, there are two visions of IoT: 1. Things Oriented vision; and 2. Internet Oriented vision. The first vision involves RFID (radio frequency identification) as a simple thing to be part of the Auto-ID Lab (Automated-Identification Laboratory), while the second vision is based on the network as core technology leading to the Semantic Web. The definitions given above lead the way to the ITU [Telecommunication Development Sector, ITU-T Y.2060 (06/2012)] as a global infrastructure for the information society, enabling advanced services by interconnecting

Environmental air pollution: near-source air pollution 65 (physically and virtually) things based on existing and evolving interoperable information and the communication technologies vision of IoT, according to which: “from anytime, anyplace connectivity for anyone, we will now have connectivity for anything.” After computer, Internet, and mobile communication networks, IoT is a new wave in the information world. The IoT refers to a huge network involving Internet and multiple sensor equipment to collect information (Sarma & Gira˜o, 2009; Wong et al., 2018) The purpose of building such a network is to recognize, locate, track, administer, and trigger the relative events. IoT architecture is basically a three-layered architecture (Fig. 2.11). The functionalities of the layers are: •

•

Perception layer. Object identification and information collection is the main function of this layer. It includes sensors, actuators, RFID tags, RFID readers/writers, and information display units, such as PDA (Personal Digital Assistant), Tablet, PC, and smartphone. Network layer. Information transfer that is collected via the perception layer is the main objective of this layer. Wireless networks, wired networks, the Internet, and network management systems are the major components of the network layer.

Cloud Server Wireless communicaon

Temperature Humidity Pressure

IoT Gateway/Frame work

Moon Lux Sensors

IoT Architecture Figure 2.11 Internet of Things (IoT) architecture.

Mobile app

66 •

Chapter 2 Application layer. Event detection, intelligent solutions, and performance of user required functions is the responsibility of this layer.

IoT deployment is diversifying from consumer-based applications such as smart home devices and wearables to mission-critical applications in the areas of public safety, emergency response, industrial automation, autonomous vehicles, and the Internet of Medical Things. As these mission-critical applications proliferate, engineers and designers must address important design and test considerations and trade-offs from the early design phase to manufacturing outcomes. The top five challenges of designing for IoT, the “5C’s of IoT,” are connectivity, continuity, compliance, coexistence, and cyber security (https://www.cybersecurity360.it/tag/iot/). Connectivity: Enabling a seamless flow of information to and from a device, infrastructure, cloud, and applications is a top IoT challenge because wireless connectivity is highly complex, and dense device deployments further complicate operations. Continuity: Ensuring and extending battery life, one of the most important considerations for IoT devices. A long battery life (or low power consumption) is a huge competitive advantage in consumer IoT devices. Compliance: IoT devices must adhere to radio standards and global regulatory requirements. Compliance testing includes radio standards conformance and carrier acceptance tests, and regulatory compliance tests such as radio frequency, electromagnetic compatibility, and specific absorption rate tests. Coexistence: With billions of devices, congestion in the radio channels is a problem that will only get worse. To address wireless congestion, standards bodies have developed test methodologies to evaluate device operations in the presence of other signals. Cyber security: Most traditional cyber security protection tools have focused on network and cloud. Endpoint and over-the-air vulnerabilities are frequently overlooked. While mature technologies like Bluetooth and WLAN (wireless local area network) are used in many applications, little has been done to address the over-the-air vulnerabilities. The complexity of these wireless protocols translates into potential unknown pitfalls in device radio implementations that could allow hackers to access or take control of a device. The strategic planning and product portfolio of IoT mainly concerns the development for RF/microwave power meters and sensors. Smart sensors are built as IoT components that convert the real-world variable that they’re measuring into a digital data stream for transmission to a gateway. Fig. 2.12 shows how they do this. The application algorithms are

Environmental air pollution: near-source air pollution 67

Figure 2.12 Smart sensor building blocks. Image: rPremier Farnell Ltd.

performed by a built-in microprocessor unit (MPU). These can run filtering, compensation, and any other process-specific signal conditioning tasks. The MPU’s intelligence can be used for many other functions as well to reduce the load on the IoT’s more central resources. Air quality evaluation using fixed as well as mobile nodes of sensors (Ullo & Sinha, 2020) was implemented that was capable of checking the air quality in stationary as well as mobile ways. In this latter case, the compatible sensors were deployed as mobile nodes which can work satisfactorily in a moving environment. Data captured through smart sensor nodes were processed and analyzed with the help of machine learning techniques. Another air quality control process was studied using IoT and machine learning techniques, with a focus on the assessment of air pollution, by deploying gas sensors to help in capturing air particles and analyzing the pollutants mixed in the air. Sensor networks have been established in moving vehicles for monitoring air quality with the help of machine learning; Van and Tham (2018) described the deployment of mobile sensor nodes and WSN (wireless sensor network). Among available sensors suitable for IoT, it is worth recalling that infrared sensors were deployed to evaluate the air quality, especially in analyzing volatile organic compounds (VOCs) (Szulczynski & Gebicki, 2017) with the help of machine learning methods. The elements of VOCs were detected and analyzed using spectroscopic observations. There are a few components present in the air that help assessing the quality of the air. PM2.5, was predicted by Sarma and Gira˜o (2009) using extreme machine learning techniques tested upon spatiotemporal data collected in a certain duration of time over a range of distances covered by the sensors. Different forecasting models were suggested by Shaban et al. (2016) for quality evaluation of urban air, components like O3, SO2 and NO2 were determined, and a comparison was made for the models used in the work.

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A gas sensor-based air quality control mechanism was implemented by Ayele to determine the level of pollution in the air by predicting the pollution value; IoT was employed to analyze sensor data captured through gas sensors. This was primarily used in this work for the detection of pollutants and communicating to a WSN with the help of IoT devices connected across a WSN architecture. A smart air quality monitoring system has been studied using a long range wide area network (Deng et al., 2020), and this work has been very useful for detecting temperature, dust, humidity, and carbon dioxide components in the air. An intelligent air quality system was presented for the detection of CO2, NOx, temperature, and humidity by Rosero-Montalvo et al. (2018) using AI and machine learning techniques for developing expert systems for air quality assessment. Furthermore, PM10, PM2.5, SO2, oxides of nitrogen (NOx), O3, lead, CO, and benzene components were detected, on the basis of machine learning methods trained by spatiotemporal data, by Chiwewe and Ditsela (2016). This was extended using deep learning for the detection and detailed analysis of O3 components only. Another study employing heterogenous sensors was undertaken by Ali et al. (2015). Research trends were also analyzed to assess the quantum of research carried out in the area of SEM (Ullo & Sinha, 2020) and Table 2.2 shows a summary of the quantity of research in this case. The study of trends was made by using a publication search in the Science Direct databases in a year-wise manner. In this analysis, the time period chosen was from 1995 to 2020. It can be clearly seen that the quantum of research has been increasing with the time in both cases, namely research employing IoT, and research using IoT and machine learning. An interesting fact is an outcome of the table: the research using modern machine learning methods is still lagging behind those that do not use any machine learning. According to this review for sensors combined with IoT, in this paragraph two main important cases of studies have been reported. The first one represents the air quality monitoring evaluation that consists of three experimenting protocols: 1. first, fixed passive tubes for the monitoring of the nitrogen dioxide concentrations, placed in strategic locations highly affected by traffic; 2. second, nitrogen dioxide registered by citizens using smart and mobile pollution units carried at breathing level, have been also carried out; and 3. finally, a machine learning model, that works by using decision trees and neural networks on the mobile-generated data, showing that humidity and noise are the most important factors influencing the prediction of nitrogen dioxide concentrations of mobile stations. Passive tubes: The technique (passive sampling) is based on the passive transfer of pollutants by simple molecular diffusion of ambient air to an adsorbent which is specific to

Environmental air pollution: near-source air pollution 69 Table 2.2: Research studies based on purpose and applications of environment monitoring. Research

Purpose

OEM

Oceanic environment

IOT Based SM

Soil monitoring for farming

IoT Protocols for MEM

Marine environment acousc monitoring

IoT for air polluon

Air polluon monitoring system

IoT based SEM

Environmental monitoring

Air quality

Air quality monitoring

Large area monitoring; noisy data; accuracy and cost issues

Polluon monitoring

Air polluon monitoring System

Real me monitoring; accuracy issues

Sensor based AQM

Air polluon monitoring system

SEM

Dust and humidity monitoring

Radiaon

Radiaon monitoring

Aqua farming and energy conservaon

Aqua Farming

Mul-agent supervising system

e-health monitoring system due to temperature and radiaon changes around the surroundings Effect of surroundings during winter season only

Findings and Challenges Light weight; costly and invasive sensory networks Efficient vegetable crop monitoring; Greenhouse gases pose challenges on health of vegetables like tomato Lower latency; low power consumption; installaon and coverage issues Mobile kit “IoT-Mobair” for predicon; inferior precision; low sensivity; computaonally complex W3C standard for interoperability; interoperability issues of heterogeneous sensors

Efficient for low coverage area; low cost; easy to install; less number of pollutants are covered Wide coverage and efficiency; low cost and small size High cost and low stability against temperature variaon Water quality and quanty control; higher carbon emission and energy requirement

Device Used Wireless sensors Wireless sensors WSN and IoT Gas sensor and IoT Heterogene ous sensors Geomacs sensors and IoT Sensors with MQ3 Model, Raspberry Pi and IoT Gas sensor and LASER sensor IoT HPXe chamber Odor, pH, conductance and temperature sensor

Detecon of emergency situaons

Supervising system and AI

Effect of baeries and other radiaon

Wireless sensor network

Climate and ecology monitoring

Study of emissions in the environment

Study of emissions in the environment

Smart city and SEM

Monitoring of data center radiaon

Temperature, humidity and energy consumpon in data centers monitored for smart city and SEM

IoT

ZigBee based environment monitoring

Smart industry environment

To study hazardous effects in industries

ZigBee and WSN LoRa: Long Range

SEM in winter season LoRa technology for climate monitoring

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the targeted pollutants. The concentrations of pollutants obtained by this technique are concentrations averaged over the entire sampling period. This technique has the main advantage of being low cost and not requiring electrical recharge (see, for instance, Costabile et al., 2010). Azimut Station: is a product of Azimut Monitoring which uses electrochemical gas sensors for measuring the NO2 emissions. Through a portable emission analyzer it can provide continuous real-time monitoring of NO2, O3, noise, temperature, and humidity. Smart Citizen Kit: is a crowd-funded product developed by Fab Lab Barcelona at the Institute for Advanced Architecture of Catalonia (Mih˘ait˘a et al., 2019). This low-cost mobile sensing unit can provide real-time data measuring NO2 and CO concentrations, noise, temperature, humidity, and light. Its solar panel and low power consumption, together with an ergonomic design, make it attractive for daily usage. The device streams the data measured by its integrated sensors over Wi-Fi, using the FCC-certified wireless module on the data-processing board. Results can be visualized through the online interface or through a dedicated mobile app. There are many alternatives available to developers needing to monitor indoor and outdoor air quality using cloud-based platforms. Digi-Key’s own Next-Gen Smart Air Quality Monitoring cloud-enabled gas sensor platform combines Cypress Semiconductor’s PSoC 6 microcontrollers with gas and dust sensors from Sensirion. The PSoC 6 microcontrollers provide programmable peripherals to interface with any Sensirion sensor (Sensirion AG, Switzerland).

2.7.3 A modern monitoring network An example of sensors integration into existing monitoring networks is given by the municipality of Beijing (China) where the conventional network for particulate matter PM2.5 has been integrated with low-cost sensors. Fig. 2.13 shows how the region has been divided into cells approximately 3 km2 in size in densely populated areas and 8 km2 in rural or mountain locations, thus providing a satisfactory coverage of the entire province (Li, 2017). In each cell, an optical sensor for particulate matter has been placed. The relatively low cost of these sensors and easy calibration through a dynamic approach are such that the existing monitoring network is now assisted by more than 1500 sensors. QA and QC are the focus of this new approach. Before the installation, strict calibration work was carried out. After installation, the “cloud quality control” model is employed to transfer the quality of the standard station to 1500 small sensors so as to ensure the accuracy of the data of sensors and therefore of the whole network. The availability of optical sensors for PM2.5, based on light scattering, allows semicontinuous measurement of this pollutant almost

Environmental air pollution: near-source air pollution 71

Figure 2.13 Development of high density PM2.5 monitoring network in Beijing (China).

equivalent to the standard method based on gravimetric measurements (measuring frequency: 5 min) In the monitoring network a number of stations equipped with high quality instruments can be used to calibrate the optical sensors in order to provide a homogenous response along the monitoring network. In conclusion, IoT offers important opportunity for monitoring air pollution and the adverse effects on population or vegetation and conservation of cultural heritage. According to this perspective, the development of new sensors is expected in the near future and the integration of several environmental layers is expected to produce in real time the necessary tools to manage the atmospheric environment. Just to give some idea and an example, a very complete network can be assembled around some interconnected layers providing information to be immediately transformed into actions. A scheme for this kind of network includes: • • •

A land use map with emission cadastre directly linked to automatic source monitors and linked to traffic flow. An advanced ground-based monitoring network, linked to meteorological data, provides concentration data for the protection of population. Data on “vertical distribution” of pollutants obtained from satellites, drones, and balloons or obtained by observation on towers at different heights.

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The information can also be shared by the school or public health systems or by any other network contributing to the “smart city.” It is clear that in this kind of structure, the key element is the availability of reliable sensors. This is the goal why nowadays great scientific and technical efforts are aimed to. In line with the above discussion, in Fig. 2.14, we want to give an idea of the concept of a modern monitoring network intended for air pollution. As shown, it is based on several interconnected layers aimed at several parameters related to air pollution and to the environment. Information acquired in the layers is stored, filtered, and managed by appropriate software that returns them, or a combination of them, in a coherent spatiotemporal array useful for people responsible for air pollution management. Layers are connected to a “cloud” that is communicating with individual sensors to ensure the calibration and consistency of data. Personal monitoring devices can use information in the cloud to interpret and correct results from their individual sensors. According to data, people might require air pollution managers to take proper actions for reducing pollution levels with the optimum actions in the proper space or time frame. Direct participation of people to air pollution control options, based on real-time observations, will be a more effective solution to the problem. In Fig. 2.14, it is possible to define more precisely the nature of the layers. For instance, A—data from standard monitoring network (monitoring stations) B—emission inventory C—satellite/airborne observations

A B

Cloud Data & Compung

C D N

Popular Air Polluon Assessment

Air Polluon & Environment Management

Figure 2.14 Concept scheme for a modern air pollution monitoring network.

Environmental air pollution: near-source air pollution 73 D—land use maps N—any other available info for pollution assessment, forecast and prevention Designers of gas-sensing devices for IoT and IIoT (Industrial IoT) devices and systems are moving away from traditional, large, standalone designs. As they do so, they need to look for gas sensing solutions that allow them to improve accuracy, reliability, and response time, along with lower cost and power consumption. All while fully leveraging the capabilities of the IoT, cloud-based data gathering, and analysis platforms. Other core features to look for are interface design, sensing speed, and concentration range. As shown, there are many solutions available that not only meet designers’ needs, but also simplify the integration of these enhanced sensing capabilities in small form factors that are a must for battery-operated devices. They also include calibration capabilities and updatable firmware that are critical for the efficient configuration—and reconfiguration—of air quality monitoring designs. Using these gas sensors, coupled with cloud connectivity, designers can work within highly supportive hardware and software ecosystems to cater to current and future IoT and IIoT design requirements.

2.8 Conclusions The measurement and assessment of atmospheric pollution can now profit of new and numerous tools and infrastructures that only need to be properly used to protect public health. Once again, the need to rationally use the set of information that comes from the detection networks and other observations must be emphasized. This is to better understand the dynamics of the phenomenon and to provide political and administrative decision-makers with the tools and information necessary for managing local emissions and related controls. In fact, many detection networks are limited to the acquisition of pollutant concentrations, but invest little in the overall management of the phenomenon for which rational interpretation of the acquired data is necessary. This, in particular, is necessary for ozone pollution that presents many problems for protecting the health of exposed citizens (WHO, 2020). In fact, the secondary nature of the pollutant and the nonlinear processes of photochemical formation constitute a significant obstacle to controlling the emissions of the precursors. The new networks based on IoT will certainly provide a great step forward in this direction, but an even more decisive step will be given by the availability of tools capable of measuring the concentrations of atmospheric pollutants in the personal environment and therefore directly related to exposure. Currently, many devices are being studied to achieve this goal, but unfortunately their performance, except particulate matter sensors, is not as optimal in terms of sensitivity and accuracy. However, in the development phase there are many types of sensors that, in a short

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time, will be able to provide a decisive contribution in achieving this goal. A large mass of personal data, coupled with data from the detection networks, constitutes the new frontier of monitoring and therefore the new frontier for a substantial reduction in the exposure of citizens.

List of acronyms ASI BTX EU IoT MEMS MPU OTA WHO WLAN WSN

Atmospheric Stability Index Benzene, Toluene, Xylenes (and Other Alkyl-Substituted Benzene) European Union Internet of Things Micro Electro Mechanical System Micro Processor Unit Over-The-Air World Health Organization Wireless Local Area Network Wireless Sensor Network

List of symbols Ci Ei ω Pi Li α β Adv Ki Φ S Vd T h S X,y,z T f

Concentration of the i-th pollutant Emission rate of the pollutant i-th Dispersion capacity of the atmosphere Formation rate of the pollutant i-th Removal rate of the pollutant i-th Atmospheric dispersion parameter Atmospheric dilution parameter Advection term Reaction rate for reaction i Solar radiation flux Mass of pollutant deposed on ground Deposition velocity Temperature height Sum of oxidants (O3 1 NO2) Spatial Coordinates Time Function describing the spatial temporal distribution of a pollutant

References Ali, S., Tirumala, S.S., & Sarrafzadeh, A. (2015). SVM aggregation modelling for spatio temporal air pollution analysis. In Proceedings of the ACM MobiSys 2015 workshop on wearable systems and applications (pp. 249254). Firenze, Italy, 1819 May 2015. Allegrini, I., Febo, A., Pasini, A., & Schiarini, S. (1994). Monitoring of the nocturnal mixed layer by means of particulate radon progeny measurement. Journal of Geophysical Research, 99, 765777. Carslaw, D. C., & Bevers, S. D. (2005). Emission of road vehicle primary NO2 exhaust emission fraction using monitoring data in London. Atmospheric Environment (Oxford, England: 1994), 39, 167177.

Environmental air pollution: near-source air pollution 75 Chiwewe, T. M., & Ditsela, J. (2016). Machine learning based estimation of ozone using spatio-temporal data from air quality monitoring stations. IEEE International Conference on Industrial Informatics, 5863. Costabile, F., Bertoni, G., De Santis, F., Bellagotti, R., Ciuchini, C., Vichi, F., & Allegrini, I. (2010). Spatial distribution of urban air pollution in Lanzhou, China. Open Environmental Pollution & Toxicology Journal, 2, 815. De Santis, F., Fino, A., Menichelli, S., Vazzana, C., & Allegrini, I. (2004). Monitoring the air quality around an oil refinery through the use of diffusive sampling. Analytical and Bioanalytical Chemistry, 378(3), 782788. Deng, F., Zuo, P., Wen, K., & Wu, X. (2020). Novel soil environment monitoring system based on RFID sensor and LoRa. Computers and Electronics in Agriculture, 169105169. European Commission. (2008). Directive 2008/50/EC of the European Parliament and of the Council of 21 May 2008 on ambient air quality and cleaner air for Europe. Official Journal of the European Union, 11 June 2008. Faustini, A., Rapp, R., & Forastiere, F. (2014). Nitrogen dioxide and mortality: Review and meta-analysis of long-term studies. European Respiratory Journal, 44, 744753. Febo, A., Perrino, C., Giliberti, C., & Allegrini, I. (1996). Use of proper variables to describe some aspects of urban pollution, Environment In I. Allegrini, & F. De Santis (Eds.), Urban air pollution: Monitoring and control strategies, in, NATO Advanced Science Institutes Series (8, pp. 295317). Springer Verlag. Febo, A., Perrino, C., & Allegrini, I. (1996). Measurement of nitrous acid in Milan, Italy, by DOAS and diffusion denuders. Atmospheric Environment (Oxford, England: 1994), 30, 35993609. ´ ., Molna´r, F., Izsa´k, F., Havasi, A ´ ., Lagzi, I., & Me´sza´ros, R. (2014). Dispersion modelling of air Leelossy, A pollutants in the atmosphere: A review in cent. European Journal of Geosciences, 6(3), 257278. Li, Y. (2017). Establishment and application of sensor based PM2.5 high density monitoring network in Beijing. In Beijing international forum for metropolitan clean air actions held in Beijing on 89 June 2017. Mih˘ait˘a, A. S., Dupont, L., Chery, O., Camargo, M., & Cai, C. (2019). Evaluating air quality by combining stationary, smart mobile pollution monitoring and data-driven modelling. Journal of Cleaner Production., 221, 398418. Pasquill, F. (1961). The estimation of the dispersion of windborne material. Meteorological Magazine, 90, 3349. Pastorello, C., & Mellios, G. (2016). EEA, Explaining road transport emissions: A non-technical guide, European Environmental Agency. Luxembourg: Publications Office of the European Union. Perrino, C., Pietrodangelo, A., & Febo, A. (2001). An atmospheric stability index based on radon progeny measurements for the evaluation of primary urban pollution. Atmospheric Environment, 35, 52355244. Perrino, C., Febo, A., & Allegrini, I. (2003). “stabilita` Atmosferica ed Inquinamento da Materiale Particolato.” Inquinamento 4751. Perrino, C., Febo, A., & Allegrini, I. (2000). A new beta gauge monitor for the measurement of PM10 air concentration. In J. E. Hanssen, R. Ballaman, R. Gehrig (Eds.), Proceedings of the EMEP-WHO workshop on fine particles-emissions, modelling and measurements (pp. 147152). Plate, E. J. (1982). Engineering meteorology (p. 740) Amsterdam: Elsevier. Rosero-Montalvo, P.D., Caraguay-Procel, J.A., Jaramillo, E.D., Michilena-Calderon, J.M., Umaquinga-Criollo, A.C., Mediavilla-Valverde, M., Ruiz, M.A., Beltran, L.A., & Peluffo-Ordo´nez, D.H. (2018). Air quality monitoring intelligent systemusingmachine learning techniques. In Proceedings of the 3rd international conference on information, systems and computer science (INCISCOS 2018) (pp. 7580). Quito, Ecuador, 1416 November 2018. Sarma, A. C., & Gira˜o, J. (2009). Identities in the future internet of things. Wireless Personal Communications, 49(3), 353363. Shaban, K. B., Kadri, A., & Rezk, E. (2016). Urban air pollution monitoring system with forecasting models. IEEE Sensors Journal, 16, 25982606. Sleiman, M., Gundel, L. A., Pankow, J. F., Jacob, P., III, Singer, B. C., & Destaillats, H. (2010). Formation of carcinogens indoors by surface-mediated reactions of nicotine with nitrous acid, leading to potential thirdhand smoke hazards. Proceedings of the National Academy of Sciences of the United States of America, 107, 65766581. Spataro, F., & Ianniello, A. (2014). Sources of atmospheric nitrous acid: State of the science, current research needs, and future prospects. Journal of the Air & Waste Management, 64(11), 12321250. Stull, R. B. (1988). An introduction to boundary layer meteorology (p. 666) San Diego, Calif.: Academic.

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CHAPTER 3

The environmental pollution’s influence on public health: general principles and case studies Gianfranco Di Gennaro1, Rosa Papadopoli2, Francesca Licata2 and Carmelo G.A. Nobile1 1

Department of Pharmacy, Health and Nutritional Sciences, University of Calabria, Rende, Calabria, Italy, 2Department of Health Sciences, University of Catanzaro “Magna Graecia”, Catanzaro, Calabria, Italy

3.1 Introduction The problem of pollution cannot be defined as a recent problem since it has accompanied the human being from its first appearance on planet Earth. When the fire was lit in the caves it is conceivable that the caveman in contact with the smoke suffered from irritation to the eyes, throat, and airways. Another clue is the blackened lungs of many paleolithic mummified bodies. Lead was used in the everyday life of the ancient Romans and many thousands of deaths have been ascertained to be due to acute poisoning (Borsos et al., 2003). However, as Wilhelm Friedrich Hegel explained 200 years ago, a continuous quantitative increase lead to a final qualitative change, so the polluting insult repeated over time has led to a qualitative transformation of the environment from an entity that supports and nourishes the life of human beings to an enemy from which we have to defend ourselves. The level of environmental pollution will determine quality and life expectancy more than ever in the coming decades, especially in some less developed areas of the world. Taking this into account can have remarkable epidemiological repercussions since 23% of all deaths worldwide and 26% of deaths among children under 5 years old are due to preventable environmental factors. In the first part of this chapter how the different forms of pollution impact on human health will be described, with particular emphasis on air, water, soil, and noise pollution. In the second part of the chapter some case studies will be reported.

Current Trends and Future Developments on (Bio-) Membranes. DOI: https://doi.org/10.1016/B978-0-12-824103-5.00008-5 © 2023 Elsevier Inc. All rights reserved.

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3.2 Air pollution The Organization for Economic Co-operation and Development stated in 2016: by the mid-21st century, unless action is taken on air pollution, we will count one premature death from pollution every 5 s (Air pollution to cause 6 9 million). Even if this estimate is surely inaccurate, there is no doubt that the fight against pollution is probably the most important and perhaps demanding challenge of this century. And if we think that this problem is the preserve of restricted areas of the planet such as India or Southeast Asia, again in 2016, the WHO clarified that air pollution remains the largest environmental health risk in Europe (World Health Organization, 2016). More evidence indicates the direction that the pollution problem has taken: the percentage of people worldwide exposed to a concentration of PM2.5 higher than 35 µg/m3 was around 15% in 2010 and it will reach 30% by 2060. In addition to the increase in PM2.5 we will observe also the doubling of nitrogen oxides by 2060 as well as a considerable increase in ammonia (Air pollution to cause 6 9 million). We will see such marked increases especially because of the ever growing need to transport products, such as agricultural produce, with the consequent need for energy obtained from combustion activities which are the processes that most produce this type of emissions. Unfortunately, the decline in air quality is accompanied by the worsening of other forms of pollution, such as noise and water, mainly due to the increase in urbanization, especially in some areas of the world such as China, the United States, Nigeria, and India (Sun et al., 2020). As for air pollution, the pollutants that have the greatest impact on people’s health, according to the WHO, are particulate matter (PM10, PM2.5, and ultrafine particles), ground level O3, CO, NO, NO2, SO2, and lead. At the molecular and cellular level, the mechanisms of action used by pollutants are different. In the case of O3, the main mechanism is the development within the cells of ROS such as free radicals and hydrogen peroxide (Bocci et al., 1998). These molecules are toxic to human cells through oxidative damage, especially to membrane phospholipids. In humans, an alteration of the permeability of the respiratory epithelium is observed with a consequent decrease in lung function that can lead to edema, but it also exacerbates already present asthma and bronchitis, or causes eye irritation, headache, and weakness (Bromberg, 2016). Oxidative damage plays a central role also for particulate matter. However, the production of ROS in this case occurs following the phagocytosis of the particulate by the inflammatory cellular response, with the consequent release of proinflammatory cytokines which in turn promote the production of other ROS via stimulation of the Toll-like receptors (Boyce et al., 2012; Salvi & Holgate, 1999; Woodward et al., 2017). Also in this case, thanks to this positive loop of oxidation and inflammation, the damage is mainly borne by the respiratory system with the appearance/exacerbation of mild disorders up to COPD and lung cancer (Zhao et al., 2019).

The environmental pollution’s influence on public health 79 NO competes with oxygen in binding with the heme group and therefore interfering with the oxygenation of the organism, but NO poisoning attributable to air pollution is contained. Differently, NO2 on the one hand forms nitrogenous aerosols, which are part of PM2.5, and on the other hand has its own irritating effect on the respiratory system, which has been observed above all in weaker subjects such as children. Moreover, nitrogen oxides also contribute to photochemical pollution, as they are a precursor of tropospheric O3 and easily transform into nitric acid, generating so-called acid rain (Emmanouil & Quock, 2007; Maugh, 1984; Nitrogen Dioxide). As for SO2, the effects are similar to those of the molecules mentioned above, and as for NO2, transforming into sulfate in the atmosphere, it aggregates with the particulates and contributes to acid rain. A possible genotoxicity observed in vitro has been hypothesized for a long time also in humans but fortunately with negative results (Sulfur Dioxide; Ziemann et al., 2010). Also CO is infamous for its strong competition with oxygen in binding the heme group. At low concentrations it can cause fatigue in healthy subjects and possible chest pain in heart diseased subjects. At higher concentrations angina, headache, confusion, and flu-like symptoms are observed. At high concentrations it can be fatal and because of these acute effects it becomes very important in the context of indoor pollution (Rochette et al., 2013). The toxicity of lead is carried out through various mechanisms of action including the reduced synthesis of the heme group, through the inhibition of the enzymes that promote its synthesis such as catalase and superoxide dismutase (Nemsadze et al., 2009). The consequence is, among others, an increase in oxidative stress that leads to neurotoxicity and symptoms ranging from muscle pain, vomiting, to long-term effects including premature births, growth slowdowns, and infertility in adults. Another characteristic of lead is its ability to intervene in the physiology of the bones where it accumulates and where it can lead to a series of impairments ranging from osteoporosis to compromised healing from fractures (Carmouche et al., 2005; Pounds et al., 1991; Puzas et al., 2004). Notable pollutants are also polycyclic aromatic hydrocarbons, volatile organic compounds and dioxins (Health Organization & Office for Europe, 2013; Manisalidis et al., 2020; Page et al., 2020). Other short- and long-term effects related to air pollution in general are hypertension, stroke, myocardial infarction, atherosclerosis, and ventricular hypertrophy. From a neurological point of view we also find a decline in attentional processes and overall cognitive processes, anxiety, depression, and neurodegenerative diseases such as Alzheimer’s and Parkinson’s diseases (Bevan et al., 2021; Bourdrel et al., 2017; Brunekreef & Holgate, 2002; Genc et al., 2012; Leary et al., 2014; Manisalidis et al., 2020; Moulton & Yang, 2012; Palacios, 2017; Shehab & Pope, 2019). Diabetes, apparently unrelated to air pollution, seems also to be associated with long-term exposure to air pollutants. Globally, the current impact of air pollution can be summarized by the increase in mortality observed in areas with higher concentrations of particulate matter and by the global

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estimate of 9 million attributable premature deaths/year (Air pollution to cause 6 9 million; Landrigan et al., 2018). As expected, these effects have different magnitudes depending on the baseline risk level of the reference population and pollutant-specific effects. For example, hospitalization levels attributable to air pollution are higher in the elderly and in particularly susceptible individuals (Kelishadi & Poursafa, 2010). A specific exposure disease association is the high susceptibility of children and infants even to very low doses of lead, which can cause impairments ranging from memory disorders to mental retardation (Bellinger, 2008). It is also important to consider how other factors affect public health when interacting with exposure to air pollutants. For example, overpopulation and industrial development have much greater effects on public health in emerging countries or in those where the socioeconomic level is lower, as reported in Table 3.1, mainly due to the lack of adequate management of the problem. Similarly, the health effects attributable to climate change, such as the spread of diseases transmitted by microorganisms or insects or parasites, are exacerbated by the levels of environmental pollution, since aerosols increase the level of incoming sunlight (Manisalidis et al., 2020). Diet and genetics also interact with environmental pollution damage. A diet low in antioxidants, widespread in all latitudes, is an important risk factor for long-term damage from pollution which, as said above, uses oxidative stress as a mechanism of action. A good example of the intervention of genetics and diet is the effect that supplementation with vitamins C and E seems to have in modulating the effect of ground-level O3 in asthmatic children, but only in those homozygous for the uGSTM1 allele (Romieu et al., 2004). Table 3.1: Percentage of disability-adjusted life-years attributable to air pollution (household air pollution plus ambient air pollution) by disease and country income group.

High income Upper-middle income Lower-middle income Low income Global

Lower respiratory infections (%)

Tracheal, bronchial and lung cancers (%)

Ischemic heart disesases (%)

Ischemic stroke (%)

Hemorrhagic stroke (%)

COPD (%)

Cataracts (%)

12 34

8 30

13 24

9 20

11 24

16 41

1 14

57

38

35

28

31

52

25

64 53

48 24

43 28

36 37

22 27

51 44

35 19

Calculations based on data from the GBD 2015 Mortality and Causes of Death Collaborators (2016): 41 and the GBD 2015 Risk Factors Collaborators (2016): 42. Table from: Landrigan et al., 2018.

The environmental pollution’s influence on public health 81 Indoor pollution, as mentioned above, can sometimes have an even greater impact on human health. Indoor pollutants are both those coming from outside but above all those produced inside buildings. For example the residues of the materials used for domestic hygiene, the tobacco smoke, the CO and the particulate matter produced by the fireplaces, the asbestos fibers released in the older buildings where this material has not yet been removed, or radon that is released in the basements of buildings. Effects on human health range from short-term effects such as the triggering of asthma or allergic reactions to animal fur in apartments, to very pronounced effects such as lethal CO poisoning developed in apartments or carcinomas caused by long-term exposure to asbestos and radon (Assessment of exposure to indoor air pollutants, 1997). Indoor pollution is particularly impactful in developing countries where a high percentage of people use coal, manure, or wood to heat rooms through simple stoves. The consequence is a high risk of COPD or respiratory infections in children. Solid evidence of this type of indoor pollution is the link with perinatal mortality, tuberculosis, nasopharynx, larynx, and lung cancer (Bruce et al., 2000; Gonza´lez-Martı´n et al., 2021). With regard to indoor pollution in the workplaces, in recent decades the cases of cancer linked to occupational exposure have decreased thanks to the protection policies of workers. However, the growing industrialization of developing countries is likely to lead to an exacerbation of the problem (Protecting workers’ health).

3.3 Water pollution Water is another major means by which we come into contact with unwanted substances that can be a risk to our health. Unfortunately, as the old poet said: many have lived without love, none without water. The ways in which water can become contaminated are mainly the use of water for storage and waste removal of the productive processes of worldwide companies. Other sources of water pollution are agriculture, which represents the main contamination of river water, the spread of plastic, garbage, oils, and radioactive waste. Finally, there are countless human activities that indirectly contaminate water, such as fracking as an extraction technique for oil and natural gas (Meng, 2017; Nuccetelli et al., 2012; Schwarzenbach et al., 2010; Vasanthi et al., 2008). The most frequent risk for human health related to water pollution is the ingestion of microplastics. It is estimated that between 1.15 and 2.41 million tons of waste plastic arrive from rivers every year and the majority of the contribution is made by 10 rivers in Africa and Asia (Danopoulos et al., 2020; Lebreton et al., 2017). Europe is not much better since every minute the equivalent of 34,000 plastic bottles are thrown into the Mediterranean Sea (Flawed plastic system hits the Mediterranean). This plastic is not inert and releases micro-

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and nanoparticles that end up in our body through the food chain. A recent estimate tells us that on average we introduce every 7 days about 5 g of plastic into our bodies through food, the equivalent of a credit card (Ma et al., 2020). It is not possible to estimate to date what the long-term health effects will be. Certainly this plastic is involved in inflammatory processes and oxidative damage that accumulate with the insults addressed by other forms of environmental pollution. To aggravate the situation is the fact that this plastic can be a vehicle for toxic additives used during industrial processes such as bisphosphenol-A, phthalates, or other synthetic substances (i.e., dyes) that can be released into the oceans and reach humans through the food chain and cause immunosuppressions and be cofactors of infectious and noninfectious diseases (Campanale et al., 2020; Smith et al., 2018). Recently the role has also been suggested that plastics could play in the spread of pathological microorganisms both by ingestion and even by simple contact. This is particularly important in countries where people still use stagnant water where microorganisms and pathological carrier insects can proliferate. The microbiological risk is particularly high in countries where water sanitation methods are not applied and where there are no adequate sewage drains (Yang et al., 2020). In these scenarios, fecal oral infections are very common, often leading to diarrhea and fever but also respiratory dermatological problems. Particularly impacting are the gastrointestinal disorders caused by environmental pollution. Among these, diarrhea is particularly impactful, representing the eighth highest cause of death for all ages in the world and the fifth highest cause of death in children under 5 (Troeger et al., 2018). In Table 3.2, reported by Pru¨ss-Ustu¨n et al. (2014), a retrospective estimate of the burden attributable to diarrhea due to poor water hygiene is indicated. Also in this case the inverse proportionality between the number of deaths and income status is evident (Pru¨ss-Ustu¨n et al., 2014). Regarding chemical forms of water pollution, there are countless substances that can represent a risk of intoxication in humans. For example, acute mercury poisoning in water is well described, which can lead to shock, cardiovascular collapse, acute renal failure, and severe gastrointestinal damage (Rehman et al., 2018). However, the most recurring problem is related to long-term exposure of polluted water that can lead to damage in all areas of the body through various forms of cancer, functional damage, and mental impairment (Jaishankar et al., 2014). Today about 0.5 0.7 million deaths per year are estimated to be linked to soil contamination, heavy metals, and other chemical pollutants present in water (Landrigan et al., 2018). A particular form of mixed chemical microbiological pollution causing damage, even if indirectly, is that of antibiotic resistance. In most urban areas, hospital and domestic wastewater are combined in treatment plants. In a context such as this, a transfer of genetic material from antibiotic-resistant strains to other microorganisms is observed

The environmental pollution’s influence on public health 83 Table 3.2: Diarrhea deaths attributable to the cluster of inadequate water, sanitation, and hand hygiene. Inadequate water, sanitation, and hand hygiene Region Sub-Saharan Africa America, LMI Eastern Mediterranean, LMI Europe, LMI South-East Asia Western Pacific, LMI Total LMI

Inadequate water and sanitation

PAF (95% CI)

Deaths (95% CI)

PAF (95% CI)

Deaths (95% CI)

0.61 (0.55 0.66) 0.46 (0.36 0.50) 0.58 (0.47 0.66) 0.35 (0.28 0.46) 0.56 (0.36 0.70) 0.44 (0.31 0.54) 0.58 (0.48 0.65)

367,605 (326,795 402,438) 11,519 (9310 13,616) 81,064 (65,359 94,707) 3564 (2462 4678) 363,904 (225,359 477,720) 14,160 (10,035 18,009) 841,818 (699,059 963,626)

0.5 (0.47 0.55) 0.32 (0.28 0.34) 0.47 (0.40 0.53) 0.19 (0.19 0.27) 0.45 (0.31 0.57) 0.29 (0.23 0.33) 0.47 (0.40 0.53)

307,493 (276,989 335,899) 8125 (7101 9158) 6570 (55,266 75,876) 1970 (1654 2280) 291763 (193,198 383,423) 9429 (7519 11,242) 684,479 (580,456 780,463)

LMI, Low and middle income; PFA, population-attributable fraction. Table from: Pru¨ss-Ustu¨n et al., 2014.

(Fouz et al., 2020; Hutinel et al., 2021; Kaur et al., 2020). While this phenomenon may seem secondary and indirect, it will surely contribute to the estimated 10 million deaths that antibiotic resistance will cause each year by 2050, surpassing deaths due to cancers (de Kraker et al., 2016; O’Neill, 2014). The problem of water pollution affects the entire oceans. Oil disasters have been reported several times, for example, that of the oil tanker Deepwater Horizon which, following a fire on board, spilled between 5 and 10 million liters of oil into the Gulf of Mexico in 2010 (Liu et al., 2020). But overall the greatest danger in the oceans is represented by the contamination of marine fauna with methylmercury coming from the combustion of coal, which can reach the oceans from the air through atmospheric events but also from spills of metal mining and industrial activities (Landrigan et al., 2020). The ingestion of methylmercury through the consumption of contaminated fish, shellfish, and clams increases the risk of cardiovascular disease and dementia in adults (Mozaffarian, 2009). Exposure in utero through ingestion by the mother is also linked to damaged brain development of the fetus, reduced IQ, and increased likelihood of autism, ADHD, and learning disorders (Landrigan et al., 2020). In addition to the discharge into the oceans of plastic (10 million metric tons per year spilled into the seas) and of chemical pollutants

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coming mostly from industry that takes advantage of poor control by the authorities, a concrete danger is also represented by the so-called harmful algal blooms, uncontrolled growths of algae that find fertile ground in polluted waters. In many cases these algae can produce toxins which according to recent estimates cause up to 60,000 intoxications/year with symptoms ranging from diarrhea to neurotoxicity (Grattan et al., 2016; Landrigan et al., 2020).

3.4 Noise pollution Noise pollution can be interpreted as a particular type of air pollution. Very often it is seen as a secondary problem, but it is still a phenomenon that affects about 10% of the world population and that causes at least 1 million disability DALYs (Daniel, 2007). This burden is attributed to ischemic damage ascribable to noise (61,000 years), 45,000 to cognitive impairment in children, 903,000 to damage from sleep disturbance, 22,000 to tinnitus, and 654,000 to nuisance from noise pollution (George et al., 2013; Jarosi´nska et al., 2018). Most of the effects listed above are caused by the increasing traffic of congested urban areas. The damages attributable to noise pollution can be classified as auditory and nonauditory. Auditory effects are mainly related to hearing loss. It is shared in the literature that an average yearly noise due to loud conversations or a noisy office (about Lden 55 dB) is the threshold above which noise-related disturbances can appear. Moreover hearing loss occurs mainly due to a loss of sensitivity of the cochlear cells which cannot have remission since they are not regenerative cells. The noise-induced hearing-loss has long been a problem related to precarious working conditions and even if today this aspect has improved in most of the western countries, in the United States it still represents the largest occupational disease with a recent estimate that 22 million people are exposed to hazardous noise levels at work and that nearly $250 million are spent annually in the United States for the treatment of damage due to hear loss (Noise & Hearing Loss Prevention). Furthermore the increasing urbanization of the planet is ensuring that the global incidence of hearing loss is not decreasing. Unfortunately, the results of this condition are not only related to the quality of life of those affected, but also secondary to it, such as road or domestic accidents. The other main auditory disturbance attributable to noise pollution and which is often reported in combination with hearing loss is tinnitus and the marked decline in the quality of life of those who suffer from it (Bhatt et al., 2016; Yankaskas, 2013). An important aspect that emerges from the literature in relation to noise damage is that all age groups are affected and that the effect of the damage is cumulative. In young people, hearing loss is very often only temporary, for example due to participation to rock concerts or the extensive use of headphones for listening to music. However, even if the damage can

The environmental pollution’s influence on public health 85 occur at a young age in a subclinical way, it can become particularly disabling at an advanced age (Ecob et al., 2011; Kujawa & Liberman, 2006). Other risk factors that can promote hear loss are blood sugar, smoking, and alcohol consumption. Heredity is also of particular importance since it can explain up to 50% of the individual variability of hearing loss and represents a predisposition on which exposure and the risk factors listed above play their role (Kumar et al., 2013; Nemati et al., 2018; Samokhvalov et al., 2010; SliwinskaKowalska & Pawelczyk, 2013). The nonauditory disturbances related to noise pollution are distributed along a wide spectrum. The simple annoyance linked when unwanted noise is prolonged over time can lead to problems caused by the same mechanisms linked to stress, from alterations of the emotions that manifest themselves with displeasure or anger, up to the involvement in the onset of ¨ hrstro¨m et al., 2006). More seriously sleep disturbances depression (Muzet, 2007; O attributable to noise pollution have the most impact on people’s quality of life. Exposure exceeding 33 dB can induce nocturnal awakenings and in general alterations of the sleep structure, based on individual susceptibility (Basner et al., 2006). This can lead to short-term effects such as impaired mood or daytime sleepiness, but also to deeper effects such as cardiometabolic alterations. For example, it is well-described in the literature that noise pollution is indirectly linked to endocrine alterations, overeating, and obesity by altering sleep. These impairments related to sleep disturbances are added to the direct effects that noise has on the cardiovascular system through the activation of the autonomic nervous system with an increase in systolic, diastolic pressure, and heart rate, and with long-term consequences, including serious ones such as hypertension, ischemic damage of the myocardium, and stroke (Hahad et al., 2017; Lusk et al., 2004). While the elderly are at greater risk of hearing loss, children are particularly prone to cognitive impairments due to noise pollution. The WHO reported in 2011 the estimated correlation between the level of noise pollution, cognitive impairment, and related DALYs lost among children aged 7 19 years (see Table 3.3) (World Health Organization, 2011). Characterizing this impact Table 3.3: Estimated DALYs per year per million children aged 7 19 in the EUR-A epidemiological subregion. Noise exposure level , 55 Ldn 55 65 Ldn 65 75 Ldn . 75 Ldn

Percentage of population exposed to noise level

Percentage of population who will develop cognitive impairment

Number impaired per million

DALYs lost per million

11.24 3.14 1.82 0.33

0 20.6 50 75

0 281 9090 2475

0 37.7 54.5 14.9

From World Health Organization. (2011). Burden of disease from environmental noise. Quantification of healthy life years lost in Europe. , https://www.who.int/quantifying_ehimpacts/publications/e94888/en/ . .

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are communication difficulties, frustration, sleep disturbance, and attention and learning disorders (Ecob et al., 2011; Evans, 2006; Stansfeld & Clark, 2015). This link with noise pollution is also dictated by the fact that children, like the elderly, have a lower ability to cope with environmental stimuli. Finally, in the healthcare environment, the problem of noise in the hospital is of particular importance. Over the years, noise in hospital wards and rooms has increased, largely due to the introduction of more biomedical devices and alarms used to alert care staff. Unfortunately, the increase in noise impacts both the quality of the work of hospital staff and that of patients, and can lead to diagnostic and therapeutic errors and interference in doctor patient communications (Choiniere, 2010; Messingher et al., 2012).

3.5 Soil pollution Soil can be contaminated by different routes, almost always interconnected with the other forms of pollution seen above: from solid, liquid, or gaseous waste to the contamination with chemical residues, such as pesticides used in agriculture or other products generated from anthropic processes (hydrocarbons, dioxins, heavy metals, radioactive waste). These substances can come into contact with humans through breathing, ingestion, or absorption through the skin (Steffan et al., 2018). The most common pollutant in the soil is lead, mainly due to its release through lead-containing fuels. Children and adolescents are the category most at risk of the damage attributable to lead, as already mentioned in the context of air pollution (Balabanova et al., 2017; Filippelli & Laidlaw, 2010). Other polluting and potentially harmful elements found in the soil are cadmium, arsenic, and mercury (Steffan et al., 2018). A carcinogenic role of nonorganic arsenic has been found since 1980 with regard to skin, lung, and bladder cancer, following long-term exposure through respiration and ingestion. The mechanisms by which arsenic is linked to cancer range from suppression of the p53 protein, alterations in DNA repair, and modifications of its methylation patterns (Martinez et al., 2011). Noncarcinogenic effects, such as neurobehavioral alterations in both puberty and adulthood, are also attributed to arsenic exposure. Skin damage, such as melanosis and keratosis, can also be observed, as well as damage to the cardiovascular system with thrombotic damage due to arsenic-induced agglutination of thrombocytes (Lee et al., 2002; Paul et al., 2000; States et al., 2009). Finally, arsenic exposure is shown to be potentially linked to type 2 diabetes onset and to fetal mortality or abnormalities (Kuo et al., 2015; Vahter, 2009). Cadmium has as its main means of contact with humans the ingestion of food grown on soils rich in it. Acute cadmium exposures are similar to flu syndromes with chills and fever (Fatima et al., 2019). In the long term, however, exposure causes systemic toxicity that affects in particular the renal system by glucosuria, aminoaciduria, hyperphosphaturia, hypercalciuria, and polyuria, and the reproductive sphere with hormonal alterations that lead to reduced fertility in both sexes, inhibiting the production of oocytes and spermatozoa (Ja¨rup, 2002; Lin Zhao et al., 2017; Nogawa et al., 1977; Satarug & Moore, 2004).

The environmental pollution’s influence on public health 87 The vascular system is also involved in cadmium intoxication with endothelial damage, thrombogenic events, and elevation of blood pressure (Franceschini et al., 2017; Tang et al., 2017). Another well-described effect of cadmium on the human body is the weakening of the bones via demineralization and the inhibition of the production of collagen, with onset of fractures, pain, and musculoskeletal deformations (Bone demineralization; Sughis et al., 2011). An infamous case of mass cadmium poisoning occurred in Japan in Toyama prefecture in 1912, where the Jinzu River was contaminated with large quantities of cadmium from local mining activities and ended up contaminating irrigated rice plantations with river water that was also used as drinking water. In the decades following the beginning of the contamination, a dramatic increase in diseases related to cadmium toxicity was observed, such as colorectal cancer, ischemic heart diseases, and renal diseases (Aoshima, 2017). As seen above with regard to water pollution, antibiotics used in farms and aquacultures are excreted by animals in part without being metabolized and purifications plants are often not effective in removing them from wastewater. This implies that the reuse of antibiotic-contaminated waters for irrigation or their persistence in the soil contributes to the development of antibiotic-resistant strains (Lee et al., 2018). As for pesticides used in agriculture, they can represent a risk of short-term effects when they come into contact with the skin or are ingested in large doses. In this regard, farmers are the people most exposed to this risk. As for the long-term accumulation effects, serious risks are observable, ranging from cancer to brain damage and impairment of fertility (Baldi et al., 2021; Bhandari et al., 2020; Frazier, 2007). However, these effects are strongly dose-dependent and linked to individual susceptibility, so it is not always possible to establish a risk profile for these products. For example, glyphosate is often debated for its wide use in the treatment of wheat and its presence in derivative products such as pasta. However, if glyphosate provided evidence of carcinogenicity in rodent studies, there is no solid evidence of risk attributable to it in humans in the quantities in which it is used in agriculture (Meftaul et al., 2020). Finally, a further widespread form of pollution is that from radioactive waste which can derive mostly from the energy industry or can accidentally be the result of major environmental disasters, such as the ones that occurred in Chernobyl in 1986 or in Fukushima in 2011. The substances particularly involved as pollutants are thorium (232Th), uranium (238U, 235U), potassium (40K), and cesium (137Cs). The contamination of the soils and of the agricultural products derived from them represents above all a risk of tumors induced by damage to and/or mutation of the DNA following exposure to radiation (Ahmad et al., 2019; Jeggo & Lo¨brich, 2006).

3.6 Other forms of pollution Other forms of pollution that pose a risk to human health are light, electromagnetic, and thermal pollution. Light pollution is due to excessive or inappropriate artificial lighting in

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western cities. It is estimated that 80% of the planet’s land areas and the ones where 99% of Americans live, are environments where it is not possible to see the Milky Way at night (80 Percent of Americans). The greatest risk in this case is the alteration of the sleep wake cycle. This is due to the alteration of melatonin production, resulting in alterations of the immune and endocrine systems with a possible increased risk of obesity, depression, and other diseases such as breast cancer and diabetes (Chepesiuk, 2009; Spivey, 2010). Electromagnetic pollution is linked to the generation of artificial electric, magnetic, and electromagnetic fields, that is, not attributable to the Earth’s natural background or to natural events, such as the electric field generated by lightning. The source of this type of pollution is the increasing use of cordless electrical devices, cell phones, radars, microwave ovens, radios, computers, and so on (Bandara & Carpenter, 2018). There is no agreement in the medical literature on the health risks attributable to this type of pollution. High-energy microwaves (frequencies from 300 MHz to 300 GHz) are believed to have possible carcinogenic effects, unlike radiation at lower frequencies from 100 kHz to 300 MHz (Chekhun et al., 2011). However, the results in the literature are contrasting. For example, it was found that an average daily exposure greater than 0.3 0.4 µT to extremely low frequency electromagnetic fields could be associated with an increased risk of childhood leukemia. However, no mechanisms have been identified to explain this association (Bailey & Wagner, 2008). Thermal pollution can be of two types: the direct one, where the heat-pollutant sources come into direct contact mostly with an ecosystem (e.g., a company that pours hot waste in a lake or a river) and the indirect one, where the effects have repercussions on a global scale and where the pollutants most involved are greenhouse gases such as methane and carbon dioxide which contribute in a decisive way to the problem of global warming (Vallero, 2019). The rise in temperatures, for example, contributes to deaths mainly from cardiovascular or respiratory causes. However, other diseases are also exacerbated by high temperatures. For example, the levels of allergens causing asthma are higher at hot temperatures (Bunker et al., 2016; Hajat et al., 2006; Lam & Chan, 2019; Ziska et al., 2019). The same behavior can be observed in parasites such as malaria in Africa or the snail-borne disease schistosomiasis in China (Zhou et al., 2008). It is difficult to predict what the burden that is attributable to thermal pollution will be in the coming decades. To give an example, however, it is useful to observe how the infamous heatwave of the summer of 2003 resulted in an excess of about 70,000 deaths in Europe alone (Robine et al., 2008).

3.7 Case studies The most striking cases of demographic explosion with consequent anthropogenic pressure are represented by the endless Asian metropolises. Among these, New Delhi is one of the most studied cities in literature with hundreds of works published relating to its environmental sustainability issues.

The environmental pollution’s influence on public health 89 New Delhi has experienced a growth in terms of population that has led it to grow from 1.44 million people in 1955 to 12.8 million in 1991, to the current nearly 30 million (Delhi Population, 2021; Nagdeve, 2004). This growth, as in most cases relating to other large megacities, was not accompanied by adequate environmental sustainability policies. For example, average estimates from 2014 indicate a level of PM2.5 of 277 µ/m3 in winter and 58 µ/m3 in summer. These overall values are far from the recommended 40 µ/m3 recommended by the Indian polices and by the European Union (25 µ/m3), but also by Hong Kong and China (35 µ/m3) (Sharma et al., 2018). Despite a series of maneuvers aimed at containing the problem (catalytic cars, unleaded petrols), in 2020 Delhi was estimated to be the most polluted capital in the world with an average PM2.5 concentration of 84.1 µ/m3, more than double that of other large cities like Beijing (New Delhi Is World’s). Anyway, it is not easy to estimate the burden attributable to the pollution of the city, especially since the different areas are involved differently. The largest study in this regard was conducted by the Central Pollution Control Board in 2008. In this work, the health outcomes of Delhi citizens were compared with a control group living in rural areas of West Bengal. Respiratory symptoms and obstructive lung deficits were all significantly higher among Delhi citizens while lung function decline in Delhi was double compared to controls. Respiratory epithelial metaplasias and dysplasias were also more common in Delhi than controls. Hypertension was also identified as more prevalent in Delhi and correlated with the PM10 value. More generally, an increase in all-natural-cause mortality with increasing levels of air pollution was reported in a timeseries study on the population of Delhi. Even more alarming is the fact that much of the pollution-related diseases in Delhi remain untreated by local healthcare facilities (Epidemiological Study, 2008; Maji et al., 2018). A deep interweaving between air quality and other forms of pollution worsens the situation. For example, the poor control of the treatment and release of wastewater by the companies of Delhi has made the Yamuna, the river that crosses the city, one of the most polluted rivers on the planet and one in which the only organisms that are able to proliferate are bacteria. It is important to note that before entering the city, the Yamuna contains about 7500 microorganisms/100 mL, mostly transported by solid waste, while at the exit of the city the number increases to 9 million/100 mL (Asim & Nageswara Rao, 2021; Nagdeve, 2004). Overall, despite the Indian government’s efforts to stem the severe situation, Delhi can unfortunately be considered a model for studying the direct relationship between anthropogenic pressure and risks to human health. A situation in some ways similar, albeit on a smaller scale, to that of Delhi, can be represented by the metropolitan area of Naples, in the Campania region, Italy. Here the demographic pressure was considerable and following the building speculation at the end of the last century, a population concentration in some cases exceeded 10,000 inhabitants/km2 (Campania).

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Also in this case, the demographic increase was not accompanied by appropriate regulations and maneuvers aimed at environmental sustainability and ensuring the necessary services for the population. In the Campania region, two situations that have been raised and which currently still represent a marked risk to human health. The first one is the so-called Land of Fires, a territory of over 1000 km22 inhabited by about 2.5 million inhabitants distributed in 57 municipalities in the north of Naples area. The second is the agro nocerino-sarnese, a 200 km22 large area crossed by the Sarno river, at the southeast of the city. In the land of fires, the problem is centered on soil and air pollution. Toxic wastes from the final stages of industrial production have been illegally buried and burned for decades. The consequence is a marked increase in the air and soil of a series of pollutants including heavy metals, fine dust, nitrogen and sulfur oxides, persistent organic pollutants (POPs), benzene, and dioxin (Forte et al., 2020). It is not easy to estimate the impact that these practices have had and are still having on human health. A problem in this regard is the presence of strong confounders including the presence of a preexisting pollution attributable to the Naples metropolitan area immediately close to the land of fires. However, many studies have been conducted, especially in people with a high Waste Exposure Index, in the so-called triangle of death, the geographical area between three municipalities named Marigliano, Nola, and Acerra (Mazza et al., 2018). In general, different clusters of cancer have been identified, especially of the liver, lung, kidney, and bladder, but also of leukemia, fetal distress, childhood carcinomas, and low birth weight (Comba et al., 2006; Mazza et al., 2015; Triassi et al., 2015). Furthermore, it must be considered that this region has a strong agri-food vocation and it is not possible to estimate how much contamination of products may represent risk for human health in the long term. The problem relating to the Sarno river is in some ways similar to that of the land of fires. This short river (24 km) that flows into the Naples Bay, crosses an area that is at the same time highly inhabited and a strong agricultural hub. Here, the canning and tanning industries have for a long time poured their waste into the river, covered by an inadequate control policy. The result is that the Sarno river was, in the past, classified as the most polluted river in Europe due to the very high level of heavy metals, pesticides, solid waste, and organic matter. This has resulted in serious damage to the ecosystem and, above all, to the health of the population living on the banks of the river (Albanese et al., 2013; De Pippo et al., 2006). In fact, the river water was also used to irrigate the surrounding plantations (especially tomatoes and wheat) and the pastures for farms in the area surrounding the urban area. Over the years, high prevalences have been recorded for respiratory disorders, dermatitis, but also diseases with diffusion of fecal bacteria such as brucellosis and typhoid fevers. In addition, the WHO in 1997 reported a 17% higher mortality rate from cancer and leukemia in the Sarno River area than in other areas of the world, while other sources cite a 53% increase in the risk of Hodgkin’s lymphoma (Centro Iniziative Divulgazione, 1998; Manzione, 2006).

The environmental pollution’s influence on public health 91 High anthropogenic pressure and high population density is not always followed by out of control pollution. For example, Tokyo, one of the most congested metropolises in the world, has managed and contained the various forms of pollution, including air pollution, with an acceptable concentration of PM2.5, just a little over 10 µg/m3 , in 2019 (Tokyo Air Quality Index). However, it is interesting to note that Tokyo is a relatively quiet and silent metropolis, despite its approximately 14 million inhabitants. This was possible thanks to a huge investment in technology, the spread of cars with electric motors, and the strong promotion of public transport. Part of the credit, however, can be attributed to the habits of the Japanese population who are not prone to noisy conversations and in general are very respectful of the peace of others. Furthermore, from the urbanistic point of view, it should be noted that Tokyo has many green areas and many religious temples spread throughout the urban territory that act as oases of silence. In general the spread of noise in Japan is strongly regulated. For example, current Japanese regulations require factories not to exceed noise emissions above 50 dB during daylight hours (Jabło´nska, 2020). The result of these maneuvers was to bring Tokyo to a noise level well below that of other large Asian megacities but also that of smaller cities such as Manchester or Hanover (These are the cities with the worst noise pollution). In Hong Kong, according to the same estimates mentioned above, the noise pollution problem is greater. However, this metropolis is also famous for being the city with the greatest light pollution in the world, above other cities such as London, Shanghai, and Sidney (Light pollution in Hong Kong; “Hong Kong’s light pollution”). Hong Kong’s night brightness has been calculated to average well over a thousand times the natural night brightness. The lights of the LEDs on the buildings of the city on many occasions reach up to 500 lux, a brightness level markedly higher than the most common recommended levels. This situation has led to numerous complaints from citizens but above all, as claimed by a 2010 survey, sleep loss, weariness, and visual fatigue among them (Karol et al., 2010). A government task force in 2016 suggested the stopping of illuminated signs between 11 p. m. and 6 a.m. However, this initiative was only proposed on a voluntary basis. Disappointingly, even if this initiative found citizens on its side, at the same time it was strongly opposed by tourism and advertising companies (Lawmakers split on need for law on light pollution). In many cases the effects on human health are not only those directly attributable to pollutants. For example, there is wide knowledge of the cancer cases related to the great nuclear disasters of history but few know the many anxiety disorders and posttraumatic stress in mothers affected by the Chernobyl or Fukushima disaster, mainly attributable to the fear of developing cancer (Bromet 2012, 2014). At the same time it is interesting to mention a particular type of indoor pollution called Sick Building Syndrome, a set of symptoms declared by people after spending time in a specific building and very often attributed without concrete evidence to a particular pollutant. Symptoms range from a simple cough, to palpitations, to hypothetical

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building-related carcinomas (Joshi, 2008). Although Sick Building Syndrome is still debated in the literature, it has emerged clearly in many cases. One of the most famous is represented by the more than 180 cases of pneumonia among the participants at an American Legion convention in Philadelphia in 1976. In this case the pollutant, or rather the causative agent, has been attributed to the presence of Legionella pneumophila inside the cooling towers of the building (Fraser et al., 1977). Also with regard to electromagnetic pollution, it is often difficult to identify a clear cause effect link between the polluting source and the effects on health. In every city it is very easy to find neighborhood associations opposed to the presence of some television or radio repeater. A case that had worldwide resonance is that of the Vatican radio antennas in Cesano, a town in the north of Rome, Italy. Cases of leukemia in children under 14 who lived or had lived near the subsequently demolished antenna have been attributed to it (Michelozzi et al., 2002). In this case, the epidemiological evidence is questionable mainly due to the low number of cases considered and the low subsequent statistical power of the data analysis. In addition, a biased journalistic communication of the results was also highlighted due to conflicting positions toward the Vatican state (The invisible word’ le onde). A case of an atypical heat wave attributed to global warming is the one that involved Japan for a few weeks starting on July 15, 2018, the day in which 200 meteorological stations of 927 recorded record temperatures of over 35 C. The situation became dramatic on July 23, when in Kumagaya, Tokyo, the record peak of 41 C was reached. On July 24, the day after the heat spike, the Japanese government named the situation a natural disaster. The number of hospital admissions, mostly for heatstroke, in the days July 14 24 was 34,147 with 99 cases of patients found clinically dead by emergency medical services (Hayashida et al., 2019). Even if heatwaves are not new in the recent history, e.g., the one mentioned before 2003 that hit Europe, and although it is not always possible to identify the real causes, a 2019 attribution science study published in Scientific Online Letters on the Atmosphere draws clear conclusions right from the title: “The July 2018 High Temperature Event in Japan Could Not Have Happened without Human-Induced Global Warming” (Imada et al., 2019).

3.8 Conclusions and future trends The relationship between human activity, pollution, and health is very complex and it is difficult to predict what the future scenarios will be. In the introduction of this chapter we reported the catastrophic scenarios that would arise if we did not take up the challenge of global pollution. Fortunately this is not the case, because much has been, is, and will be done to reduce the risks attributable to the quality of the environment in which we live. India has announced that from 2030 it will only sell electric cars (India turns to electric vehicles to beat pollution). Similarly in England the goal is to remove all types of fossil fuels from the streets by 2035 (UK could ban sale of petrol). In Germany it has been

The environmental pollution’s influence on public health 93 suggested that all public transport be made free to encourage citizens not to use their cars (German cities to trial free public transport to cut pollution). A 100-meter-high skyscraper was built in Xian, China, capable of autonomously purifying the air in the surrounding 10 km2 area (China builds; Cyranoski, 2018). And there are thousands of other initiatives aimed at attacking all forms of pollution that we have seen above. Therefore, if on the one hand some trends such as the urbanization of Africa can be a source of concern, on the other hand the growing scientific technological development and the taking of responsibility of giants such as the aforementioned China and India, can help us to hope in an acceptable situation for the next few decades (Abera et al., 2020). And as demonstrated in a recent article by the Royal Society of London, efforts to combat pollution will bear fruit not only in absolute terms of morbidity/mortality reduction, but also in terms of cost benefit, since the reduction of the health burden will be greater than the costs of implementing environmental protection measures (Von Schneidemesser et al., 2020).

List of acronyms COPD DALYs GBD LMI PFA PM2.5 PM10 ROS WHO

Chronic Obstructive Pulmonary Disease Disability Adjusted Life Years Global Burden of Disease Low and Middle Income Population-Attributable Fraction Particulate Matter 2.5 µm Particulate Matter 10 µm Reactive Oxygen Species World Health Organization

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CHAPTER 4

Environmental monitoring and membrane technologies: a possible marriage? Tianling Li1, Ming Zhou2, Zhengguo Wang1, Chao Xing2 and Shanqing Zhang2 1

Collaborative Innovation Centre of Atmospheric Environment and Equipment Technology, Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, School of Environmental Science and Engineering, Nanjing University of Information Science & Technology, Nanjing, Jiangsu, P.R. China, 2Centre for Clean Environment and Energy, School of Environment and Science, Gold Coast Campus, Griffith University, Gold Coast, QLD, Australia

4.1 Introduction The ever-increasing population and rapid industrialization have placed increasing pressure on the environment. For this, environmental authorities have worldwide introduced strict monitoring regimes as a strategy to manage pollutants better and reduce any potential health risks. The increasing demands in environmental observation have led to the development of monitoring techniques that can provide reliable data to support decisionmaking. Ideally, to meet the needs of large-scale environmental pollution assessments, an analytical approach should be (1) highly reliable, sensitive, accurate, and interference-free; (2) cheap to build, easy to deploy, and low cost for operation; and (3) capable of in situ measurements (Li et al., 2017a). In this regard, membrane-based techniques possess potential advantages in meeting the aforementioned criteria. For the past decades, such a technique has been extensively employed for serving industrial production and environmental protection purposes, such as disinfection in the water industry (Ciardelli et al., 2001; Shannon et al., 2008), hemodialysis in the healthcare industry (Stamatialis et al., 2008), separation and purification in the food processing industry (Pabby et al., 2015), and resource recovery and reuse in ecological protection (Bernardo et al., 2009). In general, the membrane is employed as a selective layer to separate species of interest from a mixture (Strathmann, 1981). Such a mixture could be in gaseous form or liquid form (Pinto et al., 1999). In essence, any materials that form a thin and stable interface that regulates the permeation of chemicals in contact with it can be recognized as a membrane. This interface may be formed of metal, glass, ceramics, or polymers, or it may be ordered molecular monolayers of liquids (Pandey & Chauhan, 2001). Current Trends and Future Developments on (Bio-) Membranes. DOI: https://doi.org/10.1016/B978-0-12-824103-5.00009-7 © 2023 Elsevier Inc. All rights reserved.

101

102 Chapter 4 In environmental monitoring, the membrane-based technique represents the monitoring method that employs various membranes as adsorption/reactive layers (Fig. 4.1A), ion-exchange layers (Fig. 4.1B), or diffusion layers (Fig. 4.1C) to achieve the detection of a wide variety of environmental pollutants in water, soil, and atmosphere. First of all, membranes, especially solid and liquid membranes, acting as adsorbents/reactants can be found in most membrane-based monitoring techniques, where the specific synthetic chemical or biological membranes can selectively react with the analyte to produce measurable changes (such as electrical signal and optical signal) that can be quantitatively detected (Fig. 4.1A). Hence, this kind of membrane technique usually works together with some sensitive sensing transducers, such as electrochemical and optical transducers. For example, ion-selective membranes are usually operated with potentiometric detection to measure Ca21 in freshwater, PVC-based polymeric membranes have been incorporated with optical detectors to quantify Cu21 in aqueous extracts of soil, and gold disc voltammetric micromembrane electrodes have been combined with amperometric measurement to monitor N2O in the atmosphere (Li et al., 2019c; Lvova et al., 2020; Ping et al., 2013). Secondly, ion-exchange membranes are often used in the monitoring of micropollutions in the environment. The measurement is achieved by exchanging the analyte in the environmental media with a specific substance contained in the selective ion-exchange membranes (Fig. 4.1B). The diffusive gradient in thin-film technique (DGT) is a typical ion-exchange membrane-based monitoring technique, which has been widely applied for in situ samplings of various ionic substances in the water, soil, and sediment environment. Until now, more than 20 ions, including most of the nutrients and heavy metals, can be selectively sampled by the DGT method and then measured by the corresponding analytical techniques. In this way, ion-exchange enhances the detection sensitivity and accuracy by accumulating the analyte in the ion-exchange membrane where a detectable substance is formed and preconcentrated for later detection using different devices, such as flame atomic absorption spectrophotometry detection and inductively coupled plasma optical emission spectrometer detection for heavy metal ions (Cd61, Pb21, Cu21, etc.) (Pescim et al., 2012; Wang et al., 2017; Warnken et al., 2004a, 2004b). Thirdly, some other membrane-based monitoring methods used gas-permeable membranes to create a uniform, stable, and selective diffusion medium for analyte quantification (Fig. 4.1C). In this case, the monitoring principle is established according to the reaction between the analyte diffused through the membrane and the internal reagent(s), which results in a measurable signal that can be captured by electrochemical or optical detectors (Pinto et al., 1999). On the one hand, the membrane allows a discriminating permeation of specific analytes while regulating the diffusion kinetics. On the other hand, the membrane, acting as a barrier, isolates the sensing environment from the external media, thereby preventing probable contamination. Therefore, this kind of membrane-based technique can selectively recognize analytes and is independent of the matrix in the sample, which is superior to other methods without a membrane that are greatly affected by the sample

Environmental monitoring and membrane technologies: a possible marriage? 103

Figure 4.1 A membrane is employed as an adsorption/reactive layer (A), ion-exchange layer (B), and diffusion layer (C).

104 Chapter 4 matrix. Consequently, this kind of membrane-based technique exhibits specific selectivity and is hardly affected by the complicated detection environment, presenting excellent superiority in antiinterference ability when compared with other methods without using membranes (Ho et al., 2001; Pinto et al., 1999; Toda, 2004). Some conventional water and atmosphere monitoring techniques, such as DGT and gas permeable membrane-based conductimetric sensors, have already adopted the diffusion membrane as an important premonitoring process, where a uniform and constant diffusion rate of the analyte is provided for the subsequent detection unit. This diffusion-based method has also been widely used in developing new sensors for the monitoring of common environmental pollutants, such as organics, heavy metals, and acidic and basic gases (Li et al., 2019c; Scally et al., 2003; You et al., 2019; Zhou et al., 2021b). Under the era of big data, judgments and decision-making in various industries increasingly rely on adequate data analysis. Consequently, accurate and reliable sources of monitoring data become particularly vital. Following the trend, urgent and necessary demands are proposed for effective and environment-friendly monitoring technology. In recent years, membrane-based monitoring techniques have been developed rapidly and been widely used in various environmental areas, such as agriculture (e.g., nonpoint source pollutants detection and greenhouse gases monitoring) (Aylott et al., 1997; Li et al., 2019c; McPeak & Hahn, 1997), surface water (e.g., organic contaminants and nutrients monitoring) (Chen et al., 2017; Ding et al., 2010; Guibal et al., 2017; Huang et al., 2016a, 2016b, 2016c), sediment (e.g., heavy metal monitoring) (Gao et al., 2009; Kreuzeder et al., 2013; Song et al., 2018; Xu et al., 2018), atmospheric monitoring (e.g., inorganic and organic gaseous pollutants) (Ariga et al., 2012; Cheol Gil et al., 2000; Ha¨mmerle et al., 2008), to inspect the migration and transformation of contaminants in water, soil, and the atmosphere. This indicates that membrane technologies and environmental monitoring have been well integrated, and they have the greatest potential to promote the development of advanced analytical tools for future environmental protection.

4.2 Membrane-based monitoring methods In situ membrane-based monitoring can be operated by either direct sampling and detection of contaminants in field conditions, that is, direct sampling and detection, or passive sampling and detection, which means collecting pollutants in steady-state from the field environment followed by examination in a lab. These two categories are introduced in this section.

4.2.1 Direct sampling and detection Direct sampling and detection is a two-in-one monitoring method, that is, simultaneous analyte sampling and detection in one monitoring device, which typically combines membrane technique with synchronous analysis technique to achieve accurate substances monitoring.

Environmental monitoring and membrane technologies: a possible marriage? 105 Commonly, physical, chemical, and biological methods are integrated with a membrane technique to quantitatively and qualitatively recognize and detect specific compounds in the environment. Specifically, for organic compound detection, gas-chromatography, mass spectrometry, and spectroscopy techniques are the most frequently employed for synchronous analysis because of their ability for the simultaneous separation and identification of multiple substances from mixtures, while for inorganic compound detection, electrochemical and optical detectors are preferred due to their simple detection principles, strong operability with fast response and accurate measurement, and convenient portability. However, taking into account the actual requirements of in situ monitoring and the predictable future requirements of portability, miniaturization, and low operational cost, it is worth mentioning that stable and reliable electrochemical and optical detection technologies can better meet future sensing needs, and thus have received more attention and experienced considerable development during the past several decades. Membrane-based electrochemical sensors are currently the most widely used environmental monitoring devices. As shown in Fig. 4.2, they mainly include membrane-based potentiometric sensing devices (Fig. 4.2A), amperometric sensing devices (Fig. 4.2B), and conductometric sensing devices (Fig. 4.2C). An ion-exchange-based sensor is a typical representative of a potentiometric sensor where the shift of ion equilibrium across the membrane is represented by specific membrane potential that can be quantitatively measured so that the analyte concentration can be calculated based on the Nernst equation. Three main types of ion-exchange membrane sensors, that is, crystal electrode with solid membrane, ion-exchange with liquid membrane, and carrier electrode (e.g., enzyme electrode), have experienced rapid development and improvement in detecting environmental elements during the last 30 years (Li et al., 2017b). Membrane-based amperometric detection uses a conventional electroanalytical technique reflected in voltammetric or potentiometric measurements, which can accurately detect electroactive groups in a sample (Cao et al., 1992). It usually consists of a working electrode, an auxiliary electrode, and an electrolyte in which a fast, reversible, and redox reaction can occur. According to Faraday’s Law, the reaction rate (i.e., the rate of signal generation) is strongly correlated with the amount of diffuse component under certain operational conditions (Stetter & Li, 2008). Such a detection principle is commonly used in the monitoring of inorganic gases (e.g., O2, N2O, SO2, H2, etc.) and hydrocarbon compounds (e.g., ethylene, ethyl alcohol, acetaldehyde, acetylene, cyanide, etc.) (Chinvongamorn et al., 2008; Chiou & Chou, 1996; Hodgson et al., 1999; Jordan et al., 1997; McPeak & Hahn, 1997; Miro´ & Frenzel, 2004; Nikoli´c et al., 1991; Nikolova et al., 2000). In recent years, membrane-based conductimetric sensors have been promptly developed and improved for sensing inorganic gaseous compounds. The detection mechanism of this type of sensor depends on the measurement of conductivity change caused by the selective

106 Chapter 4

Figure 4.2 Typical membrane-based detection techniques: (A) potentiometric detection; (B) amperometric detection; (C) conductometric detection; and (D) optical detection.

reaction between the permeated analyte and specific recognition components embodied in the sensor, which is positively correlated to the diffuse analyte, further positively related to the analyte concentration in the sample media (Tongol et al., 2003). Recent research progress shows that a membrane-based conductimetric technique can simultaneously achieve in situ real-time monitoring and long-term average concentration monitoring in both aquatic ammonia nitrogen and soil ammonia volatilization monitoring, which would be of great significance for studying the real-time and cumulative effects of specific substances in the environment (Li et al., 2017a; Li et al., 2019b, 2019c). For membrane-based optical sensors, as illustrated in Fig. 4.2D, on the one hand, the colorimetric or fluorescent reagent is employed to react with the diffusive analyte to

Environmental monitoring and membrane technologies: a possible marriage? 107 produce a characteristic color or fluorescent, which can be identified by optical transducers. On the other hand, the spectral analysis, including absorption and emission spectrums analysis, can be used to quantify the amount of the analyte based on the strength of the characteristic spectrum, which is usually employed in gas molecules analysis (Liu et al., 2012). Attributed to the accuracy in optical detection, most membrane-based optical sensors possess distinct performance in sensitivity, selectivity, and reliability (Rubio et al., 2007). Nevertheless, the applications of this type of sensors in gas sensing are still restricted by the high cost of optical transducers and detectors, as well as the difficulty in achieving miniaturization. To date, increasing research has focused on the development of low-cost optic sensors for gas (e.g., CO2, NO2, SO2, and NH3) monitoring (DeGrandpre, 1993; Frenzel et al., 2004; Mana & Spohn, 2001; Satienperakul et al., 2004; Schmitt et al., 2012; Schulze et al., 1988; Themelis et al., 2009; Willason & Johnson, 1986), and the latest research reveals a portable membranebased sensing probe that is applicable for real-time monitoring of the instantaneous and time-weighted average gaseous chlorine concentrations. Such a configuration could open a new horizon for in situ gas sensor development by incorporating different membrane technologies (Zhou et al., 2021a, 2021b).

4.2.2 Passive sampling and detection In situ passive sampling technology can accumulate the monitoring substances on-site without affecting the surrounding environment. The concentration of the analyte accumulated in the passive sampler can truly reflect the real concentration or the timeweighted average concentration in the environment. Many passive sampling methods are developed based on membrane technology, of which the DGT technique is a well-known one that has been commonly used to detect elementary substances and mixtures in the natural environment, especially in soil, sediment, and water (Huang et al., 2016c; Li et al., 2019a; You et al., 2019). DGT employs a specifically assembled passive sampling device, which usually holds an analyte-specific binding agent and a diffusive layer, which can automatically accumulate the component of interest when deployed in the field. A typical application of this technique is to monitor unstable compounds, such as ionic and complex substances that are dissociated from soil or sediments, which can be irrevocably immobilized in the binding layer once they have diffused through the diffusive layer. In this way, the concentration gradient is formed between the interface of the membrane layer and binding layer (Fig. 4.3) (Ernstberger et al., 2002; Sun et al., 2013). In the process mentioned above, membranes are employed to sophisticatedly control the substances diffusion process. The average analyte concentration for a given deployment period can then be obtained by laboratory-measured analyte level in the selective binding layer.

108 Chapter 4

Figure 4.3 Mechanisms of DGT technique.

The diffusive layer regulated target analyte transport process allows the concentration of the analyte to be determined based on Fick’s first law of diffusion, according to which, the time-weighted average concentration (CDGT) of the analyte under a given deployment time (t) can be determined by Eq. (4.1) (Davison & Zhang, 1994): CDGT 5

M ðΔg 1 δÞ DAt

(4.1)

where M is the accumulated amount of analyte in the binding gel, Δg is the thickness of the diffusive layer; δ is the thickness of the diffusive boundary layer, which can be obtained according to previously published study (Davison & Zhang, 2012; Galceran & Puy, 2015; Scally et al., 2003); D represents the diffusion coefficient of the analyte in the diffusive layer, measured by diffusion behavior analysis or DGT time-series comparative analysis (Ding et al., 2016; Pan et al., 2015; Zhang & Davison, 1999); and A denotes the exposed surface area of DGT sampler. Structurally, DGT devices are usually composed of a binding layer that can swiftly and irrevocably accumulate the analyte species, a diffusive layer that permits all analyte species to diffuse across, a defensive filter membrane that avoids other substances adhering to diffusive gels, as well as a front ring buckle clasped to the main structure to keep all the layers tightly connected (Li et al., 2019a). Based on such a construction principle, four main types of DGT devices, namely piston type, dual-mode, flat type, and liquid binding phase devices, have been developed. As reviewed by Cal et al. (Li et al., 2019a), and shown in Fig. 4.4, the four types have similar main structures as well as distinctive design features

Environmental monitoring and membrane technologies: a possible marriage? 109

Figure 4.4 The configurations of membrane-based sensors: (A) piston type DGT device; (B) dual-mode DGT device; (C) typical flat-type DGT device; and (D) liquid binding phase device. Modified from Li, T.L., et al. (2019c). Membrane-based conductivity probe for real-time in situ monitoring rice field ammonia volatilization. Sensors and Actuators B-Chemical, 286, 6268; Liu, S., et al. (2016). A nanoparticulate liquid binding phase based DGT device for aquatic arsenic measurement. Talanta, 160, 225232.

so that they can be better adapted to a specific monitoring environment. Among them, piston type and dual-mode are commonly employed for dry soils and waters measurement (Luo et al., 2014; Pan et al., 2015); the flat type is usually used for the measurement of sediments and flooded soils (Ding et al., 2016; Wu et al., 2015); and the liquid binding phase device is mainly used for the analysis of a specific analyte in solution. It is worth pointing out that, among all the layers of DGT devices, the binding layer plays a decisive role in the analyte measurement, where quantitative physical and chemical reactions would occur, and accumulated analyte concentrations strongly depend on the binding capacity induced by the binding agents. Therefore, it is feasible and essential to use specific DGT devices for determining the distribution and migration of analytes according to the appropriate selection of binding agents (Fan et al., 2013; Li et al., 2005a). Binding layers can also employ both single and hybrid binding agents, as well as both solid and liquid binding agents. As long as the reagents are well combined with solid gels or liquid solutions and integrated with the above four types of devices for a specific monitoring environment, the sampling and subsequent detection of most organic and inorganic substances, such as nutrients, heavy metals, and pesticides, in soils, sediments, and waters can be achieved. The applications of DGT technology could be dated back to 1994 when William Davison and Hao Zhang first proposed the DGT principle and used it to monitor common trace

110 Chapter 4 metals in water (Davison & Zhang, 1994; Zhang & Davison, 1995). From then on, DGT has been developed and improved to enable monitoring of the concentration of plenty of elementary substances and mixtures, involving various metals (Altier et al., 2016; Gao et al., 2009; Gimpel et al., 2003; Yabuki et al., 2014), nutrients (Cai et al., 2017; Menzies et al., 2005), organic chemicals/compounds (Chen et al., 2012, 2013; Dong et al., 2014), radioactive elements (Drozdzak et al., 2015; Leermakers et al., 2009), oxyanions (Stockdale et al., 2008, 2010), and rare earth elements (Yuan et al., 2018) in various environmental media. Later developments also support the synchronous detection of metals and oxyanions that present the feasibility of investigating the multiple associations among different compounds (Mason et al., 2005; Panther et al., 2013; Wang et al., 2017). Furthermore, the combination of DGT with other sampling/detection techniques, such as dialysis (Xu et al., 2012), diffusive equilibrium in thin films (Gao et al., 2007; Pradit et al., 2013), and planar optodes (Hoefer et al., 2017; Lehto et al., 2017), has provided solid technical support for the accurate and in-depth understanding of the biochemical evolution processes. In addition, the incorporation with laser ablation inductively coupled plasma mass spectrometry (Stockdale et al., 2010; Warnken et al., 2004a) or computer imaging densitometry (Ding et al., 2013; Teasdale et al., 1999) make it possible to achieve a two-dimensional high-resolution (sub-mm) distribution of analyte species in diverse environments (e.g., sediments and the rhizosphere).

4.3 Environmental applications To date, quite a number of studies on the development of the monitoring of concentration, speciation, and distribution of inorganics and organics using membrane techniques have been undertaken. The recent advances in applying membrane technologies to the monitoring of water, soil, and atmosphere environments are reviewed in this section.

4.3.1 Water environment As the foundation of all life, water security is always the top priority of environmental issues. As a result, water quality monitoring has been well-recognized as a critical and essential task for environmental protection, leading to the vigorous development of various water environment monitoring technologies. The increasing demand in gaining water quality information has driven the research in recent decades toward more selective and sensitive monitoring technique developments, especially for new emerging contaminants. Membrane-based monitoring techniques thus attract significant research attention due to their highly selective and accumulative nature that could be a solution for achieving effective and reliable water quality monitoring. In recent years, a variety of potential water contaminants, especially some inorganic and organic substances in different water bodies,

Environmental monitoring and membrane technologies: a possible marriage? 111 such as lake water, river water, estuary water, seawater, wastewater, and tap water, have been systematically studied using membrane-based methods. As mentioned in Section 4.2, both direct sampling and detection, and passive sampling and detection methods can be used in water pollutants monitoring. According to the membraneinduced separation pattern differences in direct sampling and detection methods for the water environment, these methods can be further categorized as dialysis methods and gasdiffusion-based methods. Unlike grab or time-averaged sampling methods that provide instantaneous or time-averaged analyte concentration over a designed deployment period, dialysis methods typically respond much faster because the detector is usually implanted in the sensing device, whereby fluctuations in analyte concentrations can be continuously monitored. However, due to the lack of discrimination, dialysis methods are conventionally regarded as a molecular sieve-like separation technique instead of a selective sensing method. Despite that, many studies still used this method as a sample pretreatment step since macromolecules could be excluded from passing the sample through the membrane, hence minimizing interference. For water environment applications, dialysis methods had frequently been an on-line incorporation with electrochemical detectors (Vargas et al., 2016), molecular absorption spectrophotometry (Nagul et al., 2013), atomic absorption spectrometry (van Staden et al., 1998), liquid chromatography (Jen et al., 2001), and spectrophotometric detectors to monitor trace analytes (Mataix & Luque De Castro, 2001). A representative setup of dialysis methods can be found in work presented by Pinger and coworkers, who developed a 3D-printed equilibrium dialysis device that can be used for the monitoring of different ions (Pinger et al., 2017). Gas-diffusion-based methods were applied to determine volatile compounds in aquatic samples. The membranes used are typically polymeric nonporous or porous hydrophobic membranes, which are usually inactive to the tested environment. The extraction of the gaseous species is motivated by the diffusion gradient caused by the difference in chemical potential between two sides of the membrane, e.g., gradients in temperature, (partial) pressure, concentration, as well as the electrical potential of the analyte. The major advantages of this method are the fast diffusion process that can spontaneously proceed at room temperature, which ensures fast detection. More importantly, the method eliminates all the ionic species interference since only gaseous species can diffuse through the hydrophobic membrane. This method can also be easily incorporated in the currently available automatic measurement systems, such as flow injection analysis (FIA) (Somboot et al., 2017), capillary electrophoresis (CE) (RuizJime´nez & de Castro, 2006), gas chromatography (Ripatti et al., 2019), and highperformance liquid chromatography (Hylton & Mitra, 2007) to monitor a wide variety of water contaminants. According to this principle, a gas-permeable membrane was incorporated with a conductometric detector for real-time in situ monitoring of ammonia in aquatic environments, which offered an effective tool for obtaining insightful ammonia distribution information in water environments. Tables 4.1 and 4.2 summarize some typical

Table 4.1: Membrane-based direct sampling and detection of organic compounds in all kinds of water bodies.

Detection limit

Response/ sampling time

Analyte

Membrane

Detection principle

Oxalate

Modified cellulose acetate film

OD

0.007 μg/mL

, 9s

Toluene

Ethylenepropylene copolymer

OD

80 μg/L

—

Poly(acrylonitrile-cobutadiene)

OD

10 μg/L

—

Teflon

OD

27 μg/L

—

Polyisobutylene

OD

337 μg/L

—

Polydimethylsiloxane nonporous membrane Hollow fiber silicone membrane

CG

0.6 μg/L

15 min

MS

244 ng/L

2.1 min

Chloroform

Hollow fiber silicone membrane

MS

, 2.78 μg/L

1.1 min

CG

, 25 μg/mL

20 min

Volatile halogenated organic compounds Sulfadimethoxine

Polydimethylsiloxane nonporous membrane Semipermeable hollow fiber polydimethylsiloxane membrane Modified PVC membrane

MS

,1 μg/mL

—

ED

7.5 ng/mL

2 min

Diclofenac

PVC membrane

ED

1.1 3 1027 M

60 s

CG, Chromatograph; ED, electrochemical detection; OD, optical detection; Ms, mass spectrometry.

Sample type

References

Food and environmental water Environmental Water Environmental Water Environmental Water Environmental Water Wastewater

Kazemzadeh and Moztarzadeh (2005)

Environmental water Environmental water Swimming-pool water River Environmental water Wastewater

Karlowatz et al. (2004) Flavin et al. (2006) Flavin et al. (2006, 2007) Yang and Tsai (2002) Liu and Pawliszyn (2005) Nelson et al. (2004) Nelson et al. (2004) Liu and Pawliszyn (2005) Letourneau et al. (2015) Almeida et al. (2013) Elbalkiny et al. (2019)

Table 4.2: Membrane-based direct sampling and detection of inorganic compounds in all kinds of water bodies. Analyte

Membrane

Detection principle

Response/ Detection limit sampling time Sample type

Carbonate, Ca21 Pb21 Phosphate

Polymeric membrane

ED

1 μM



Freshwater

Polymer membrane Imprinted polymer membrane

ED ED

711 μg/mL 0.16 mg P/L

30 s 

Water Wastewater

ED

2.01026 M

22 s

Wastewater

Cu21

Plasticized membranes using copper-carboxybenzotriazole Modified agarose membrane

OD

0.07 μg/L

4 min

Environmental water

Nitrite

Modified cellulose acetate film

OD

1 ng/mL

, 7s

Carbonate Ca21 NH41

Ion-selective membranes Ion-selective membranes Ion-selective membranes

ED ED ED

2 μM 1 μM 0.3 μM

  

Food and environmental water Freshwater Freshwater Freshwater

NH41

Ion-selective membranes

ED

30 μM



Freshwater

NO32

Ion-selective membranes

ED

0.1 μM

, 1 min

Freshwater

NO32

Ion-selective membranes

ED

0.5 μM



Seawater

NO32

ED

0.3 μM



Freshwater

NO22

Carbon black modified ionselective membranes Ion-selective membranes

ED

0.5 μM



Freshwater and seawater

Phosphate Cl2 Pb21 Cr31

Ion-selective Ion-selective Ion-selective Ion-selective

ED ED ED ED

10 μM 2.45 mg/L 0.3 μM 0.1 μM

 , 10 s 25 s 

Wastewater Freshwater Wastewater Wastewater

Cu21

Ion-selective membranes

ED

5 nM



Wastewater

Cu21

micromembranes micromembranes membranes membranes

References Pankratova et al. (2015) Sun et al. (2019) Warwick et al. (2014) Abu-Dalo et al. (2015) Hashemi et al. (2008) Kazemzadeh and Daghighi (2005) Yuan et al. (2015) Ping et al. (2013) Athavale et al. (2015) Dumanli et al. (2016) Le Goff et al. (2003) Cuartero et al. (2015) Paczosa-Bator et al. (2014) Pankratova et al. (2017) Lee et al. (2009) Cheng et al. (2012) Guo et al. (2011) ´nchez-Moreno Sa et al. (2009) Ganjali et al. (2015) (Continued)

Table 4.2: (Continued) Analyte

Membrane

NH41

Hydrophobic polytetrafluoroethylene millipore membrane Crown-ether membrane Crown-ether membrane Solid-state membrane

Cd21 Pb Phosphate

Cr(VI) Hg(II) Uranyl ion Nitrite ion Pb(II) Fe31 NH41

PVC membrane P4VP-g-PVDF nanoporous membrane PVC membrane Triacetyl cellulose polymeric membrane Solid-state ion selective membrane PVC membrane

Detection principle

Response/ Detection limit sampling time Sample type

References

ED

2 μg/mL

Environmental water

Li et al. (2017a)

ED ED ED

6 3 1029 M  8 3 1029 M  ,1.0 3 1026 M , 60 s

Tap water Tap water Surface water

OD ED

1.1 3 1025 M 0.1 μg/mL

714 min 

ED

2.0 3 1028 M

2 min

River water Mineral water/ ground water/ surface water Tap and seawater

OD

0.08 μg/mL

4548 min

Spring water and sewage

ED

2 μg/mL

5s

Wastewater

Betelu et al. (2007) Betelu et al. (2007) Tafesse and Enemchukwu (2011) Gu ¨ell et al. (2007) Pinaeva et al. (2019) Metilda et al. (2007) Afkhami et al. (2012) Fan et al. (2020)

ED

3.6 3 1027 M

10 s

Tap and mineral water

ED

1026.5 M

510 s

Wastewater

Zamani et al. (2009) Huang et al. (2019)

, 1s

ED

1025.3 M

510 s

Wastewater

Huang et al. (2019)

Cu(II)

Solid-state ion selective membrane Solid-state ion selective membrane Polymer inclusion membrane

OD

0.06 mg/L



Natural and wastewaters

Pr(III)

PVC membrane

ED

5.2 3 1028 M

8s

Tap, mineral and river water

Jayawardane et al. (2013) Pourjavid et al. (2012)

NO32

ED, Electrochemical detection; OD, optical detection.

Environmental monitoring and membrane technologies: a possible marriage? 115 organic and inorganic substances measurement in water using direct sampling and detection methods. Passive sampling and detection methods, either DGT techniques or other sampling ˇ et al., 2020), used binding agents to immobilize the techniques (Sraj et al., 2018; Sraj analyte(s) for subsequent measurement. The mechanism of this technique can be seen in Section 4.2. Since passive sampling can use the same binding agents and corresponding device structures to monitor pollutants in both water and soil, the applications of passive sampling in water and soil will be summarized together in Table 4.4, according to the types of binding agents used in binding layers.

4.3.2 Soil environment The soil system is another critical environmental ecosystem where contaminant information needs to be effectively monitored to serve environmental protection purposes. The broad soil system includes not only industrial, agricultural, and living production land but also wetland systems and sediment systems close to various water bodies. It is worth mentioning that, due to the characteristics of poor fluidity, poor uniformity and complex composition of the soil, soil pollution presents irreversibility, concealment, accumulation, and an hysteretic nature that is challenging to control compared to water pollution and air pollution, which makes reliable and efficient soil monitoring technologies urgently needed. Up to now, the use of in situ membrane-based monitoring technology has provided scientific insights into understanding the environmental behavior, environmental effects, bioavailability, and toxicity of pollutants such as heavy metals, organics, nutrients, and other pollutants in soil ecosystems such as farmland, sediments, and wetlands. Among these technologies, DGT has been recognized as the most effective and most promising green sampling technology in soil environment monitoring. In the past 20 years, with the improvement of the binding membrane and the exploration of new binding agents, DGT has been developed from low capacity to high capacity, and the particle size of the binding membrane has changed from the micrometer to nanometer range and from a single binding agent to composite binding agents, which greatly expand its application ability. Specifically, many new specific binding materials have been successfully synthesized and used in new DGT developments for the speciation analysis of heavy metals in soil. Pan employed functionalized N-methyl-D-glucamine resin as a DGT binding layer for selectively measuring Cr(VI), which presented a large adsorption capacity, low detection limit, and strong antiinterference ability, suggesting its feasibility for in situ monitoring of Cr speciation and further evaluation of Cr risk in soil (Pan et al., 2015). Fan introduced mercapto-functionalized silica to DGT devices, for the first time, to determine dissolved inorganic Sb(III), which showed outstanding ability for speciation measurements of Sb(III) in both water and sediment environments (Fan et al., 2016). Similarly, Bennett successfully presented DGT that used a binding layer comprising a thiol-based adsorbent

116 Chapter 4 (3-mercaptopropyl functionalized silica gel) to selectively measure Sb(III) in different water bodies (Bennett et al., 2016). Also, his research group confirmed that DGT with titanium dioxide-based adsorbent (Metsorb) could achieve selective measurement of Se(IV) within practical limits of accuracy in water and sediment systems (Bennett et al., 2010). Besides, environmental behaviors and the effects of some organic matters investigated by DGT have been revealed in recent years. Chen first applied DGT for the measurement of organics (named o-DGT sampler) in soil systems to investigate the mobility and lability of four typical antibiotics—sulfamethoxazole, sulfamethazine, and sulfadimethoxine, trimethoprim. The results suggested that o-DGT is a useful analytical tool for obtaining insightful information of polar organic chemicals in soil, and it enables in situ assessing their bioavailability (Chen et al., 2015). Similarly, Cole et al. (2018) employed silica-bound sorbents as DGT adsorption gels that enable the preconcentration of five organotins (dibutyltin, diphenyltin, monobutyltin, triphenyltin, and tributyltin) that are frequently found in coastal sediment. The findings revealed that C8 sorbent possessed optimum performance in uptake and recovery of organotins in a pH between 4 and 9 with a designed ionic strength (0.011 M NaNO3), suggesting its potential of being a practical analytical tool in acquiring the speciation and migration of these contaminants (Cole et al., 2018). Moreover, DGT also provided an important basis for exploring soil bioavailability, especially the prediction and absorption mechanism of plant absorption of heavy metals. A representative work was done by Nolan et al. (2005) who investigated the speciation and availability of Zn, Cu, Pb, and Cd in various well-equilibrated metal-contaminated soils from different sources using DGT-based samplers for the prediction of metal uptake by plants. The data showed that the kinetically labile solid-phase pool of metal played an crucial role in Zn and Cd absorption by wheat (Nolan et al., 2005). Tian compared the performances of DGT device with other techniques for metal measurement in a paddy field and the results verified DGT is significantly superior to other methods (such as soil solution, CaCl2 extractions, and HAC extractions), and revealed for the first time that the DGT measurement quantitatively incorporates main factors reflecting bioavailability (Tian et al., 2008). With the development of soil monitoring technologies in recent decades, the current soil monitoring is rapidly developing toward multitarget pollutant monitoring, trace monitoring, and rapid and portable in situ monitoring. Table 4.3 summarizes the application of direct membrane-based technology in soil environment monitoring, and Table 4.4 summarizes the application of the passive sampling method in water and soil based on the types of binding agents used in binding layers.

4.3.3 Atmospheric environment With the increasing frequency of air pollution incidents in recent years, air quality has received more and more attention from the public, which puts forward restricted requirements on air quality monitoring, leading to the rapid development of atmospheric

Table 4.3: Membrane-based direct sampling and detection of organic and inorganic compounds in soil. Detection principle

Response/ Detection limit sampling time

Sample type

References

ED

5.8 3 1026 M , 5 s

Farmland soil

ED

4.6 3 1026 M 8 s

Soil

Ion-selective membrane

ED

1.3 mg/ L

2 min

Soil slurries

PVC-based polymericmembranes Polymer microporous membrane Polyimide films

OD

0.03 mg/L

Near real-time

OD

-

Near real-time

Aqueous extracts of soil Soil

EB

0.53 pM

20 s

Soil slurry

Kamel et al. (2019) Hassan S. et al. (2019) Ali et al. (2019) Lvova et al. (2020) Leone et al. (2017) Hondred et al. (2020) Lazik et al. (2019) Kumar et al. (2021) Bandi et al. (2014)

Type

Analyte

Organic compounds

Flucarbazone Polyaniline film and ionanion sensing membrane Dimethylamine PVC membrane Nitrate Cu(II)

Inorganic compounds

Moisture Paraoxon

Membrane

ED

0.1%



Natural soil

K1

Tubular gas selective membrane Valinomycin membrane

ED

0.1 μM



Laterite soil

Cu21

Polymeric membrane

ED and OD

1.2 3 1028 M 9 s

CO2

OD, Optical detection; ED, electrochemical detection; EB, electrochemical biosensor.

Soil

Table 4.4: Membrane-based passive sampling and detection of organic and inorganic compounds in water and soil. Applied condition Type

Analyte

Organic Drugs: methcathinone and ephedrine compounds Antibiotics: sulfamethoxazole, sulfamethazine, sulfadimethoxine, and trimethoprim Drugs: ketamine, methamphetamine, and amphetamine Perfluoroalkyl substances: perfluorooctanoic acid, and perfluorooctane sulfonate Antibiotic-sulfamethoxazole Endocrine disrupting chemicals: estrogens, alkyl-phenols, and bisphenols Antibiotics Tetracyclines Endocrine disrupting chemicals Organotins: monobutlytin, dibutyltin, tributyltin, diphenyltin, triphenyltin Personal care products: preservatives, antioxidants, and disinfectants Anionic pesticides Bisphenols: BPA, BPB, and BPF

Binding agents

pH

Ionic strength

Sample type

References

Resin XAD18

411

Surface water

Zhang et al. (2018a)

Resin XAD18

6.37.6

0.0010.5 M NaCl 

Soil

Chen et al. (2015)

Resin XAD18

49

Water

Guo et al. (2017)

Resin XAD18

48

Guan et al. (2018)

Resin XAD18

69

Surface waters and wastewaters Water

Resin XAD18

3.59.5

Wastewaters

Chen et al. (2018)

Resin XDA-1 Nanosized zinc oxide particles Resin XDA-1 C8 silica sorbent

7.38.9 59

Coastal waters Pig breeding wastewater Seawater Coastal sediment Surface water

Xie et al. (2018a) You et al. (2019)

Surface water

Guibal et al. (2017)

Surface water

Zheng et al. (2015)

hydrophiliclipophilicbalanced Oasis HLB or Oasis MAX sorbent Activated charcoal

79 49 3.59.5 38 48

0.0010.1 M NaCl 0.01 M NaCl

0.0010.1 M NaCl 0.0010.5 M NaCl 0.50.8 M NaCl 13 M NaCl 0.40.8 M NaCl 0.011 M NaNO3 0.0010.1 M NaCl 10221 M NaCl 0.0010.01 M NaCl

Chen et al. (2012)

Xie et al. (2018b) Cole et al. (2018) Chen et al. (2017)

Heavy metals

La(III), Lu(III), Ce(III), Tm(III), Pr(III), Dy (III), Er(III), Gd(III), Nd(III), Eu(III), Tb(III), Ho(III), Yb(III), Sm(III), and Y(III) Ni, Mn, Cu, As, Cr, Co, Pb, Fe, and

Chelex100

39

3100 mM NaCl

Soil

Yuan et al. (2018)

Chelex100

79

0.01 M NaNO3

Gao et al. (2009)

Ni, Cr, Zn, Cu, Cd, and As

Chelex100

39



Cd, Ni, Pb, Cu, Zn, and Co

48



Au(III)

Suspended particulate reagentiminodiacetate Activated carbon

Coastal sediment Freshwater sediments Water

29.5

0.012 M NaCl

Mo, As, V, Sb, and W

Ferrihydrite

48



Se(IV), V(V), Se(VI), As(III), As(V), and PO432 Uranium

Ferrihydrite and Metsorb

48

0.0010.2 M NaNO3 1.0 3 10241.0 M NaCl 0.010. 5 M NaNO3 0.(0005)0.1 M NaCl 0.0010.05 M NaNO3 0.0010.05 M NaCl 0.00050.1 M NaCl . 0.005 M NaCl

Cr(VI) and Cr(III)

Whatman DE 81 with 19 amino binding functional groups Whatman DE 81 49

Hg(II)

P81 Whatman

3.58.5

V

Amberlite IRA 910

39

As(V)

Amberlite IRA 910

59

Methylmercury

Saccharomyces cerevisiae

3.58.5

Pb

Saccharomyces cerevisiae

4.58.5

V(V), As(V), Sb(V), Mo(VI), and W(VI)

Metsorb

3.988.24

As(III), As(V), and SeI(V)

Titanium dioxide-based adsorbent Tulsion CH-95

3.58.5

CH3Hg1 and Hg21

CH3Hg1: pH4.18.1, Hg21: pH4.110.03

0.0010.7 M NaNO3 0.00010.75 M NaNO3 0.11000 mM NaCl

Natural Waters Surface water Freshwater and seawater River

Song et al. (2018) Warnken et al. (2004a, 2004b) Lucas et al. (2012) ¨ sterlund et al. O (2010) Price et al. (2013) Li et al. (2006)

Water

´rez et al. (2016) Sua

River

Destro Colac¸o et al. (2014) Luko et al. (2017)

River and acid drainage water River Rolisola et al. (2014) River River and seawater Water Freshwater and seawater Sediment

Tafurt-Cardona et al. (2015) Pescim et al. (2012) Panther et al. (2013) Bennett et al. (2010) Ren et al. (2018)

(Continued)

Table 4.4: (Continued) Applied condition Type

Analyte

Binding agents

pH

Ionic strength

Sample type

References

P(V), Mo(VI), Cr(VI), Sb(V), As(V), V(V), W (VI), and Se(VI) As(III) and As(V)

Zirconium oxide

4.428.45

Zirconium oxide

2.09.1

Zirconium hydroxidesilver iodide Zirconium hydroxide and suspended particulate reagentiminodiacetate ZrOChelex

49

Freshwater and seawater Freshwater and seawater Sediment

Ding, SM et al. (2016) Sun et al. (2014)

As and S(II)

0.1500 mM NaCl 0.01750 mM NaCl 0.01100 mM NaCl 1100 mM NaNO3

Sediment

Kreuzeder et al. (2013)

59

23 mM 750 mM NaCl

ChelexMetsorb

5.038.05

Chelexferrihydrite

38

Mercapto-functionalized silica 3-Mercaptopropyl functionalized silica

38

0.0010.7 M NaCl 0.0010.1 M NaCl 0.0010.7 M NaNO3 0.0011.0 M NaCl

NO3-N

Purolite A520E

3.58.5

NH41-N

Microlite PrCH cation exchange resin AMI-7001 anion exchange membranes CMI-7000 cation exchange membranes Divinylbenzene-based absorbent with amine functional groups

3.58.5

P, As, Cu, Co, Zn, and Mn

Cd(II), Fe(II), Co(II), Sb(V), Ni(II), Cu(II), Zn(II), Pb(II), P(V), Mn(II), V(V), As(III)/As (V), Se(VI), Mo(VI), W(VI), and Cr(VI) Co, Mn, Cu, Ni, Cd, Pb, As, V, Sb, Mo, W, and P As, Cu, Cd, Zn, and Pb Sb(III) Sb(III) and As(III)

Nutrients

NO3-N NH41-N NO3-N

48

4.078.05

3.58.5 3.58.5 38

0.00010.008 M NaCl , 0.012 M NaCl 0.00010.014 M NaCl 0.00030.012 M NaCl 00.018 M NaCl

Xu et al. (2018)

Freshwater Wang et al. (2017) and seawater, sediments Freshwater Panther et al. (2014) and seawater Water and soil Huynh et al. (2012) Water

Fan et al. (2016)

Contaminated freshwater sediment Freshwater

Bennett et al. (2016)

Freshwater

Huang et al. (2016c)

Freshwater

Huang et al. (2016a)

Freshwater

Huang et al. (2016a)

Paddy soil

Cai et al. (2017)

Huang et al. (2016b)

Liquid binding agents

NH41-N

Microsized zeolite

38

P

Zirconium oxide

310

S22 K1

AgI .8 Amberlite IRP-69 cation 48 exchange resin 0.050 M of ethyleneimine 48

Cu21, Cd21, and Pb21 Cu21, Cd21, and Pb21 Cu21 and Cd21 Cu21 Cu21 and Cd21 Dissolved reactive phosphorus

Hg21 As(III) and As(V) Dissolved reactive phosphate Dissolved reactive phosphate

Solution of polymerbound Schiff base 0.003 M of sodium polyacrylate 0.030 M of polyvinyl alcohol Poly(4-styrenesulfonate) aqueous solution Polyquaternary ammonium salt aqueous solution Thiol-modified carbon nanoparticle suspension Nanoparticulate Fe3O4 aqueous suspension Iron oxide nanoparticles Zr-based metal organic frameworks

48.5 48 5.68.6 48 310

Around 7 4.59 310 6.58.5

0.00110 mM NaCl 10 nM-0.1 M NaCl 0.01 M NaNO3 0.001 M or 0.01 M NaCl 1 3 10240.1 M NaNO3 1 3 10240.1 M NaCl Low ionic strength 1 3 10240.7 M NaCl Low ionic strength 10241 M NaNO3 0.0010.5 M NaNO3 0.0010.5 M NaNO3 0.0010.5 M NaNO3 0.01100 M NaCl

Water

Feng et al. (2015)

Sediment

Ding et al. (2010)

Water Soil

Teasdale et al. (1999) Tandy et al. (2012)

Water

Sui et al. (2013)

Water

Fan et al. (2013)

Natural river water River water sample Freshwater

Fan et al. (2009b)

Water

Chen et al. (2014)

Water

Wu et al. (2017)

Water

Liu et al. (2016)

Water

Zhang et al. (2018b)

Lake water

Qin et al. (2018)

Fan et al. (2009a) Li et al. (2005b)

122 Chapter 4 monitoring technologies. Due to the high flexibility of membrane technology, it can be effortlessly used together with different detection methods (e.g., chemical detection, optical detection, etc.) and operation methods (e.g., FIA, microfluid control, CE, etc.) to achieve efficient, reliable, and accurate air quality monitoring. In terms of the membrane-based electrochemical sensors, the first potentiometric gas sensor was developed by Severinghaus and Bradley, which employed polytetrafluoroethylene membrane to determine CO2 in blood (Severinghaus & Bradley, 1958). After that, Strickler and Beebe introduced polyvinyl fluoride membrane to the potentiometric principle to create the first ammonia gas sensor serving environmental monitoring purposes (Strickler & Beebe, 1972). Besides, the first gas membrane-based amperometric sensor was invented by Clark for measuring O2, and the first gas membrane-based conductimetric ammonia sensor was developed by Hendricks (Hendricks et al., 1942). With regards to the membrane-based optical sensors, CO2 sensor based on fluorescence detection, ammonia fiber optic sensor based on light absorbance, O2 sensor based on fiber optic fluorescing measurement, as well as air quality pollutants (e.g., parathion and formaldehyde) monitoring based on biochemical colorimetric determination have been developed, and extensive membrane-based optical gas sensing techniques with good specificity, precision, and stability have experienced ever-increasing development over the past few decades (Arnold & Ostler, 1986; Wolfbeis & Posch, 1986; Wolfbeis et al., 1988; Zhujun & Seitz, 1984). In addition, the combination with the flow injection method further offers a wide range of application opportunities for membrane-based gas sensors in a variety of environmental areas (Frenzel, 1990). Table 4.5 summarizes the typical membrane-based gas monitoring technologies for environmental monitoring. Table 4.5: Membrane-based atmospheric gas monitoring methods. Analyte

Operation method

Principle

Electrode or recognition component

Detection limit

CO2

PB

Potentiometry

pH electrode



O2

PB

Potentiometry



NH3

PB

Potentiometry

1028 M

Frenzel (1990)

Cyanide

PB

Potentiometry



SO2

PB

Potentiometry

O2 electrode with zirconium dioxide solid electrolyte Ammonium sensitive liquid membrane electrode Metallica silver wire electrode Crystalline iodide doublemembrane tubular electrode

Severinghaus and Bradley (1958) Dietz (1982)

Frenzel et al. (1990) Araujo et al. (1998)

O2

PB

Amperometry

Gold disc voltammetric microelectrode

10%

3.2 mg/L

References

McPeak and Hahn (1997) (Continued)

Environmental monitoring and membrane technologies: a possible marriage? 123 Table 4.5: (Continued) Analyte

Operation method

Principle

N2O

PB

Amperometry

Ethylene

PB

Amperometry

Ethyl alcohol

PB

Amperometry

Acetaldehyde

PB

Amperometry

Acetylene

PB

Amperometry

SO2

PB

Amperometry

H2

PB

Amperometry

NH3 NH3

FIC PB

Conductimetry Conductimetry

Cl2

PB

Conductimetry

CO2

FIO

NH3

FIO

Formaldehyde PB

Optical (detection wavelength 554 nm) Optical (detection wavelength 590 nm) Amperometry

Ethanol

PB

Phenol Benzene vapor NO

Electrode or recognition component

Detection limit

Gold disc voltammetric microelectrode Gold deposited gas-diffusion electrode Gold deposited gas-diffusion electrode Gold deposited gas-diffusion electrode Gold deposited gas-diffusion electrode Gold deposited gas-diffusion electrode Tungsten carbide-based gas-diffusion electrode Boric acid Boric acid

10% 40 μg/L 2 μg/L 1 μg/L 20 μg/L 0.6 μg/L 1% 0.3 vol.% 1 μg/L

References McPeak and Hahn (1997) Jordan et al. (1997) Hodgson et al. (1999) Hodgson et al. (1999) Hodgson et al. (1999) Hodgson et al. (1999) Nikolova et al. (2000) ˇ (1997) Kuba´n Li et al. (2019c) Zhou et al. (2021b)

9 μg/L N,N-diethyl-pphenylenediamine sulfate salt Mixed acid/base indicator 2.50 Satienperakul 3 102 μg/ L et al. (2004) Colorimetric dye



Schmitt et al. (2012)

2 μg/L

Amperometry

Formaldehyde dehydrogenase Alcohol oxidase enzyme

0.36 mg/ L

PB

Amperometry

Tyrosinase enzyme

22 μg/L

PB

Optical detection

Bioluminescent bacteria

0.2 vol.%

PB

Optical detection

Protein doped solgel thin film

1 mg/L

Ha¨mmerle et al. (2008) Mitsubayashi et al. (1994) Kaisheva et al. (1997) Cheol Gil et al. (2000) Aylott et al. (1997)

FIC, Flow injection conductimetry; FIO, flow injection optic method; PB, probe.

4.4 Conclusions and future trends Highly selective and sensitive monitoring methods are of great practical application value for environmental protection purposes. For decades, scientists and engineers have made enormous efforts to develop methods that can meet these objectives and support the increasingly strict requirements for environmental monitoring. The marriage of membrane

124 Chapter 4 technologies with environmental monitoring has great potential to improve environmental sensing capability and provide sufficient high-resolution data to reduce any potential health risks and better guide the implementation of environmental remediation strategies. Up to now, the innovative corporation of different types of membranes with different physical/ chemical/biological detection principles can already support environmental data collections use for: 1. Water environment monitoring. Based on advanced monitoring technology, the sources, distribution, migration, and changes of pollutants in various water bodies can be systematically studied, and the trend of water pollution can be timely predicted to achieve comprehensive protection of water resources and water safety. 2. Soil environment monitoring. Studying the soil quality background information, monitoring and forecasting the change of the soil environment can be capable of achieving soil pollution investigation and soil pollution prevention and control, so as to scientifically and effectively repair and control the soil environment in a targeted manner. 3. Atmospheric environment monitoring. On the one hand, tracking and monitoring the concentration and change of pollutants in the atmospheric environment can provide a basis for the traceability and prevention of atmospheric pollution. On the other hand, regularly monitoring public weather is of great significance for long-term meteorological forecasting, climate analysis and evaluation, atmospheric environment evaluation, and agricultural meteorological services. Currently, despite the advances in membrane-based monitoring devices, most of the measurements are based on the passive samplinglab analysis mechanism where challenges still exist to meet the practical needs in today’s smart sensing era due to the cost and welltrained labor involved. Additional research is needed to provide "all-in-one" solutions to different application scenarios. A critical path could be taking advantage of the development in electronic and computing technology to realize instrumentation, computerization, and automation so as to achieve real-time analysis in membrane-based devices without human intervention during long periods of time. In this regard, researchers have already made attempts to achieve real-time in situ environmental monitoring. For example, by integration of a gas-permeable membrane with a conductometric detector, ammonia profiles can be in situ real-time monitored (Li et al., 2019c). Such an implementation model can be readily configured to measure other gaseous compounds by changing the recognition reagent and the transducer (optical or electrochemical) or using a different membrane. This could be a direction for future sensor developments for environmental monitoring. As a critical component in the device, advanced membrane development is also a restraining factor hindering progress in this field as it determines method selectivity to a great extent. Overall, membrane-based environmental sensors offer superior advantages in improving method sensitivity and selectivity that might open a new horizon for sensing system development to meet today’s environmental monitoring needs.

Environmental monitoring and membrane technologies: a possible marriage? 125

Acknowledgment The authors gratefully acknowledge the financial supports from National Natural Science Foundation of China (No. 21806080), and The Start-up Foundation for Introducing Talent of NUIST (No. 2018r017).

Acronyms 3D CE CG DBT DET DGT DPhT ED FAAS FIA FIC FIO GPMCS ICPO-OES Metsorb Ms OD o-DGT PANI PB PVC

Three-Dimensional Capillary Electrophoresis Chromatograph Dibutyltin Diffusive Equilibrium in Thin Films Technique Diffusive Gradient in Thin-film Technique Diphenyltin Electrochemical Detection Flame Atomic Absorption Spectrophotometry Flow Injection Analysis Flow Injection Conductimetry Flow Injection Optic method. Gas Permeable Membrane-based Conductimetric Sensors Inductively Coupled Plasma Optical Emission Spectrometer Titanium Dioxide-based Adsorbent Mass Spectrometry Optical Detection DGT for the determination of organics Polyaniline Probe Polyvinyl Chloride

Symbols A M P P1 P2 A D M Δg δ

Analyte Membrane component Product Product 1 Product 2 Exposed surface area of the DGT device Diffusion coefficient of the analyte in the diffusive layer Accumulated mass of analyte in the binding gel Diffusive layer thickness Diffusive boundary layer thickness

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CHAPTER 5

Potentially toxic elements (As, Cd, Cr, Hg, and Pb), their provenance and removal from potable and wastewaters Warren R.L. Cairns1,2, Carmine Apollaro3, Ilaria Fuoco3, Giovanni Vespasiano3, Antonio Procopio4, Olga Cavoura5 and Massimiliano Varde`1,2 1

Institute of Polar Sciences (ISP), National Research Council of Italy (CNR), Venice-Mestre, Veneto, Italy, Department of Environmental Sciences, Informatics and Statistics (DAIS), Ca’ Foscari University of Venice (UniVE), Venice-Mestre, Veneto, Italy, 3Department of Biology, Ecology and Earth Sciences (DIBEST), University of Calabria (UniCAL), Arcavacata di Rende, Calabria, Italy, 4Department of Health Sciences, University Magna Graecia (UMG), Catanzaro, Calabria, Italy, 5Department of Public Health Policy, School of Public Health, University of West Attica, Athens, Greece 2

5.1 Introduction 5.1.1 General overview Potentially toxic elements are naturally occurring constituents of the Earth’s crust characterized by high toxicity at low concentration (Carolin et al., 2017). Such elements include cadmium (Cd), chromium (Cr), lead (Pb). and mercury (Hg), and the metalloid, arsenic (As). Because of their nonbiodegradability, and thus their tendency to accumulate in environmental media, pollution by such elements is a major environmental issue worldwide (Rahman & Singh, 2019), particularly when natural and/or anthropic processes result in their release to ground and surface waters. On the basis of harm, probable human exposure, and occurrence rate, As, Pb, Hg, Cd, and hexavalent Cr(VI) were classified in 1st, 2nd, 3rd, 7th, and 17th place, respectively, in the priority list of harmful substances (ATSDR, 2019), whereas the World Health Organization (WHO) has set threshold values in drinking water at 10 µg/L for As, 3 µg/L for Cd, 50 µg/L total Cr, 0.6 µg/L for Hg, and 10 µg/L for Pb (WHO, 2017). The geochemical behavior of these elements, their environmental transport, and their accumulation in aquatic systems vary depending on natural sources, contamination levels, and local geochemical conditions.

Current Trends and Future Developments on (Bio-) Membranes. DOI: https://doi.org/10.1016/B978-0-12-824103-5.00005-X © 2023 Elsevier Inc. All rights reserved.

137

138 Chapter 5

5.1.2 Arsenic Arsenic (As) is a metalloid occurring in air, rocks, soils, water, and living organisms. In the atmosphere, it can be released from volcanic activities, wind erosion, emissions from soils due to low-temperature volatilization, marine spray, forest fires, and from anthropogenic inputs (Sa´nchez-Rodas et al., 2015), the latter contributing to about 30%
70% of global As release (Flora, 2014; Smedley & Kinniburgh, 2002). Airborne As is transferred to water bodies through wet or dry deposition. In rural areas As concentrations in rainfall and snow are commonly less than 0.03 µg/L, whereas in zones affected by anthropogenic activities, As concentration is in the range 0.5
16 µg/L (Flora, 2014; Smedley & Kinniburgh, 2002). A large number of primary and secondary minerals1 (.200) contain As both as an essential structural constituent and a trace component (Drahota & Filippi, 2009; Majzlan et al., 2014; Smedley & Kinniburgh, 2002). The As-bearing mineral group includes arsenates, sulfides and sulfosalts, oxides, arsenides, arsenites, silicates, metal alloys, and elemental As (Majzlan et al., 2014; Mandal & Suzuki, 2002; Smedley & Kinniburgh, 2002). However, the primary As-minerals are relatively rare and only some of these are commonly found in the natural environment, such as arsenopyrite (FeAsS) and As-rich pyrite (Fe(S,As)2) (Mandal & Suzuki, 2002; Smedley & Kinniburgh, 2002; Sracek et al., 2004; Tabelin et al., 2018). The latter represents the main sulfide mineral which plays a prominent role in As environmental pollution (Deditius et al., 2008; Smedley & Kinniburgh, 2002). It can incorporate variable amount of As, occasionally in excess of 10% by weight (Abraitis et al., 2004; Barker et al., 2009; Blanchard et al., 2007; Lipfert, 2006; Reich & Becker, 2006; Savage et al., 2000; Zacharia´sˇ et al., 2004). These minerals are generally concentrated in hydrothermal veins or rocks affected by hydrothermal alteration (Flora, 2014; Tabelin & Igarashi, 2009). Secondary minerals, represented by As-oxides such as arsenolite (As2O3), Fe-arsenates such as scorodite (FeAsO4  2H2O), Fe-sulfoarsenates/sulfoarsenites, Ca and Mg arsenates, and other metal arsenates also influence As mobility in the environment (Drahota & Filippi, 2009). Average As concentration in the Earth’s crust ranges from 1.5 to 2.1 mg/kg (Kloprogge, 2020; Wedepohl, 1995; Yaroshevsky, 2006). Smedley and Kinniburgh (2002) reported a solid data collection of average As concentrations in different types of rocks. Igneous rocks generally contain ,5 mg/kg As, with the exception of volcanic rocks, such as volcanic glasses, that can incorporate c. 6 mg/kg As. Metamorphic rocks contain up to 5 mg/kg As, although phyllite and slates can have As concentrations up to 18 mg/kg, whereas in sedimentary rocks As concentration is usually in the range 5
10 mg/kg (Smedley & Kinniburgh, 2002).

1

Primary minerals are the constituents of igneous rocks formed during the crystallization of primeval magma, whereas the secondary minerals originate as a result of weathering processes.

Potentially toxic elements (As, Cd, Cr, Hg, and Pb), their provenance and removal 139 The weathering processes acting on As-containing rocks can lead to As mobilization in soils and waters depending on local geochemical conditions, such as redox potential and pH. After release from primary sources, the fate of As in the soil environment depends on factors such as sorption by soil solid phases, volatilization due to biological transformations, uptake by plants, and leaching due to water drainage (McLaren et al., 2006). The range for background As concentrations in uncontaminated topsoils worldwide is in the range 1
100 mg/kg (McLaren et al., 2006). Generally soil concentrations of As are of the order of 5
10 mg/kg (Smedley & Kinniburgh, 2002 and references therein) although As levels in soils are strongly linked to the parent material and the degree of weathering (McLaren et al., 2006). Oxidation of arsenian pyrite and other mineral sulfides starts at near ambient temperature (,50 C) and can be driven by dissolved oxygen (DO) or other oxidizing agents such as ferric ions and nitrates (Holmes & Crundwell, 2000; Ravenscroft et al., 2009). Bacteria can also act as catalysts, increasing the oxidation rates of sulfide minerals (Henke, 2009). However, As levels in groundwaters can increase also by mixing with geothermal waters (typically Asenriched) or as a result of release from Fe(III)-oxyhydroxides due to the occurrence of particular geochemical conditions (e.g., in alkaline or reducing environments) (Chauhan et al., 2009; Ravenscroft et al., 2009). Both amorphous and crystalline forms of Fe(III)oxyhydroxides play key roles in controlling dissolved As concentration (Sracek et al., 2004). The oxidation states of As are 23 (arsine), 0 (arsenic), 13 (arsenite), and 15 (arsenate). Inorganic As(V)- and As(III) species are the most common forms in aqueous systems (Figoli et al., 2020), although organic As species are also present, in the form of monomethylated acids and dimethylated acids in both As(III) and As(V) forms (Ravenscroft et al., 2009; Smedley & Kinniburgh, 2002). Under oxidizing conditions As(V) species prevail and undergo pH-dependent protonation
deprotonation reactions producing different oxyanionic species, such as H3AsO4, H2AsO42, HAsO422, and AsO432 (Mandal & Suzuki, 2002). Under reducing conditions, As(III) prevails with the uncharged complex H3AsO3 favored under acid and mildly alkaline conditions; while at pH .9.2 charged oxyanions H2AsO32 and HAsO322 dominate (Tabelin et al., 2018). Generally, As(III) is more mobile than As(V) between pH 3
8 because of the prevalence of its uncharged oxyanion, H3AsO3, making the adsorption processes more difficult from electrostatic point of view (Wang & Mulligan, 2006). However, both As(III) and As(V) can coexist in the same environment due to the slow oxidation rates of As(III) to As (V) when only DO is present as an oxidant (Tabelin et al., 2018). The As content of groundwaters can vary from ,0.05
5000 µg/L, whereas in open seawater the concentration is typically around 1.5 µg/L (Smedley & Kinniburgh, 2002).

5.1.3 Cadmium Cadmium (Cd) is a nonessential trace metal considered harmful for human health (UNEP, 2010). The mean emission of Cd from natural sources including volcanic activity,

140 Chapter 5 weathering, erosion, wind-blown dust, marine spray, and wildfire is quoted as 15,000
88,000 tons/year (Richardson et al., 2001; UNEP, 2010), while the emissions deriving from anthropogenic activities (e.g., smelting, mining, and agriculture) seem to be lower (Rahman & Singh, 2019). Only 27 minerals are known to contain Cd, generally as Cu-Pb-Zn ore minerals (Liu, Hystad, et al., 2017). Of these, greenockite (CdS) is the most significant, often occurring together with sphalerite (ZnS) because of geochemical similarity between zinc and cadmium. Other, albeit rare, Cd-bearing minerals are quadratite (Ag(Cd, Pb)AsS3), monteponite (CdO), otavite (CdCO3), burnsite (KCdCu217(SeO3)2O2Cl9), birchite (Cd2Cu2(PO4)2(SO4) 5H2O), edwardsite (Cu3Cd2(SO4)2(OH)6 4H2O), and keyite (Cu213Zn4Cd2(AsO4)6 2H2O) (Kloprogge, 2020). More common minerals, including sulfides and other deposits contain Cd as a trace component (Thornton, 1986). Concentrations of Cd in the Earth’s crust range from 0.15 to 0.20 mg/kg (Adriano, 2001; Kloprogge, 2020; Yaroshevsky, 2006). Several sources report that the igneous rocks contain Cd concentrations ranging from 0.001 to 0.60 mg/kg (Adriano, 2001; Kabata-Pendias, 2010). Slightly higher values (0.005
0.87 mg/kg) were detected in metamorphic rocks, whereas in certain sedimentary rocks, concentrations can reach 500 mg/kg (Adriano, 2001; Rambeau, 2006). Carbonate rocks usually contain a low amount of Cd (0.035
0.05 mg/kg) (Kabata-Pendias, 2010), although in some geological settings these rocks can contain higher Cd concentrations (Rambeau, 2006). Commonly, elevated Cd concentrations are related with black shales (Duan et al., 2020; Liu, Xiao, et al., 2017) and phosphorites (Garrett et al., 2008; Rambeau, 2006). The concentration of Cd soils is mainly associated to its abundance in the parent material as well as to atmospheric, agricultural, or industrial input (Kubier et al., 2019; Su et al., 2014). In unpolluted soils worldwide, the abundance of Cd is on average 0.36 mg/kg, although values depend on the country and the soil type (Kubier et al., 2019). Kabata-Pendias (2010) reported the average contents of Cd in soils lie between 0.06 and 1.1 mg/kg in different countries. Usually, the soils developed from igneous rocks contain the lowest concentrations of Cd (0.10
0.30 mg/kg), whereas 0.10
1.00 mg/kg and 0.30
11 mg/kg are the ranges of Cd concentration of soils deriving from metamorphic and sedimentary rock weathering, respectively. As with the other potentially toxic elements, the most important factors controlling Cd mobility are pH, redox potential, the presence of dissolved organic matter (DOM), inorganic carbon, as well as oxyhydroxides and clay minerals (Kubier et al., 2019). At near-neutral and alkaline pH values, the Cd mobility is very low due to its sorption to Fe(III)-oxyhydroxides and clay minerals, and its precipitation as silicate and carbonate minerals (Kubier et al., 2019). Conversely, it appears to be highly mobile in oxic and acidic waters (Kubier & Pichler, 2019). In the aquatic environment Cd is mostly present in the Cd(II) oxidation state and occurs as eight stable isotopes (Zhong et al., 2020). The main fraction of total soluble Cd comprises Cd21 ions, while the remaining fraction is present as inorganic and organic species such as

Potentially toxic elements (As, Cd, Cr, Hg, and Pb), their provenance and removal 141 CdCl1, CdCl20, CdCl32, Cd(SO4)222, CdSO40, CdHCO32, CdCO30, Cd(CO3)222, CdOH1, Cd(OH)20, Cd(OH)32, Cd2OH31, and CdNO31 (Kubier et al., 2019). Lower concentrations of Cd were detected in freshwaters (0.01
3 µg/L) than seawaters (,0.01
9.4 µg/L) (Adriano, 2001).

5.1.4 Chromium Chromium (Cr) is a potentially toxic pollutant occurring in atmosphere, minerals, rocks, and in derived soils, waters, and living organisms (Shanker et al., 2005; Zayed & Terry, 2003). Although anthropogenic activities input large amount of chromium (c. 75,000 ton; Kieber et al., 2002) annually to the atmosphere, in excess of 43,000 ton/year is put into the environment by natural sources like weathering of rocks and soils, dust, and volcanic activity (Kieber et al., 2002; Shahid et al., 2017). The metal can be present in several oxidation states but only Cr(III) and Cr(VI) are stable under environment conditions (Shahid et al., 2017; Shanker et al., 2005). Both Cr(III) and Cr(VI) species are common (Kloprogge, 2020; Liu, Hystad, et al., 2017), and occur in more than 70 minerals. A typical Cr(VI)-mineral is crocoite (PbCrO4), occurring in oxidized lead deposits (Liu, Hystad, et al., 2017; Liu, Xiao, et al., 2017), whilst the main Cr(III)- mineral is chromite (FeCr2O4), belonging to the spinels group (Adriano, 2001; Shahid et al., 2017). Other minerals containing Cr(III) are garnets, tourmaline, pyroxenes, olivines, amphiboles, and serpentine minerals (Apollaro et al., 2018; Babula et al., 2008; Bloise et al., 2016; Liu, Hystad, et al., 2017; Liu, Xiao, et al., 2017; Quantin et al., 2008). Naturally occurring Cr is commonly associated with ultramafic rocks because of the Cr-bearing minerals typical of these environments (Bloise et al., 2019; Chrysochoou et al., 2016; Oze et al., 2007). The estimated amount of Cr in the Earth’s crust ranges from 80 to 350 mg/kg (Adriano, 2001; Kloprogge, 2020; Liu, Hystad, et al., 2017; Yaroshevsky, 2006). The Cr content in ultramafic rocks can be .3000 mg/kg, slightly lower content is found in mafic rocks, whereas in acid rocks such as granites, Cr content may be less than 50 mg/kg (Adriano, 2001; Alloway, 2012; Chrysochoou et al., 2016; Kabata-Pendias, 2010). Weathering processes are the main cause of Cr-enrichment in natural soils (Alloway, 2012). Estimations regarding Cr concentration in soils range from 10 to 300 mg/kg in soils worldwide (Adriano, 2001; Kabata-Pendias, 2010; Zayed & Terry, 2003). Nevertheless, soils developed from ultramafic or serpentine rocks show higher Cr concentration of above 100,000 mg/kg. Redox potential and pH are the main factors controlling geochemical behavior (sorption/desorption processes and chemical speciation) of Cr in the environment. In soil media, Cr(VI) species predominate in oxygen-rich environments. However, Cr(VI) species are unstable in the soil environment, remaining mobilized in both acidic and alkaline soils, whereas anoxic conditions and pH values .5.5 cause its reduction and immobilization as Cr(III) (Kabata-Pendias, 2010). Other factors controlling the fate of Cr

142 Chapter 5 speciation in soils are the presence of other components such as hydrous metal oxides, natural organic matter, and microorganisms (Maqbool et al., 2015; Pantsar-Kallio et al., 2001). In aqueous solution, both Cr(III) and Cr(VI) species occur with Cr(III) prevailing under reducing conditions, while Cr(VI) prevails under oxidizing conditions. The latter exists as different species at different pH values: within the normal pH range of natural waters (pH 6
8), chromate (CrO422), hydrogen chromate (HCrO42), and dichromate (Cr2O722) are prevalent, while chromic acid (H2CrO4) occurs under more acidic conditions (Barrera-Dı´az et al., 2012; Rakhunde et al., 2012). In several ophiolite aquifers worldwide, it has been noted that the total dissolved Cr is present mainly or entirely in its hexavalent state (Ball & Izbicki, 2004; Dermatas et al., 2015; Fantoni et al., 2002; Kazakis et al., 2015; Megremi, 2010). The oxidation of Cr(III) contained in the minerals and its release as Cr(VI) into groundwater needs a strong oxidant. As reported by several authors, Mn oxides seem to be the only suitable oxidant in these natural systems. While several oxidation experiments have been performed considering Mn oxides as the oxidant (Dai et al., 2009; Kim et al., 2002; Landrot et al., 2012; Oze et al., 2007; Tang et al., 2014), this generally accepted hypothesis was recently questioned by Apollaro et al. (Apollaro, Buccianti, et al., 2019; Apollaro, Fuoco, et al., 2019). Indeed, based on geochemical modeling, the authors argue that in ophiolite areas, Cr oxidation could be driven by trivalent Fe in serpentine minerals (Apollaro, Buccianti, et al., 2019; Apollaro, Fuoco, et al., 2019; Fuoco et al., 2020). The world mean value of Cr in seawaters is estimated to be 0.3 µg/L, whereas in freshwaters the mean level is 1 µg/L (Adriano, 2001). Although background levels of Cr in groundwaters depend on local conditions of individual areas, geogenic Cr in groundwater usually does not exceed concentrations of 90 µg/L total Cr or 70 µg/L Cr(VI) (Chrysochoou et al., 2016).

5.1.5 Mercury Mercury is a metal considered as one of the 10 primary chemicals of concern (Wang et al., 2020). It is issued into the environment through human activities such as the burning of fossil fuels, and natural sources, including degassing from Hg-bearing phases and from aquatic and terrestrial systems (the process is characterized by the reduction of Hg21 to Hg0), geological activity (geothermal and volcanic processes), biomass burning (e.g., fires of forests), biological activities (e.g., plant growth), and erosion of Hg-bearing minerals (Gworek et al., 2016, 2020; Kallithrakas-Kontos & Foteinis, 2015; Varde` et al., 2019). The total global Hg emissions from natural processes and sources to the atmosphere range from 4600 to 6000 ton/year with the primary (geogenic) inputs of only 80 2 600 ton/year (Driscoll et al., 2013; Gu et al., 2019; Gworek et al., 2016; Liu et al., 2011; Pirrone et al., 2010).

Potentially toxic elements (As, Cd, Cr, Hg, and Pb), their provenance and removal 143 In nature, Hg is typically found as the sulfide minerals cinnabar (a-HgS), metacinnabar (b-HgS), or both (polymorphs of HgS). Less important sources are livingstonite (HgSb4S8), corderoite (Hg3S2Cl2), and 35 other Hg-containing minerals. Small amounts of Hg can also occur in deposits with other metals or in different type of rocks including coal deposits and limestone (Gu et al., 2019; Rahman & Singh, 2019; Risher & DeWoskin, 1999). The average Hg content of the Earth’s crust is 0.0675 6 0.0175 mg/kg (Adriano, 2001; Kloprogge, 2020; Rahman & Singh, 2019; Yaroshevsky, 2006). As reported by Adriano (2001) and references therein, Hg content of most igneous rocks is generally ,200 µg/kg (range 5
250 µg/kg). Except for shales high in organic matter where concentrations can be up to 3250 µg/kg, most sedimentary rocks also have Hg content of ,200 µg/kg (limestone and sandstone with average concentrations of 40 and 55 µg/kg and ranges of 40
220 and 10
300 µg/kg, respectively). Once introduced into soils, Hg(II) quickly forms inorganic mercuric salts and minerals (e.g., HgCl2, HgO, or HgS), or, organo-Hg compounds under favorable conditions (Windmo¨ller et al., 2015). High soil pH facilitates the binding of Hg to Fe-Mn oxides (O’Connor et al., 2019), whereas under acidic conditions Hg(II) release is favored (Coufalı´k et al., 2012). In soil, the Hg background concentration ranges from 30 to 100 µg/kg, with a mean value of 60 µg/kg (Adriano, 2001; Gworek et al., 2020). In proximity of ore deposits (gold, molybdenum, and base-metal), soils may contain Hg concentration from 50 to 250 µg/kg, and in some instances as much as 2000 µg/kg. In the presence of Hg deposits, soil levels of Hg can be considerably higher (range of 1000
10,000 µg/kg) and in some cases in the region of 100,000 µg/kg (Adriano, 2001; Windmo¨ller et al., 2015). Mercury has three oxidation states: 0 (elemental mercury), 11 (mercurous mercury), and 12 (mercuric mercury). Mercuric Hg(II) is the main oxidation state found in natural soils and aquatic environments, whereas gaseous Hg(0) primarily exists in the atmosphere. Free Hg21 ions do not usually exist in natural water but form complexes with organic and inorganic ions or ligands, such as hydroxide (OH2), chloride (Cl2), sulfide (S22) anions, and DOM, because of their strong binding affinities (Gu et al., 2019; Gworek et al., 2016; O’Connor et al., 2019). The mobility, solubility, and toxicity of different Hg forms decrease as follows: organo-Hg, inorganic Hg(II), and Hg(0) (Rahman & Singh, 2019; Sysalova´ et al., 2017). In water, Hg shows many forms which depend on the redox conditions. Airborne Hg(0) is oxidized to mercuric Hg [Hg(II)] that is deposited in the ocean and on land, ultimately making its way into lakes, rivers, streams, and wetlands. The forms HgCl422 and HgOH2 prevail in oxidized conditions, sulfur-related forms (HgS22 and CH3HgS2) are dominant in reducing conditions, whereas HgS dominates in aquatic sediments (insoluble form) (Gworek et al., 2016; Rahman & Singh, 2019). In the intermediate conditions inorganic Hg can be converted into organic forms such as methyl mercury (MeHg) compounds and ethyl

144 Chapter 5 mercury (EtHg) compounds, the most toxic forms of mercury, by sulfate- or iron-reducing bacteria. Specifically, when Hg reaches surface waters it is usually oxidized to Hg12, which is either methylated by sulfate-reducing bacteria or, less frequently, reduced to elemental mercury, a process called demethylation, via biotic and abiotic (photochemical) pathways and then returns to the atmosphere via volatilization. MeHg1 is a very stable ion and when found in water it is quickly adsorbed by phytoplankton and/or transferred to biota, where it bioaccumulates, through several physical and biological processes (Kallithrakas-Kontos & Foteinis, 2015). High concentration of Cl2 ions leads to increased dissolution of Hg solid phases and allows the formation of stable complexes with mercury, such as HgCl32, HgCl22, HgCl422, or HgBrCl2, (Grassi & Netti, 2000). The total dissolved Hg concentration in lakes or terrestrial aquatic systems ranges from 0.1 to 10 ng/L (Varde` et al., 2019), whereas in the open ocean concentrations range from 0.1 to 0.5 ng/L (Gu et al., 2019).

5.1.6 Lead Among the potentially toxic elements in the Earth’s crust, Pb is the most abundant. Concerning worldwide Pb releases, Nagajyoti et al. (2010) provide a summary of historical surveys of annual emission: wind-blown dusts and volcanic eruptions cause annual emission of 10 and 6.4 kg  106 respectively. Less important are the contributions of forest wildfires, vegetation, and sea salt of 0.5, 1.6, and 0.1 kg  106, respectively. In nature, Pb commonly occurs as a mineral with sulfur or oxygen and rarely is found in its metallic form. Although there are more than 200 Pb-bearing minerals, only a few, such as galena (PbS), anglesite (PbSO4), and cerussite (PbCO3), are common (Abadin et al., 2007; Tabelin et al., 2018). The physical
chemical alteration of galena-rich ore deposits favors the release of Pb to the surrounding surface water and groundwater and causes the formation of a wide variety of secondary Pb-bearing minerals, such as anglesite [PbSO4] (in acidic environments), cerussite [PbCO3] (in alkaline environments), pyromorphite [Pb5(PO4)3Cl], hydrocerussite [Pb3(CO3)2(OH)2], and plumbojarosite [PbFe6(SO4)4(OH)12] (Abadin et al., 2007). The oxidative alteration of primary sulfide minerals and the subsequent interactions with carbonate and aluminosilicate favor the formation of these secondary minerals. Commonly, Pb minerals are found in association with copper, iron, and zinc sulfides, as well as silver, gold, bismuth, and antimony minerals. The solubility of secondary phases (log Ksp of
27.5,
7.7,
12.8,
84.4,
17.5, and
12.6), for galena, anglesite, cerussite, pyromorphite, hydrocerussite, and plumbojarosite (Bao et al., 2021) is generally pH-dependent, as pH varies through time in response to the stability of secondary minerals, acid neutralization, and changing rates of sulfide oxidation. High Pb concentrations are found in areas with hydrothermally altered rocks (Tabelin et al., 2018). Typical Pb concentrations in some ores are 11,000 mg/kg in copper ores, 24,000 mg/kg in

Potentially toxic elements (As, Cd, Cr, Hg, and Pb), their provenance and removal 145 Pb and zinc ores, 6.60 mg/kg in gold ores, 3
111 mg/kg in bituminous coal, while 20 mg/kg is a typical concentration in wood (Abadin et al., 2007). The average amount of Pb in the Earth’s crust is 16.5 6 3.5 mg/kg (Adriano, 2001; Goyer, 2001a; Heinrichs et al., 1980; Kloprogge, 2020). As reported by Adriano, 2001 and references therein, Pb concentration in rocks is variable with mean values of 15 mg/kg (range 2
30 mg/kg) in igneous rocks, 9 mg/kg in limestones, 7 mg/kg (range ,1
31 mg/kg) in sandstones, 20 mg/kg (range 6
50 mg/kg) in shales, up to 150 mg/kg in black shales, 9 mg/kg in carbonates, and 16 mg/kg (up to 60 mg/kg) in coal. These data are consistent with those provided by other authors (e.g., Turekian et al., 1961; Wedepohl, 1995). In topsoils the Pb concentration varies widely due to the geological background and the accumulation of atmospheric particulates derived from anthropogenic and natural processes. The approximate range for background Pb concentrations in uncontaminated topsoils worldwide is 12
85 mg/kg (Alloway, 2012 and references therein). In general, Pb exhibits very low mobility in the environment at pH between 4 and 8, despite relatively high Pb concentration, because of two mechanisms (Tabelin et al., 2018): (1) Pb21 precipitation as carbonate such as hydrocerussite (Pb3[CO3]2[OH]2) and cerussite (PbCO3); and (2) Pb21 sorption to clay minerals and Fe(III)-oxyhydroxides. Pb-bearing phases, represented by carbonates, are the less soluble of the Pb compounds, therefore precipitation of these minerals could sequester dissolved Pb from solution at pH 6
8 with a sufficient supply of HCO32 (Abadin et al., 2007; Tabelin et al., 2018). Where HCO32 concentration was very low, considerable Pb contamination (up to 100 µg/L of dissolved Pb) was observed in marshes with pH value around 6.3, while streams and lakes, characterized by higher HCO32 concentration and pH, showed lower dissolved Pb due to its precipitation as Pb-carbonate minerals. The immobilization of Pb21 is further enhanced for the presence of carbonate minerals like calcite and aragonite in soils and sediments. This condition allows the formation of a disordered PbCO3 phase on the minerals surfaces that recrystallizes into hydrocerussite and cerussite (Godelitsas et al., 2003; O’Day et al., 1998). Sorption of Pb21 to Fe(III)-oxyhydroxides, formed from the oxidation of pyrites, and to clay minerals such as illite and smectite, formed during the phyllic/sericitic-type or argillictype alteration of the rocks (Pirajno, 2009), contributes significantly to the low Pb mobility between pH 4 and 8 in rocks rich in Pb. The Pb concentration in solution is limited by the presence of sulfate ions in water that favor the formation of PbSO4. The mobility of Pb is limited due to Pb21 as PbSO4 precipitation even under strongly acidic conditions (Tatsuhara et al., 2012). At low pH, metal species bound to hydroxides, carbonates, and other soil components enhance their solubility into solution, increasing rates of Pb migration through the soil. Pb leaching was found to increase at low pH both for the greater solubility of Pb-carbonates

146 Chapter 5 and Fe(III)-oxyhydroxides and the competitive effects of hydrogen ions that limit Pb adsorption to clay minerals (Tabelin et al., 2018). Tabelin and Igarashi (2009) noted that under alkaline conditions Pb leaching slightly increased but only in the presence of DO. Under these conditions, the higher release of Pb could be attributed to increased oxidation of Pb-containing pyrites and/or Pb-sulfides in hydrothermally altered rocks (Tabelin et al., 2012). Pb can exist in different oxidation states: (0) in elemental Pb and (12) or (14) in compounds. In the environment, Pb is mainly found in the (12) state in minerals and inorganic compounds. The chemical behavior of inorganic Pb compounds is like that of the alkaline earth metals. There are three common Pb-oxides: lead(II)oxide (PbO); lead tetroxide (Pb3O4) or lead(II, IV)oxide; and lead dioxide (PbO2) or lead(IV)oxide. The (14) state is only formed under strongly oxidizing conditions. Inorganic Pb(IV) compounds are relatively unstable and it is unlikely to find them in ordinary environmental conditions (Abadin et al., 2007). In organic lead compounds, Pb is commonly present in its tetravalent (14) oxidation state (Carr et al., 2004; Haynes, 2014). The Pb concentration and mobility in aqueous environments is generally controlled by the formation and dissolution of secondary precipitates and is driven largely by the surrounding bedrock geochemistry (Abadin et al., 2007; Bao et al., 2021; Rahman & Singh, 2019) Pb concentrations are generally low in natural springs and groundwater ranging from undetected to 100 µg/L (US EPA, 2013). A United States Geological Survey study of groundwater in the United States (2000
2016) found that Pb concentrations .15 µg/L were detected in ,1% of samples investigated. These anomalies were commonly associated with geographic areas where the Pb solubility potentials (the quantity of Pb that could dissolve) were naturally high (Jurgens et al., 2019). Pb levels in seawater are typically in the range of 0.050
0.30 µg/L in coastal waters, influenced by anthropogenic activity, and about 0.001
0.036 µg/L in the open ocean (Angel et al., 2016). Equilibrium calculations show that at pH .5.4, the total solubility of Pb is approximately 30 µg/L in hard water2 and approximately 500 µg/L in soft water2 (Abadin et al., 2007; Bao et al., 2021; Rahman & Singh, 2019).

5.2 Toxicity of As, Cd, Cr, Hg, and Pb In 2010, the General Assembly of the United Nations (UN) stated that the access to clean and safe drinking water is a human right (WHO, 2017). Although most drinking water contamination is of microbiological origin, several problems can result from chemical contamination, which, in contrast to microbial health effects, is more often associated with 2

Hardness is expressed as mg of CaCO3 per liter of water. Hard water .120 mg of CaCO3 per liter; soft water ,80 mg of CaCO3 per liter.

Potentially toxic elements (As, Cd, Cr, Hg, and Pb), their provenance and removal 147 health concerns that arise after prolonged periods of exposure. Among such chemicals, potentially toxic elements, when present in excessive quantities, are associated with widespread adverse long-term human health effects. Once inside the human body, potentially toxic elements are eliminated with great difficulty and over time, they can accumulate causing physiological structural damage with severe acute, chronic, or long-term effects (Engwa et al., 2019; Hong et al., 2020; Moura et al., 2012). Transported and compartmentalized into cells and tissues, potentially toxic elements can injure blood constituents, cause lung, liver, kidney, and other vital organ damage, disrupt the endocrine and reproductive system, provoking mutations that can lead to cancer, and eventually, alter the central nervous system (CNS) producing muscular, physical, and neurological degenerative disorders simulating diseases such as Alzheimer’s and Parkinson’s disease (Engwa et al., 2019; Hong et al., 2020; Monisha et al., 2014; Moura et al., 2012; Valko et al., 2005). The availability of information on health effects that exposure to potentially toxic elements may have in human population studies is severely limited by ethical barriers associated with human toxicological studies and a lack of quantitative information on background concentrations of exposure. For this reason, the most frequently used source of information is toxicological studies on laboratory animals. However, these are often limited by the use of a relatively small number of in vivo experiments and the use of high dosages, leaving doubts about the reliability of these results for human health. Thus, in most cases, the guideline value for each element is supported by a series of multiple studies, including human data (WHO, 2017).

5.2.1 Arsenic Arsenic biochemistry resembles that of other elements of the same group such as phosphorus (P) and nitrogen (N) and its toxic effects are strictly influenced by its solubility and oxidation state (Centeno et al., 2005). As in drinking water is classified by the International Agency for Research on Cancer (IARC) in Group 1, as a (known) carcinogen to humans for bladder, lung, and skin cancers (IARC, 2012). Similarly, the US Environmental Protection Agency (US EPA) categorizes arsenic in class A (known carcinogen) environmental toxicant (US EPA, 1990). Most epidemiological evidence points to over 140 million people in Argentina, Bangladesh, Chile, India, Taiwan, Vietnam, and different areas of the United States chronically exposed to water contaminated with arsenic at concentrations of .1000 µg/L, significantly greater than the World Health Organization guideline value (Almberga et al., 2017; D’Ippoliti et al., 2015; Hasanuzzaman et al., 2018; WHO, 2017). In humans, As in drinking water is mainly absorbed through the gastrointestinal tract and then, conjugated to hemoglobin, reaches various organs within a few hours. It is mainly accumulated in tissues containing a high concentration of thiol groups (e.g., hair, nails, skin). Absorbed As can enter cells directly or be transformed from

148 Chapter 5 the pentavalent to the trivalent form and undergo alkylation by methyltransferase enzymes (Engstro¨m et al., 2015; Tchounwou & Centeno, 2008). Inorganic As is considered the most toxic form of this element, especially in its trivalent state which is evaluated as up to 2
10 times more toxic than pentavalent As(V) (Goyer, 2001b). Although both organic and inorganic As are rapidly eliminated from the human body, and the more toxic inorganic As has a whole-body half-life of only 4
5 days (Moura et al., 2012), through binding to thiol groups or replacing phosphate groups it can inactivate over 200 enzymes causing adverse effects on different organs in chronic long-term exposures (Bozack et al., 2018). Consequently, As in drinking water was classified by both the WHO and the IARC as a human carcinogen causing skin, lung, liver (angiosarcoma), and bladder cancer, while there is less evidence of its association with other types of cancer (ATSDR, 2009; D’Ippoliti et al., 2015; Engwa et al., 2019; IARC, 2012; WHO, 2010). Long-term exposure to high concentrations of arsenic is also related to damage to numerous organ systems including cardiovascular, gastrointestinal, hematological, respiratory, dermal, immune, endocrine, and reproductive systems along with peripheral and nervous system (ATSDR, 2009; IARC, 2012). Both general and peripheral nervous systems can be affected by the oxidative stress caused by mitochondrial damage associated with increasing cellular levels of As, also associated with structural and functional damage to the cardiovascular system (Baker et al., 2018; Chen et al., 2016). Hypotheses regarding the mechanism by which As induces carcinogenesis showing positive evidence in in vitro (animal and human cells) experiments as well as in human tissues that are associated with chromosomal abnormalities, oxidative stress and altered growth factors (Nurchi et al., 2020). Furthermore, As and its metabolites readily cross the placental barrier with resultant As levels of 50 µg/L or greater that are associated with increased risk of neonatal and infant mortality (ATSDR, 2009; IARC, 2012; WHO, 2010). More recently, lower As levels (10 µg/L) have been related with preterm birth and very low birth weight, raising concerns that the current regulatory standards insufficiently protect against adverse effects of prenatal exposure to As (Hasanuzzaman et al., 2018).

5.2.2 Cadmium Cadmium is considered an extremely dangerous chemical for humans and animals (Bernard, 2008; Tchounwou et al., 2012). Once absorbed, Cd accumulates in soft tissues, mostly kidney and liver, and is efficiently retained in the human body having a long half-life lasting up to 35 years (Genchi et al., 2020; WHO, 2017). The IARC has classified cadmium and its compounds in Group 1 (Carcinogenic to humans) (Genchi et al., 2020; IARC, 1997) meanwhile in the European Union’s Restriction of Hazardous Substances Directive, Cd is one of the six substances banned because of its classification as a carcinogen (Stewart & Wild, 2014). In humans, exposure to Cd can severely damage various organs and systems such as the nervous, reproductive, adrenal, hematopoietic systems, gastrointestinal tract, and

Potentially toxic elements (As, Cd, Cr, Hg, and Pb), their provenance and removal 149 mucous tissue, and can cause osteoporosis, coronary heart disease, fetal malfunction, kidney damage and many others (Genchi et al., 2020; Kumar et al., 2019; Omeljaniuk et al., 2018). Many of the negative effects on human health are associated with the oxidative stress that Cd induces through the inactivation of the sulfhydryl groups of the enzymes involved in the antioxidant mechanisms [e.g., SOD, CAT, glutathione (GSH)]. Oxidative stress together with the induction of inflammatory processes and damage to DNA through mutagenesis and effects on the cell cycle are the major Cd-induced carcinogenic mechanisms (Genchi et al., 2020; Kumar et al., 2019). Numerous epidemiological and clinical studies have highlighted the association between Cd contained in the blood and breast cancer (Nagata et al., 2013; Peng et al., 2015) and nasopharyngeal carcinomas. Furthermore, recent epidemiological data connect exposure to this toxic metal in the environment to cancers of the urinary bladder, pancreas, prostate, and kidney (Genchi et al., 2020). Moreover, some neurodegenerative disorders such as Parkinson’s and Alzheimer’s diseases, multiple sclerosis, and amyotrophic lateral sclerosis were related to Cd-dependent neurotoxicity (Genchi et al., 2020; Kumar et al., 2019). The most severe type of chronic Cd-poisoning, associated with exposure to contaminated river water, is referred to as itai-itai disease (meaning “it hurts, it hurts”) and first appeared in Japan in the early 1990s. Itai-itai disease is pathogenetically referred to as renal tubular dysfunction resulting from exposure to environmental Cd (Aoshima, 2019) and new cases of itai-itai disease continue to be identified in different areas of the world.

5.2.3 Chromium Chromium is extensively disseminated in the environment and can exist in seven oxidation states, mainly trivalent and hexavalent states. The hexavalent form is the most toxic species of Cr while Cr(III) is about a thousand times less toxic and causes few or no health problems (Des Marias & Costa, 2019; Tchounwou & Centeno, 2008; WHO, 2017). The main mechanisms by which Cr(VI) induces significant cellular damages are through raising of oxidative stress, breaking of chromosomes, and formation of DNA adducts (Costa & Ortiz, 2020; Des Marias & Costa, 2019). IARC has classified Cr(VI) in Group 1 (carcinogenic to humans) and Cr(III) in Group 3 (not classifiable as carcinogenic in humans). Hexavalent Cr is largely present in the environment as chromate oxyanion (CrO4)22 that, closely resembling phosphate and sulfate anions, can be transported into cells and distributed in all tissues through the same mechanisms (Costa & Ortiz, 2020; Des Marias & Costa, 2019). While trivalent chromium is scarcely absorbed by any path, Cr(VI), absorbed by the gastrointestinal tract or lungs, can easily cross the cell membrane and undergo intracellular reduction to reactive intermediates by ascorbate and biological thiols resulting in oxidative stress and reactions with DNA and protein (Costa & Ortiz, 2020; Des Marias & Costa, 2019; WHO, 2017). In vivo and in vitro experiments have shown that chromate compounds can damage DNA in multiple ways by producing chromosomal

150 Chapter 5 aberrations, alterations in sister chromatid exchanges of DNA replication, and transcription (Costa & Ortiz, 2020; Des Marias & Costa, 2019). There is substantial evidence that Cr can promote carcinogenicity in humans as increased stomach tumors have been reported in animals and humans exposed to hexavalent chromium in drinking water (Engwa et al., 2019). Several retrospective epidemiological studies, aimed at evaluating the potential development of cancer in humans through environmental exposure, have not shown any correlation with oral exposure to total Cr or Cr(VI) (WHO, 2017), despite the IARC classifying compounds of Cr(VI) as human carcinogenic compounds (Group 1) by inhalation based on sufficient evidence in both humans (lung cancer) and experimental animals. These contradictory results, associated with the different routes of exposure, can be partly explained by the reduced oral Cr(VI) absorption capacity of the oral gastrointestinal tract (WHO, 2017).

5.2.4 Mercury When ingested orally, elemental Hg is poorly absorbed and therefore causes little toxicity (Tariq, 2019). However, Hg can be converted to MeHg by the action of microorganisms (by phytoplankton in the ocean and in the aqueous environment), primarily by sulfate-reducing bacteria (Carocci et al., 2014), thus gaining access to the food chain, and resulting in human exposure through ingesting of contaminated predatory fish (i.e., king mackerel, swordfish, and shark), shellfish, and sea mammals (Tariq, 2019; Tchounwou et al., 2012). MeHg is purged from the body in the inorganic form mainly by the action of the biliary tract at the rate (1% of the body load per day). Much of the body burden of Hg resides in the proximal convoluted renal tubule (Bernhoft, 2012) bound to metallothionein. Accumulation also occurs periportally in the liver with smaller quantities in testes, choroidal plexus, and epithelial tissues (Bernhoft, 2012). The sites of greatest accumulation of MeHg are the brain, liver, kidneys, placenta, and fetus, particularly in the fetal brain and peripheral nerves and bone marrow (Bernhoft, 2012). The deposited MeHg undergoes a slow demethylation to inorganic Hg so that its half-life in humans is about 70 days (Bernhoft, 2012). Intracellularly, it reacts with the sulfhydryl groups of intracellular molecules (tubulin, ion channels, enzymes, GSH, and transporters) inhibiting the actions of these molecules and interfering with regular cellular functions (Carocci et al., 2014; Rice et al., 2014). Damage to mitochondria, due to GSH depletion, appears to be the most significant mechanism by which Hg causes toxicity and results in changes in calcium homeostasis and improved lipid peroxidation (Carocci et al., 2014; Rice et al., 2014). The CNS is the main target of prolonged exposure to highly lipophilic short-chain alkylmercury compounds which is associated with the so-called “Hunter-Russell syndrome,” also known as “Minamata disease.” This disease is a form of intoxication first recorded in 1956 in the coastal area of Minamata Bay (Japan), caused from exposure to highly toxic MeHg formed from the

Potentially toxic elements (As, Cd, Cr, Hg, and Pb), their provenance and removal 151 bacterial methylation of inorganic Hg in industrial wastewater (Drasch et al., 2004; Tchounwou et al., 2012). Analogous cases recorded in Iraq, Pakistan, and again Japan in the period 1956
72 have highlighted that the effects of MeHg intoxication are determined not only by its maximum concentration but also by the time of CNS exposure to toxic concentration, that, in the most serious cases, can cause irreversible effects due to the damage of neuronal cells (Drasch et al., 2004). Once the two mainly absorbed species, Hg0 and MeHg, enter the blood, they rapidly cross cell membranes, such as the blood
brain barrier and the placental barrier, bioaccumulating and causing negative impacts on human health (Rice et al., 2014). Numerous epidemiological data sets have associated increased Hg levels with infertility in both men and women (Rice et al., 2014). In males, Hg can have negative effects on spermatogenesis and testicular weight (Rice et al., 2014). In women, Hg has been shown to inhibit hamper the release of follicle-stimulating hormone and luteinizing hormone by altering estrogen and progesterone levels provoking painful, ovarian dysfunction, or irregular menstruation, early menopause, and uterus rollover (Rice et al., 2014). Exposure to elevated levels of organic, inorganic, and metallic Hg can harm the growing fetus (Engwa et al., 2019) and, through breast milk, can damage the developing baby’s pulmonary, central, and nephrotic nervous systems (Carocci et al., 2014; Engwa et al., 2019). Even exposure to low Hg levels (25
100 nM) can disrupt neuronal excitability interacting with N-methyl-D-aspartate receptors and induce neuronal deterioration (Xu et al., 2012). In pregnant women Hg can affect the fetus and offspring can suffer from cerebellar symptoms, retention of primitive reflexes, mental retardation, malformations, and other abnormalities (Carocci et al., 2014; Engwa et al., 2019). Exposure to Hg has also been associated with Kawasaki disease (Carocci et al., 2014) which results from immune system impairment and whose symptoms include photophobia, fever, skin rashes, pharyngitis, tachycardia, and oral lesions, among others (Carocci et al., 2014). Circumstantial data suggests a potential pathogenic role for inorganic Hg in provoking Alzheimer’s disease (Carocci et al., 2014) and syndromes comparable to those reported in amyotrophic lateral sclerosis (ALS), including extremity weakness, spasticity, tremor, fasciculation, hyperreflexia, and ataxia (Carocci et al., 2014). Nevertheless, a cause-and-effect association between exposure to MeHg and ALS has not been specifically determined. Accumulation of Hg in the heart has been correlated to dilated cardiomyopathies. In fact, levels of Hg in the heart tissue of persons who died from this disease were found to be on average 22,000 times higher than those of persons who died from other types of heart disease (Rice et al., 2014). In vitro studies have shown that MeHg may hamper the cardioprotective activity of paraoxonase 1 (Rice et al., 2014). High levels of Hg in the body are also associated with anemia, including hemolytic anemia and aplastic anemia, probably because Hg competes with iron for binding to hemoglobin (Rice et al., 2014). Supplementary data have also suggested that Hg may be a causative reason of mononucleosis and involved in leukemia and Hodgkin’s disease (Rice et al., 2014). Some evidence also suggests a relationship between Hg exposure and kidney damages, glomerulonephritis, chronic renal diseases, acute tubular necrosis, renal cancer, and nephrotic syndrome (Rice et al., 2014). Low levels of Hg exposure

152 Chapter 5 can affect the endocrine system by disrupting the thyroid, pituitary, adrenal glands, and pancreas (Rice et al., 2014), thus affecting several hormones such as insulin, estrogen, testosterone, and adrenaline (Rice et al., 2014).

5.2.5 Lead Lead from natural sources is rarely present in tap water. More often its presence is due to the deterioration of old plumbing systems. Absorbed Pb is mostly stored in the liver and partially in the kidneys, whereas the residual Pb is distributed throughout the body (brain, pancreas, spleen, prostate, ovary, testes, spinal cord, cerebral cortex, adrenals, heart, skeletal muscles, and fat tissue) (WHO, 2017). Pb in bones is estimated to have a biological halflife of 1 year, but Pb can persist 10
20 years in cortical bone. Elimination of Pb from the human body occurs in two steps: purging from soft tissues and from blood in nearly 20
30 days; then gradual elimination from the bones; consequently, Pb can persist in the body for decades (Charkiewicz & Backstrand, 2020; Omeljaniuk et al., 2018). The accumulation of Pb in blood, bones, and, to some extent, in kidneys, liver, brain, and skin has been demonstrated to affect the function of the hepatic, reproductive, immune, endocrine, and gastrointestinal systems (Krzywy et al., 2010; Omeljaniuk et al., 2018). Furthermore, Pb exposure has been associated with cancer, albeit through partial evidence of a carcinogenic effect of lead and its inorganic compounds on humans (Krzywy et al., 2010; Wani et al., 2015), including the reported relationship between brain cancers and work-related exposure in various countries (Australia, Finland, Russia, Sweden, and the United States) (Ahn et al., 2020), and between concentrations of Pb in blood and some tumors (lung and brain) in Finland and the United Kingdom (Omeljaniuk et al., 2018; Steenland et al., 2019). Exposure to Pb can inhibit the activity of numerous enzymes by binding to the thiol groups of their amino acids or by modifying the transport of essential metal cations such as Ca (Nurchi et al., 2020) with consequent cell damage mediated by the formation of reactive oxygen species (Nurchi et al., 2020). This oxidative stress causes alterations in the composition of fatty acids in membranes participating in processes such as endocytosis and exocytosis, and processes of signal transduction and can also cause changes in gene expression (Charkiewicz & Backstrand, 2020). The brain is the most susceptible organ to Pb exposure since it can go through the endothelial cells at the blood
brain barrier interfering with synapse formation (Wani et al., 2015). In adults this can produce alterations in the nervous system including hand
eye coordination, decreased visual intelligence and memory, reduction in cognitive functioning, visual and auditory disorders, and psychiatric conditions such as anxiety and depression (Wani et al., 2015). More serious conditions, like permanent damage of CNS function, can occur with increased blood Pb levels (50
100 µg/dL) (Wani et al., 2015). Exposure to Pb also has an adverse impact on the male and female reproductive system. In males, impotence and endocrine disorders related to a reduction in the number of spermatozoa and their motility have been reported (Wani et al., 2015),

Potentially toxic elements (As, Cd, Cr, Hg, and Pb), their provenance and removal 153 whereas more severe problems have been reported for the female reproductive system including miscarriages, premature birth and low birth weight in babies, and developmental problems in childhood. Blood Pb levels in mothers and babies are generally comparable as Pb in maternal blood goes into the fetus via the placenta and breast milk (Wani et al., 2015). Consequently, numerous epidemiologic studies in children under 5 years of age have revealed that even low-level Pb exposure (5
25 µg/dL in blood) caused a diminishing of intellectual development that interferes with the capability to learn, impairs memory, lowers IQ, and interferes with development and growth (Charkiewicz & Backstrand, 2020; Engwa et al., 2019; Krzywy et al., 2010). In addition, blood Pb levels lower than 50 µg/L have been associated with a reduction in school performance in children, with a decrease in IQ of 2
4 points for each µg/L increase in blood lead levels (Charkiewicz & Backstrand, 2020; Wani et al., 2015; WHO, 2017). Finally, low-level environmental Pb exposure may increase renal insufficiency in patients who have chronic renal disease (Wani et al., 2015), whereas limited evidence has been reported for the relationship between prolonged Pb exposure and an increase in blood pressure and heart rate variability, coronary heart disease, and death from stroke (Wani et al., 2015).

5.2.6 Guidelines limit and health risk assessment approach of selected potentially toxic elements With the aim of assessing the quality of drinking waters and the potential health risk of PTEs to the population, several studies were conducted to investigate their levels in various water sources, i.e., surface water, spring water, and groundwater, including bottled water (Apollaro, Buccianti, et al., 2019; Apollaro, Fuoco, et al., 2019; Chabukdhara et al., 2017; Varde` et al., 2019). Concentrations of PTEs including As, Cd, Cr, Hg, and Pb were analyzed mainly by using ICP, AAS, and AFS instrumentations (Apollaro, Buccianti, et al., 2019; Apollaro, Fuoco, et al., 2019; Birke et al., 2010; Cicchella et al., 2010; Muhammad et al., 2011; Naddeo et al., 2008; Varde` et al., 2019). Average concentrations of trace elements determined in drinking samples were compared with maximum admissible concentrations (MACs) set by national limits and/or international guidelines, such as US EPA and WHO. The health risk assessment approach has been calculated by applying the chronic daily intake (DI)/average daily dose taken (ADD) or dose taken (DT), and the hazard quotient (HQ) and, when considered, the carcinogenic risk (CR). Dose has been calculated using a general Eq. (5.1) as reported by previous works (Muhammad et al., 2011; Varde` et al., 2019) as follows: DI HM 5

CHM  Dw Bw

(5.1)

154 Chapter 5 where DIHM represents the calculated DT from drinking water (µg/kg  d); CHM is the average concentration of heavy metal (µg/L); Dw represents the average volume of drinking water ingested every day (L/d); and Bw is the average body weight (kg). The estimated weekly intake is obtained by multiplying DI values by seven, and then compared with provisional tolerable weekly intake (PTWI). Using Eq. (5.2) the HQ has been calculated as follows: HQHM 5

DI HM RfD

(5.2)

where RfD is the reference dose for each PTE. The RfD for As, Cd, Cr, Pb, and Hg was established by US EPA at 3.0E 2 04, 5.0E 2 04, 1.5, 3.6E 2 02, and 3.00E-04 mg/kg d, respectively (US EPA, 2005). When exposed populations show HQ ,1 they are considered to be safe from adverse health effects. 5.2.6.1 Arsenic A large data set of As in groundwater samples collected in Pakistan was reported by Shahid et al. (2018), where average As concentration of 120 µg/L exceeded the WHO guideline value (WHO, 2011a) by more than 10 times. This work described spatial variability of As by analyzing .40 studies that included .9000 groundwater samples, covering an area populated by more than 47 million people and a high risk of As poisoning in drinking water. HQ and CR have been found at 14.7 and 0.0029 showing that these values were significantly higher than the threshold limit of 1 and 1026, respectively. Contamination by As in groundwaters observed in some regions of East Asia such as Bangladesh, China, and India causes elevated As exposure for hundreds of millions people. Recently, the health risk associated for As ingestion from different dietary sources (including drinking water) was calculated for infants and toddlers in the United States. Drinking water consumption was a significant source of inorganic As, accounting for 18% of the total for infants/toddlers in the range 4
24 months old (Shibata et al., 2016). Recently, Zuzolo et al. (2020) produced the first national health risk assessment on As in Italy by using potential carcinogenic and noncarcinogenic risks approach. Levels of As above WHO national and standard limits, with an associated risk of cancer (skin, lung, and bladder cancer) for different age groups (children, teenagers, and adults) of the population, were observed in approximately 80% of analyzed drinking waters. In some areas of the Italian peninsula characterized by complex geological features, the high concentrations of As (up to 27.20 µg/L), and the duration of exposure, were the main factors that led to the international and national reference values of 1 3 1025 (WHO, 2011a) and 1 3 1026 (D.L. 4, 2008), respectively being exceeded.

Potentially toxic elements (As, Cd, Cr, Hg, and Pb), their provenance and removal 155 However, D’Ippoliti et al. (2015) explained that drinking water with As concentration less than the EU limit can also result in a mortality risk. Therefore, with the aim to eliminate the health risk for As from drinkable waters a Maximum Contaminant Level Goal has been established at 0 µg/L by US EPA (US EPA, 2001). Although the EU MAC (Directive 98/83/EC, 1998) of 10 µg/L in potable water is widely respected in the Netherlands, Dutch drinking water companies set the goal of supplying water with a As concentration ,1 µg/L. This takes into account the effects on human health of chronic, low concentrations As exposure that are still uncertain and foresee an annual saving between h7.2 and h14 million on the health system from costs related to lung cancer cases attributable to the intake of As. 5.2.6.2 Cadmium Present in-group IIB of the periodic table, Cd is an element characterized mainly by an oxidation state 12, and, only in a few compounds, 11. Having no role in metabolic functions and being a nonessential metal, Cd is considered a toxic metal for humans. Its high toxicity causes adverse outcomes including high blood pressure, kidney damage, premature birth, and weight loss. The main route of involuntary Cd intake in the general population is primarily through food, and secondarily through drinking water and inhalation of ambient air. Adverse effects due to Cd intake have been recognized through occupational exposure studies where inhalation is the main route of intake for humans with cases recorded from accidental ingestion of dust in the workplace where Cd is used (IARC, 2012). Cadmium pollution of drinking waters observed in different countries across the world originates from both natural sources and man-made activities. It is attributable to erosion of natural deposits (as ores containing different elements), galvanized pipe corrosion, metal refinery discharge, runoff from waste batteries and paints, and agricultural activities. Chronic consumption of Cd via drinking water was evaluated in several studies worldwide by performing a health risk assessment approach (Avino et al., 2011; Jaishankar et al., 2014; Shah et al., 2012; Zhang et al., 2014). The highest level of Cd allowed in drinking water and bottled water is 5 µg/L, set by US EPA (US EPA, 2009), FDA (FDA, 2007), and Directive 98/83/EC relating to potable water quality, respectively, whilst WHO (2004) suggested a lower guideline value of 3 µg/L. Directive 2009/54/EC, on the exploitation and marketing of natural mineral waters, has set the maximum contaminant level of Cd in bottled waters at 3 µg/L. In a case study in Pakistan, Cd concentrations of up to 100 µg/L, significantly above the national and international threshold limit, were found in groundwaters, giving a high HQ value of 5.80. Man-made activities such as industrial and domestic discharge, leach from piping materials, and agriculture practices were the causes of high levels of Cd (Khan et al., 2015). Due to its long half-life (10
30 years), Cd pollution is an ongoing problem, especially in countries where rapid industrial growth

156 Chapter 5 (such as China) leads to greater attention to the effects on population health and carcinogenic and noncarcinogenic risks. The objective of stakeholders is therefore the control and prevention of Cd exposure in order to reduce the adverse effects of this toxic metal contamination in the environment on ecosystems and on humans (Wang et al., 2021). 5.2.6.3 Chromium The EU standard limit for the presence of total chromium, including Cr(VI), in drinking and bottled water in Europe has been set at 50 µg/L (Directive 98/83/EC; Directive, 2003/ 40/EC). This limit value is in agreement with US EPA (US EPA, 1990) and WHO (WHO, 2004) guidelines. Despite the US EPA decision to modify the Cr limit to 100 µg/L (US EPA, 2021), in 2014 the California Department of Public Health established a MCL at 50 µg/L for Cr(tot) and 10 µg/L for Cr(VI). New high-quality data for the evaluation of carcinogenic and noncarcinogenic effects from Cr(III) and Cr(VI) in drinking water carried out by the US National Toxicology Program has allowed to confirm the guideline value at 50 µg/L as adequately valid as a protective limit for the health of the exposed population (NTP, 2008a, 2008b). The assessment from WHO based on current knowledge of water treatment technologies, toxicology, and analytical methods of measurement and speciation of Cr, resulted in no modification to the current guide value which was considered to be an effective limit. In Italy, from June 2021 the adoption of the provisional limit for Cr(VI) at 10 µg/L entered into force as a precaution for the risk assessment of the presence of Cr(tot) in drinking water. The control of Cr(VI) concentration is applied when the concentration of Cr(tot) in the water exceeds 10 µg/L (D.M. 14/11, 2016). In a case study in a region of Iran, high Cr concentrations in drinking water were reported. Levels between 2.01 and 116 µg/L, and HQ with values up to 1.16 and 1.93 for children and adults, respectively, were determined in water samples. The average concentration of Cr in .40% of water samples resulted in a noncarcinogenic risk with HQ .1 for children, higher than adults, and in general, a CR .106 for the exposed population in over 90% of samples (Farokhneshat et al., 2016). 5.2.6.4 Mercury Drinking and bottled water guideline values and legal limits for Hg set by national and international institutions or organizations vary. Specifically, the EU, US FDA and EPA, and WHO have established maximum concentration values for Hg in drinking water and bottled natural water at 1, 2, and 6 µg/L, respectively (Directive 98/83/EC; Directive, 2003/40/EC; FDA, 1995, WHO, 2005). In recent years, investigations of inorganic Hg in drinking water have been carried out on a national and regional scale. In the most recent studies conducted on a European, national and regional scale, respectively, concentrations of Hg were found at ultratrace levels (Apollaro, Buccianti, et al., 2019; Apollaro, Fuoco, et al., 2019; Birke et al., 2010; Cicchella et al., 2010; Naddeo et al., 2008; Varde` et al., 2019). In addition to

Potentially toxic elements (As, Cd, Cr, Hg, and Pb), their provenance and removal 157 assessing the concentration level and spatial variability, these studies allowed the calculation of DT, HQ, and PTWI on three different groups of population, establishing that there were no health risks for the exposed population from drinking water of the areas analyzed (Varde` et al., 2019). It is mandatory to continue the monitoring of Hg levels in drinking water since cases of Hg contamination in groundwaters have been reported even recently. In the Treviso area, Veneto region (Italy), Hg concentrations over 10 µg/L have been determined, for which the environmental protection agency is continuing to verify the presence of Hg in the investigated wells (ARPAV, 2020). The case studies of drinking water pollution such as those reported for Cr, Pb, and Hg, demonstrate a high risk of adverse effects for the group population that is most sensitive to toxic metals and/or substances. Thus it is mandatory to continuously monitor the quality of drinking waters, including monitoring the status of the water distribution network by the drinking water companies. 5.2.6.5 Lead In Europe, the limit value for Pb in both drinking and bottled waters is 10 µg/L (Directive, 2003/40/EC; Directive 98/83/EC). A threshold limit of 10 µg/L has been implemented in 2010 by the Joint FAO/WHO Expert Committee on Food Additives, replacing the PTWI of 25 µg/kg of body weight since it is not possible to establish a new PTWI considered adequate for the protection of health. Although the use of lead additives in gasoline has decreased since the 1970s, it is probable to find Pb in soil, sediments, and water bodies due to the extensive use that was made in the past or in incorrect management of the drinking water system as recently observed in the United States (Frank et al., 2019; Hanna-Attisha et al., 2016; Ritter et al., 2002).

5.3 Metal removal from water As mentioned in the previous sections, the occurrence of heavy metals in the environment, either from natural or anthropogenic sources, can affect and does affect the health of millions of people around the world. As such, a lot of effort has been put into developing materials and methods for removing toxic elements from the global drinking water supply. One of the main anthropogenic sources of metals to the aquatic environment are municipal wastewaters (Hargreaves et al., 2018). They effectively sum the emissions from a wide array of domestic and industrial sources, from household piping to industrial emissions (So¨rme & Lagerkvist, 2002), and contain Cr, Cu, Hg, Ni, Pb, and Zn, all of which can have negative effects on environmental and human health, as detailed earlier in this chapter. The Italian Health Ministry (Ministero della Salute, 2016) reports that gray waters that are relatively uncontaminated with Hg can be successfully treated in municipal wastewater treatment works using coagulation, sedimentation, and filtration followed by polyaluminum

158 Chapter 5 chloride (PAC) treatment and ion exchange processing to reduce levels below 1.0 µg/L. They report that Cu is more difficult to remove, and Ni levels are easily controlled by these processes. However, Cr, particularly as the hexavalent form Cr(VI), requires a chemical reduction to Cr(III), followed by precipitation and filtration for complete removal. They also note that reverse osmosis (RO) membranes and ultrananofiltration methods now exist. The treatment of groundwater for the removal of toxic elements has been reviewed (Da’ana et al., 2021) with the authors listing a large array of potential low-cost methods for this application. However, it is unclear how many of these are in use. They do point out that the treatment cost depends on the quality of the source groundwater. Local usage of chemicals like fertilizers and pesticides, along with overextraction of groundwater can degrade the groundwater quality, making the treatment of run-off and wastewater important if we are to protect drinking water supplies.

5.3.1 Metal removal in municipal wastewater treatment works Municipal wastewater treatment plants are not specifically designed to remove potentially toxic elements (Cantinho et al., 2016), and any metal removal that occurs is mainly due to metals partitioning into the solid phases in the water treatment processes. This results in metal enriched sludges that need to be properly disposed. In the primary sedimentation tanks of treatment works, metals removal is highly dependent on the chemical form of the element. In other words, it is important to know whether the element is present in a soluble or an insoluble form (Hargreaves et al., 2018) or whether it is bound to dissolved organic material. Removal and reduction in the amount of total suspended solids in the sedimentation tank (Inna et al., 2014a) can result in a sizeable reduction in Cu and other ˇ cancar et al., 2000) are highly mobile, elemental concentrations, but elements such as Ni (Sˇ and thus are not easily removed with the suspended particles. A confounding factor is that many elements bind to ligands within the dissolved organic carbon (DOC) in the soluble fraction of treated water (Ziolko et al., 2011), meaning that they remain in solution and do not settle out in the primary treatment stage. Further removal can be achieved in the biological treatment stage by biological reaction and phase separation (Hargreaves et al., 2018). Although primarily designed to remove organic contaminants, it can remove some soluble metals from wastewater along with suspended particles. Extracellular polymeric substances generated in the biological process act as binding sites for metals (Liu et al., 2001) and have been found to remove from between 99% of Zn to 26% of Cr in waters containing up to 100 mg/L of the elements investigated. However, it is reported that the most promising methods for elemental removal from waters are flocculation/coagulation and sorbent removal (Ida & Eva, 2021) by enhancing elemental removal during settling processes such as those outlined above. In their review, Ida and Eva

Potentially toxic elements (As, Cd, Cr, Hg, and Pb), their provenance and removal 159 (2021) report that sorption technologies may be most effective for Cu and Ni removal, whereas coagulation may be most effective for Cd, Cr, Cu, Hg, Pb, and Zn removal. Coagulation is achieved through the addition of chemical reagents to the water that required treatment (Hargreaves et al., 2018). Ferric chloride (FeCl3) PAC, and synthetic polymers such as polyacrylamide are typically used. The elements are removed in a process similar to coprecipitation in analytical chemistry. Particles and elements are removed by settling as a hydroxide precipitate after a stirring and agglomeration step. These methods can all be further optimized for the removal of trace elemental contaminants from ground- or wastewaters, and this will be the focus of the rest of this section.

5.3.2 Enhanced elemental removal processes 5.3.2.1 Electrocoagulation One improved method for removing elemental contamination is electrocoagulation (Bazrafshan et al., 2015). It is often used to treat wastewater from domestic, industrial, and agricultural effluents and has been shown to be able to remove soluble ionic species and heavy metals from wastewaters with reduced sludge production. As mentioned above, in traditional coagulation/flocculation, FeSO4 or Al2(SO4)3 or their chloride salts are added as coagulants with NaOH to promote precipitation, and the impurities are removed by sedimentation. These chemical additives may also contain impurities further complicating the removal process. Instead, in electrocoagulation, the coagulant agents are added in situ by effectively electrochemically dissolving sacrificial Al or Fe electrodes (Mollah et al., 2004). The resulting flocculants have a much higher surface area compared to preprecipitated hydroxides (Khandegar & Saroha, 2013) so they capture more impurities and are more easily removed by filtration. 5.3.2.2 Membranes Membrane technologies are widely employed in wastewater treatment plants (Castro-Mun˜oz et al., 2021), particularly for ultrafiltration, nanofiltration and RO. However, there is still much work to be done to improve their use on industrial scales (Kehrein et al., 2020) so that they can efficiently recover water as a resource from treatment works. Most of the membranes used are polymeric in nature and can be functionalized for various applications (Castro-Mun˜oz et al., 2021) such as seawater desalination, or treatment of agro-food, mine, petroleum stream, or textile wastewaters. 5.3.2.3 Biological treatment of contaminated waters To overcome some of the disadvantages of physiochemical removal techniques (sludge production, high operational costs, and difficulty in treating large volumes with low concentrations), many attempts have been made to use biological processes to remove

160 Chapter 5 potentially toxic elements or detoxify metalloid species (Kikuchi & Tanaka, 2012). These have concentrated on the use of biomass as an adsorbent (biosorption), biological organisms as active elemental accumulators (bioaccumulation), biological mediation of redox processes, the use of biologically derived material as a precipitation agent (bioprecipitation), and the use of plants to sequester elements in their biomass (phytoremediation).

5.3.3 Case studies Many of the case studies listed below are intended for As removal. There are an enormous number of methods published for As removal from waters. This is because, as mentioned earlier in this chapter, As is a toxic element, with soluble species in several oxidation states that can be easily transported in aqueous matrices (Mudhoo et al., 2011). Since arsenic was discovered in 1250, its use has been responsible for many accidental as well as deliberate poisonings. With surface water sources becoming scarce in many parts of the globe, the use of groundwater, often contaminated with As, is leading to increased population exposure (Basu et al., 2014, Litter et al., 2019). In Bangladesh and particularly in the Ganges Delta area, the problem is becoming extremely severe (Garelick et al., 2005), with over 36 million people at risk, mostly in poor communities without centralized water supplies. This has driven the large scientific effort in its removal. 5.3.3.1 Coagulation methods An example of the use of coagulation for the simultaneous removal of As, Fe, and Mn from groundwater has been reported (Bora et al., 2018), using NaHCO3 as a pH conditioner, KMnO4 as an oxidant and FeCl3 as the coagulant. Levels of As were reduced to ,1 µg/L and Fe and Mn were reduced to ,0.03 and 0.009 mg/L, respectively. The authors did this by adjusting the dose of the FeCl3 required based on the initial quantity of Fe in the groundwater, aiming for a total 8.6 mg/L of Fe in total. Half of the dose of NaHCO3 was added before water treatment to bring the pH to 8.5, after addition of the KMnO4 and FeCl3 solutions, the pH of the solution was then adjusted to 7.3 with the remaining NaHCO3 solution. In this reaction scheme, the KMnO4 oxidizes the Fe21 ions present to Fe31 which then form hydroxide coagulates following the reaction: 1 3Fe21 1 MnO2 4 1 7H2 O-3FeðOHÞ3 1 MnO2 1 5H

The Mn ions form insoluble MnO2 and are removed by precipitation: Mn21 1 KMnO4 -2MnO2 1 K1 The KMnO4 is also used to oxidize the As31 to As51 which is more easily removed from the solution by the FeOOH ion floc that forms at pH 7.3 after the formation of Fe(OH)3 in solution. A synergistic effect was also noted, as As can also adsorb onto the MnO2

Potentially toxic elements (As, Cd, Cr, Hg, and Pb), their provenance and removal 161 precipitates formed in the reactions above. A field trial of this method reduced As in groundwater from an initial concentration of 91 µg/L to ,1 µg/L, Fe concentrations were reduced from 23 mg/L to ,0.03 mg/L, and Mn concentrations were reduced from 1.9 mg/L to ,0.009 mg/L despite the addition of Mn as a treatment ion. The authors further demonstrated that this method was effective for Cd, Co, Cr, Cu, Ni, and Pb removal from groundwaters (Bora & Dutta, 2019). After adding their reagent mix and leaving the waters for 4 h to coagulate, reduction of between 99.5% (Pb) to 79% (Cd) was reported, as the FeOOH, 5Fe2O3.9H2O, and MnO2 precipitates formed strongly adsorb the elements present together with the formation of oxyanion precipitates of Cd and Pb. A different approach to coagulation was taken by Pramanik et al. (2016) who used a combination of Al and biologically derived coagulants to remove As and Fe from drinking water. In this study, alum (Al2(SO4)318H2O) was used as the coagulant together with seeds from the Moringa oleifera tree ground into a fine powder and used to make a 1% m/v suspension in deionized water. A temperature of 22 C and Alum doses between 5
25 mg/L at a pH between 4 and 6 were used for water treatment. Removal of As and Fe by coagulation was best at an alum concentration of 25 mg/L and at pH 4, with a 92% reduction in As concentrations and a 78% reduction in Fe concentrations in the treated water. Coagulation methods were then compared with using biologically activated carbon (BAC) and biologically activated filters (BAF). These were prepared by dosing activated carbon with activated sludge and additional nutrients to encourage biofilm growth on the surface. After 35
40 days, these cartridges were able to remove DOC from water and were deemed ready for use. Used alone, after a 60-minute contact time with the water to be treated .85% of the Fe and As present was removed. When used in combination with alum at 5 mg/L and a pH of 6.96, followed by biological treatment with the BAC or BAF cartridges for 60 mins, 100% of the As and 96% of the Fe in the waters was removed. Alum was shown to be a superior flocculation agent compared to the tree seed powder, and when used in combination with BAF was able to reduce the As content of groundwaters (.1800 µg/L untreated concentration) to below the WHO allowable limit of 10 µg/L. Recently, the use of electrocoagulation for the removal of As (and fluoride) from waters has been reviewed (Sandoval et al., 2021). The authors report that the most common anode materials are Al or Fe as they easily form hydrolysis products in the form of hydroxide ions with the general formula M(OH)n after anodic electrodissolution. The removal of As from ground- or wastewater by electrocoagulation is expedited by the oxidation of As31 to As51 (Li et al., 2012), because between pH 4
10 As51 has a net negative change, whilst As31 has no net charge (Hansen et al., 2007), so once in the pentavalent form, As is more easily removed from solution by the following reaction from (Sandoval et al., 2021; Hansen et al., 2007) with Fe electrodes:    32 FeðOHÞ3 ðsÞ 1 AsO32 4 ðaqÞ- FeðOHÞ3 AsO4 ðsÞ

162 Chapter 5 And by a similar reaction with Al electrodes (Kobya et al., 2011):    32 AlðOHÞ3 1 AsO32 4 ðaqÞ- AlðOHÞ3 AsO4 ðsÞ By 2021, up to 13 reactor designs had been reported in the literature (Sandoval et al., 2021) working in batch or continuous flow modes. Generally, electrocoagulation has good removal efficiencies for As, with values of .90% routinely achieved by various methods. We invite the reader to directly consult the review by Sandoval et al. (2021) if interested in this technology, as much more specific information is present there. Electrocoagulation has also been investigated for the removal of hexavalent Cr from drinking water (Pan et al., 2016), driven by the proposed reduction in permissible levels in drinking water from 100 to 10 µg/L in the United States. Reduction of Cr(VI) to Cr(III) with Fe is well established and the reaction rate is dependent on pH as per the reaction: 21 CrO22 1 3H2 O 1 H1 2CrOH21 1 3FeðOHÞ1 4 1 3Fe 2

The Cr(III) then reacts with the Fe hydroxides produced to form a precipitate. 1 xCrOH21 1 ð1 2 xÞFeðOHÞ2 2 1 ð1 2 xÞH2 O2Crx Fe12x ðOHÞ3ðsÞ 1 ð1 1 xÞH

Although Fe(II) can be added by chemical addition, electrocoagulation has been used to produce Fe(II) in situ (Pan et al., 2016) using an iron anode. In an aerated reactor at pH 8, with a cell voltage of 4 V and a current of 37 mA across a solution of 460 µS/cm conductivity, Cr(VI) concentration was reduced from 500 µg/L to below the instrumental detection limit for Cr in ,6 mins. 5.3.3.2 Membranes Membranes for the removal of As and other elements from drinking water have been used for quite some time. Using RO membranes made of either polyamide (ES-10) or polyvinyl alcohol (NTR-729HF, Nitto Denko Corporation, Japan), Kang et al. (2000) found that pH control was extremely important for the removal efficiency of As(III) and was slightly less important for the As(V) oxidation state. The authors suppose this is because the membranes have a negative charge and the charge of the As species increases with pH. Specifically, trivalent As at a pH below 9 exists as the uncharged H3AsO3 ion, above this pH until pH 13.5 it exists as the H2AsO32 ion, whereas As(V) is a neutral ion (H3AsO4) below pH 2.26 and becomes the charged ion H2AsO42 up to pH 6.7. Above this, up to pH 11, it gains an extra charge as the HAsO422 ion and above pH 11 is takes the AsO432 form. Thus, negatively charged membranes reject As ions in high pH solutions. With these unmodified membranes, As(V) removal of .90% was possible above pH 5 but effective As(III) removal sharply increased from pH 7 to 10. Control of pH was found to be much less crucial for Sb removal, and near complete Sb(V) removal

Potentially toxic elements (As, Cd, Cr, Hg, and Pb), their provenance and removal 163 was achieved between pH 3 and 10, whilst Sb(III) removal became less effective above pH 7. To improve As removal, membrane micro- and nanofiltration with and without iron coagulation has been reported (Nguyen et al., 2009). Using the same nanofilter as mentioned above (NTR-729HF) As(V) removal efficiency of .80% and As(III) removal efficiency of between 54% and 59% were found as the transmembrane operating pressure increased from 85 to 500 kPa at pH6. The authors then tried the same experiment using inline addition of zero valent Fe, which is nanoscale (10
100 nm) Fe0 prepared from FeSO4.7H2O after reduction with NaBH4 (Ponder et al., 2000). This nanoscale Fe then oxidizes to Fe21, and depending on pH and redox conditions reacts to give Fe3O4, Fe(OH)2, and Fe(OH)3, which are adsorption surfaces for As(III) and As(V). Using a test solution containing 500 µg/L of either As(III) or As(V) with 0.3 g/L of zero valent Fe, the authors reported .90% removal of both As species after a contact time of 10 mins at a filtration pressure of 200 kPa, resulting in water with an As concentration of ,10 µg/L. Problems with filtration due to fouling of the membranes have been observed (Ahmad et al., 2020), therefore the use of ultrafiltration with waters with different turbidities has been tried (Moreira et al., 2020). These authors retrofitted a water treatment plant with a dead-end ultrafiltration unit to remove As, Fe, and Mn bound to the colloidal ,0.2 µm fraction after Fe coagulation. The large fractions were removed by settling and sand filtration, using ultrafiltration in dead-end mode since all the source water passes through the membrane, and higher volumes of water can be processed. In addition, operating in semicontinuous mode after a sand filter with intermittent backwashing reduced the possibility of membrane fouling. The trial was carried out using a commercially available submerged ultrafiltration module with a polyetherimide-based membrane and average pore diameter of 0.04 µm, with a filtration area of 0.047 m2 and a permeability of 431.6 L/m2/h1/bar1. The filtration unit was installed in a 2 L tank and was operated at 0.15 6 0.01 bar and 25 C 6 1 C. To reduce fouling the tank was continuously aerated and after tests the filters were cleaned by recirculating water and back flushing with distilled water. After coagulation and sand filtration, a significant reduction in As, Fe, and Mn in the different feed waters was possible. For the worstcase feed water containing 0.4 mg/L As, 50 mg/L Fe, and 3 mg/L Mn, As was reduced to around 8 µg/L, Fe concentrations were below 0.3 mg/L but Mn concentrations remained above the WHO limit of 0.1 mg/L. With ultrafiltration, the elemental concentrations were further reduced: in the highest turbidity water, the As concentration was reduced to 3 6 2 µg/L, Fe was reduced to 0.08 6 0.01 mg/L, and Mn was reduced to 0.13 mg/L. The authors conclude that the addition of an ultrafiltration unit allowed the production of water that met drinking water standards for residual ion concentrations, color, and turbidity.

164 Chapter 5 RO membranes have also been found to be highly effective in the removal of other elements, such as Cd and Cu (Qdais & Moussa, 2004). Using polyamide spiral wound nanofiltration and RO membranes to treat an artificial wastewater containing 500 mg/L of Cd and Cu, a reduction in the target ion concentrations of .98% was achieved resulting in a reduction in Cu concentrations to 3.5 6 1.7 mg/L and Cd concentration to 1.7 6 0.1 mg/L in the produced permeate water when operated at an applied pressure of 13 bar. To improve the selectivity of RO towards elemental cations (Ujang & Anderson, 1996) ethylenediaminetetraacetic acid (EDTA) was added to the feed water. To obtain a baseline reading, a 500 mg/L sodium solution was passed through the membrane at 414 KPa, 25 C and a water recovery of 40%. Under these conditions, sodium rejection (removal from the water) was .95%. Under the same conditions the removal of Cu and Zn was found to be 93%
96%. This rose to nearly 99% for Zn and 98% for Cu when the molar ratio of EDTA in the feed water was increased to 2 moles of EDTA per mole of Cu or Zn at pH 3
5 at an operating pressure of .600 KPa. An advance on this methodology is the use of polymer-enhanced ultrafiltration (Huang et al., 2016), using polyvinylamine (PVam) or other water-soluble polymers as the complexing agent. In this process, the target elements coordinate with water-soluble polymers, forming macromolecules much larger that the molecular weight cut-off (MWCO) of ultrafiltration membranes. In this way the elements are retained together with the coordinating polymer, removing the undesired elements from the water stream. In order to be efficient, these polymers need to be sufficiently water soluble, have many chelating sites, and have a molecular weight above the MWCO of the filtering membrane. In some cases, the solubility can be altered under specific conditions, so they effectively become metalfree coagulants/flocculants. (Huang et al., 2016), tested the capacity of PVam as a reagent for the removal of Cd(II), Co(II), Cu(II), Fe(III), Mn(II), Ni(II), Pb(II), and Zn(II), from wastewaters. using a polyethersulfone membrane with a MWCO of 10 kDa in a dead-end ultrafiltration cell with a feed volume of 300 mL and a membrane area of 36 cm2. All experiments were carried out at ambient temperature (23 C) with a transmembrane pressure of 200 kPa. With the addition of 0.1% w/v of PVam to the water being treated, nearly complete removal of Cu, Fe, and Pb was observed, whilst only 60% of Ni was removed and ,40% of the other metals, showing that elemental removal was very dependent on the coordination efficiency of PVam with the target elements. This situation dramatically improved for all elements except Co when the PVam concentration was raised to 1% m/v, with almost complete removal of the target elements, but this concentration of polymer compromised the flow rate of the membrane. Consequently, at high elemental concentrations the authors suggest using the polymer as a flocculant, as it precipitated from solution in the presence of high elemental concentrations (e.g., at Cu concentrations .200 mg/L), whereas at lower concentrations the polymer worked best in polymerenhanced ultrafiltration mode.

Potentially toxic elements (As, Cd, Cr, Hg, and Pb), their provenance and removal 165 Many other potential technologies exist for the removal of potentially toxic elements from wastewater such as membrane adsorption (Khulbe & Matsuura, 2018), use of nanostructured materials (Tolkou et al., 2020), and surface filtration (Hoslett et al., 2018), as well as specifically technologies for certain elements such as Cr (Almeida et al., 2019) and Cd (Purkayastha et al., 2014), but none seem to be ready or actually implemented in current treatment works. Indeed, a recent review on the possibilities of using enhanced removal technologies (Ida & Eva, 2021) noted that low-cost adsorbents are promising methods for removing toxic elements during primary settling, and that they may be most effective for Cu and Ni whilst coagulation technologies seem most promising for Cd, Cr, Cu, Hg, Pb, and Zn removal.

5.3.4 Effectiveness of current treatment works The fate of elemental contaminants in current urban wastewater treatment plants has been studied using a Danish wastewater treatment plant (Yoshida et al., 2015). This plant treats 25.3 million m3 per year from 265,000 inhabitants, and about 85% of the water is from domestic users, with the rest from industry, which is mostly food processing and pharmaceutical plants. Analysis of the influent and effluent waters shows that only a few elements come out with reduced concentrations, specifically Ba, Cd, Cr, Cu, Pb, and Zn, the others remained virtually unchanged. Despite these results, significant partitioning of elements between the primary and secondary sludges was observed, with only a few elements found primarily in the effluent water (Ca, Cl, K, Mg, and Na). This underlines the importance of industry-specific treatment works for reducing elemental loads in wastewaters. Another important point, which is shared by another study of a UK treatments works (Inna et al., 2014b) is that return points for water inside the treatment works contain significant quantities of elements, such as Cu, and should be targeted as potential sites for coagulation plants to improve their performance. Trends in the removal of metals from industrial wastewaters have been reviewed (Barakat, 2011). It is noted that the industries that produce the most metal-containing wastes are electroplating, printed circuit board manufacture, wood processing, and petroleum refining. All of these generate toxic wastewaters, residues, and sludge that must be treated to meet maximum contaminant levels before release into the environment. Electroplating wastewaters are commonly treated by electrocoagulation (Favero et al., 2021; Fu et al., 2021; Prasetyaningrum et al., 2021) or by use of biologically derived adsorbents (Rahman et al., 2021). It has been estimated that approximately 75% of electroplating facilities use some sort of hydroxide precipitation (Purkayastha et al., 2014) to treat the wastewaters before discharge. This technology can reduce the Cd load in the wastewaters by 98%
100%.

166 Chapter 5 One final method for the removal of heavy metals and other elements from effluent waters from wastewater treatment plants before discharge to the environment are constructed wetlands (Vymazal et al., 2010). The authors note that municipal waste in the Czech Republic is increasingly being treated by horizontal subsurface flow through constructed wetlands. Trace elements are not normally contaminants, but their accumulation within the sediments of the filtration beds could become of concern and require excavation and removal. The mobility of trace elements in wetlands are determined by the redox potential and pH, but in constructed wetlands and the inflow effluent, the pH is typically neutral so it has little influence, meaning that the redox potential takes prime importance. Under aerobic conditions metals accumulate by sedimentation with the precipitation of Fe/Mn hydrous oxides, through a combination of precipitation and coprecipitation events as Al, Fe, and Mn for a variety of insoluble oxides, oxyhydroxides, and hydroxides. This combination of compounds is able to immobilize Cd, Cu, Ni, and Zn in the sediments. Under anoxic reducing conditions, sulfate reduction to H2S results in the precipitation of insoluble metal sulfides by the reaction: M21 1 H2 S-MSk 1 2H1 where M21 represents a divalent ion of Cd, Cu, Fe, Ni, Pb, or Zn. The authors of this study tested the effectiveness of seven flow-through constructed wetlands by analyzing the elemental concentrations in the sediments or filter beds. The samples came from beds with an age of between 2 and 16 years. They found that the elemental concentrations in the sediments of these artificial wetlands were quite low and were similar to lightly polluted natural wetlands. In other words, concentrations were much lower than those found in constructed wetlands used for the treatment of mine drainage or industrial wastewaters. They found that the concentrations in the sediment did not reflect the operational time, instead the amount of accumulated sediment was more indicative of the age of the wetland. This means that the amount of an element trapped in the wetland over time increased with the increased sediment mass without producing a toxic waste product. They noted that elemental concentrations in the sediment occasionally exceed the limits for agricultural soils, but in general the constructed wetlands seem to work properly. Constructed wetlands are not just used for the treatment of municipal wastewaters, they have also been used extensively for the treatment of acid mine drainage at active and abandoned mines (Pat-Espadas et al., 2018). In a review, these authors have reported that constructed wetlands have been used for many years to reduce the impact of these highly contaminated waters. They are currently the most widely used passive remediation system for four main reasons, which are: •

Aerobic wetlands are a tried and tested technology for treating net alkaline mine waters (with Fe as the main pollutant).

Potentially toxic elements (As, Cd, Cr, Hg, and Pb), their provenance and removal 167 • • •

They are relatively low cost compared to active systems and require minimal maintenance once in operation. They can cope with large fluctuations in wastewater volumes. Once properly landscaped, they are aesthetically pleasing.

These constructed wetlands rely on many synergistic interactions between all the different components to successfully remove or immobilize elemental contaminants. The interactions between plants and microorganisms are important for metal removal, as are the eventual addition of leaf litter and the growth of biofilms. Plants are a key component, since they can directly uptake/accumulate the metals and detoxify them, as well as promoting adsorption and precipitation mechanisms that can be assisted by the addition of bacteria and a well-chosen support. Metal removal also occurs in the soil and substrate as detailed in the previous study and this is determined by the support added to the wetland at the start. Mineral supports in constructed wetlands include limestone, dolomitic limestone, gravel, coarse gravel, sand, sandy soil, and bentonite. To this, organic support materials such as peat, manure, or charcoal can be added, as the overall aim is to reduce the bioavailability of the contaminants by interactions with this support, such as ion exchange or precipitation adsorption. This means that constructed wetlands have a limited life span (around 20 years) (PatEspadas et al., 2018) and that the residues can build up and become contaminated to where they can be classified as hazardous waste (Swash & Monhemius, 2005).

5.4 Conclusions and future trends As noted above, PTEs have many natural and anthropogenic sources from which they can enter ground and surface reservoirs that are used for drinking water extraction. These elements can have negative effects on human health, therefore it is essential that drinking water is protected. Drinking water can be protected by ensuring that wastewater does not come into contact with sources used for drinking water extraction. Although this is well regulated in many countries, such legislation is absent or not implemented in many parts of the world. The next line of defense is the cleanup of wastewater to prevent groundwater contamination. The last line of defense is the treatment of raw drinking water to remove toxic elements. This is particularly necessary where PTEs are naturally present in groundwater. Current treatment technologies are not designed for the specific removal of PTEs and may become less effective as the number of elements discharged increase, especially those used in modern consumer technologies (smartphones, computers) that do not even have any discharge limits.

168 Chapter 5 To combat these problems, more specific materials are required to remove PTEs whilst leaving the essential element content intact. Modified membranes and solid phase resins can play a large role in the future in improving the quality of drinking water around the world.

List of acronyms AAS AFS ATSDR BAC BAF Bw CHM CNS CR DIHM DO DOC DOM DT Dw EDTA EPSs FAO GSH HQHM ICP MAC MCL MWCO PTEs PTB PTWI PVam RfD US EPA VLPW WHO

Atomic Absorption Spectrometry Atomic Fluorescence Spectrometry Agency for Toxic Substances and Disease Registry Biologically Activated Carbon Biologically Activated Filters Body Weight Concentration Heavy Metal Central Nervous System Carcinogenic Risk Daily Intake Heavy Metal Dissolved Oxygen Dissolved Organic Carbon Dissolved Organic Matter Dose Taken Dose Water Ethylenediaminetetraacetic Acid Extracellular polymeric substances Food and Agriculture Organization Glutathione Hazard Quotient Heavy Metal Inductively Coupled Plasma Maximum Admissible Concentration Maximum Contaminant Level Molecular Weight Cut-Off Potentially Toxic Elements Preterm Birth Provisional Tolerable Weekly Intake Polyvinylamine Reference Dose United States Environmental Protection Agency Very Low Birth Weight World Health Organization

List of symbols Bw CHM DIHM DT Dw HQHM RfD

Body Weight Concentration Heavy Metal Daily Intake Heavy Metal Dose Taken Dose Water Hazard Quotient Heavy Metal Reference Dose

Potentially toxic elements (As, Cd, Cr, Hg, and Pb), their provenance and removal 169

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CHAPTER 6

Some organic compounds in potable water: the PFASs, EDCs and PPCPs issue Luisa Patrolecco1, Jasmin Rauseo1, Nicoletta Ademollo1, Stefano Polesello2, Massimiliano Varde`3,4, Sarah Pizzini3,4 and Francesca Spataro1 1

Institute of Polar Sciences (ISP), National Research Council of Italy (CNR), Rome, Italy, 2Water Research Institute (IRSA), National Research Council of Italy (CNR), Brugherio, Italy, 3Institute of Polar Sciences (ISP), National Research Council of Italy (CNR), Venice, Italy, 4Department of Environmental Sciences, Informatics and Statistics (DAIS), Ca’ Foscari University of Venice (UniVE), Venice, Italy

6.1 Introduction Water is becoming one of the biggest problems for the future and is the cause of strong international disputes, so much so that it can be considered the black gold of tomorrow. Climate change and the increase in temperature are causing the loss of water so that some areas of the planet are characterized by a scarce availability of this resource (Candela et al., 2012; Tielbo¨rger et al., 2010; Wheeler et al., 2013). Moreover, anthropogenic activities (domestic, industrial, agricultural, livestock, hospitals) can threaten natural aquatic environments, altering them chemically and biologically (Ha¨der et al., 2020). The evolving use of land for urban and industrial purposes is expected to cause a growth in the urban population; in particular, it has been estimated that about 60% of the global population will live in urban areas by 2030 (Lo´pez-Doval et al., 2017). These changes can dangerously impact water ecosystems and watersheds, often used as freshwater reservoirs near urban areas, in terms of multiple stressors, including mixtures of organic contaminants, which can reach aquatic systems by surface run-off, sewage discharges, outflows from wastewater treatment plants (WWTPs), industrial emissions, and wet and dry depositions of atmospheric pollutants (Lo´pez-Doval et al., 2017). Indeed, several studies published over recent decades report an increasing number of natural and synthetic organic contaminants in aquatic environments (Ha¨der et al., 2020; Jiang et al., 2014; Lapworth et al., 2012; Pal et al., 2010; Peng et al., 2018; Pic & Lorenzo, 2018). They are commonly found in surface and groundwaters and include both conventional and emerging contaminants (ECs), especially personal care products (PCPs), combustion products, plasticizers, pesticides, endocrine disruptors, drugs, and antibiotics (Leung et al., 2013; Machado et al., 2016; Current Trends and Future Developments on (Bio-) Membranes. DOI: https://doi.org/10.1016/B978-0-12-824103-5.00001-2 © 2023 Elsevier Inc. All rights reserved.

183

184 Chapter 6 Patrolecco et al., 2015; Sodre´ et al., 2010; Spataro et al., 2019; Velicu & Suri, 2009). Among ECs, endocrine disrupting compounds (EDCs) and pharmaceuticals and personal care products (PPCPs) are widely found in treated wastewater, drinking water, groundwater, soil, and sludge (Brausch & Rand, 2011; Loos et al., 2013; Luo et al., 2014; Yang et al., 2017). EDCs include over 800 chemicals that are used in the formulations of a variety of industrial products such as pesticides, plastic bottles, toys, metal food containers, and detergents (Campos et al., 2019). Surface and groundwaters are the major renewable resources for the production of drinking water throughout the world (Zwiener, 2007) and maintaining their good quality is crucial both for the protection of human and environment health, and because of the important economic and political implications that would arise as a consequence of a limited availability of these resources. In regions where there is a scarce availability of water or there are densely populated urban areas, an attractive solution to meet water requirements is the indirect reuse of potable water (Jones et al., 2005; Zwiener, 2007). However, many organic micropollutants, which are not effectively eliminated by wastewater and drinking water treatment plants (Blum et al., 2018; Caracciolo et al., 2019; Ikehata et al., 2008; Patrolecco et al., 2015; Spataro et al., 2019) can cause the contamination of raw water resources and water supplies. Speculating a worst-case scenario, drinking water could be regarded as the most direct way of human exposure to residual concentrations of several organic contaminants (Jones et al., 2005; Zwiener, 2007). This chapter aims to provide an overview of the current state of knowledge about the occurrence of some classes of organic micropollutants in water resources, focusing on PPCPs, EDCs, and per- and poly-fluoroalkyl substances (PFASs), most of which are defined as ECs. Starting from the current international directives on surface and drinking water protection, the chapter deals with the problems caused by the main sources of organic pollutants, their distribution in the aquatic environment, and their occurrence in potable waters, by critically reviewing the effectiveness of removal during drinking water treatments. The environmental and toxicological risk implications are also considered, since research on the potentially harmful effects of organic contaminants on ecosystems, including biota and humans, is still an important challenge to achieve a correct protection and management of water resources.

6.2 International directives on surface and drinking waters The efforts of European and other international authorities to develop and apply appropriate policies aimed at guaranteeing and maintaining drinking and surface water quality take the form of legislation, together with accurate and sensitive analytical methods, which are in continuous evolution, especially due to evidence about the occurrence and harmful effects of “new” contaminants in water sources.

Some organic compounds in potable water: the PFASs, EDCs and PPCPs issue 185 The European Drinking Water Directive (98/83/EC, Council of the European Unionion, 1998) set standards for 48 parameters, among which are 26 chemicals selected for their potential impact on human health, including trace elements like heavy metals (As, Cr, Ni, Pb) and organic substances like polycyclic aromatic hydrocarbons (PAHs), pesticides, chlorinated solvents (tetra- and tri-chloroethylene, 1,2-dichloroethane), and trihalomethanes or disinfection by-products. The EU Water Framework Directive (WFD, 2000/60/EC, European Parliament & Council and E., 2000) of November 2001 identified 33 priority substances, among which were PAHs, metals, and phenolic compounds, to be monitored in surface and groundwaters, representing a significant risk to or via the aquatic environment. Environmental quality standards (EQSs), expressed as the annual average concentration in surface water, have been proposed for priority substances to provide a benchmark for achieving the good surface water chemical status that EU member states are required to respect. The EQSs for these 33 substances were subsequently established (Directive 2008/105/EC, European Commission, 2008), and then the number of priority substances was increased to 45 (Directive 2013/39/EU, 2013). Alkylphenols (APs) and their derivatives are also listed in the WFD (2000/60/EC, European Parliament & Council and E., 2000). The EQS for nonylphenol (NP) and octylphenol (OP) were set at 0.3 and 0.1 μg/L, respectively (David et al., 2009). The US Environmental Protection Agency (US EPA) developed chronic criterion recommendations for NP: 6.6 μg/L in freshwater and 1.7 μg/L in saltwater (Brooke et al., 2005). Currently, no EU guideline values exist for alkylphenols ethoxylates (APEs) in drinking water. However, tolerable daily intake (TDI) values exist for bisphenol A (BPA), NPs ethoxylates (NPnEOs), and NP, namely 50 μg/kg (Knutsen et al., 2018), 13, and 5 μg/kg body weight per day, respectively (Nielsen et al., 2000). In 2006, restrictions on the use of perfluorooctane sulfonate (PFOS) were laid down by Directive 2006/122/EC of the European Parliament. PFOS, perfluorooctanoic acid (PFOA), and other related compounds were initially added to the restricted substances list in annex XVII of REACH (Registration, Evaluation, Authorization, and Restriction of Chemicals) regulation (EU, 2017/1000, European Union, 2017). These substances are of very high concern because of their carcinogenic, mutagenic, or toxic for reproduction and PBT (persistent, bioaccumulative, and toxic) properties and in 2009, PFOS, its salts, and perfluorooctanesulfonyl fluoride, were listed in annex B of the Stockholm Convention (SC, 2018). PFOA, perfluorohexane sulfonic acid (PFHxS), and their related compounds are also under consideration for addition to the Stockholm Convention (SC, 2018). The EQSPFOS is 0.65 ng/L for freshwater and 9.1 ng/g for biota (Directive 2013/39/EC). Since drinking water intake is shown to be an important source of human perfluoroalkyl acid (PFAA) exposure, guidelines for safe PFAA levels in drinking water have been published in various

186 Chapter 6 countries: 90 ng/L is the limit set for the sum of PFASs by the Swedish National Food Agency (Livsmedelsverket, 2017); the Italian National Health Institute has established maximum levels for PFAS in drinking water: PFOS # 30 ng/L, PFOA # 500 ng/L, and other PFASs # 500 ng/L; while the US EPA has proposed a provisional threshold of 0.4 g/L for the sum of PFOA and PFOS in drinking water (Environmental protection Agency USA, 2009). The EFSA has established a preliminary tolerable weekly intake of 4.4 ng/kg body weight per week for the sum of 4 PFASs: PFOA, PFNA (perfluorononanoic acid), PFHxS, and PFOS (Knutsen et al., 2018). Shorter chain (,C7) homologs are currently being tested and used as substitutes for PFOS and PFOA in industrial processes (Valsecchi et al., 2017), but the available toxicological and ecotoxicological data are currently not sufficient for deriving EQSs. In 2020, the authorities of five EU countries agreed to prepare a joint REACH restriction proposal to limit the risks to the environment and human health from the manufacture and use of a wide range of PFASs (https://echa.europa.eu/-/five-european-states-call-for-evidence-on-broad-pfas-restriction). The lack of monitoring data about occurrence, levels, and frequency of PPCPs in surface, ground, and drinking waters results in knowledge gaps for risk characterization, and environmental regulatory actions (https://www.wqa.org/Portals/0/Technical/Technical% 20Fact%20Sheets/2014_Ps-PCPs-EDCs.pdf). Although there are, currently, no threshold limits for PPCPs in drinking water and no regulatory requirement to monitor them at the European level, there has been much legislation about water monitoring over recent decades. In 2007, PPCPs such as diclofenac, iopamidol, musk fragrances, and carbamazepine were identified as future emerging priority candidates for monitoring under the EU WFD (2000/60/EC, European Parliament & Council and E., 2000). The European Commission (EC) Decision 2015/495/EU (The European Commission, 2015) led to the first Watch List of substances, including an antiinflammatory, EDCs, and macrolide antibiotics, to be checked in the field of water policy. It was then updated in 2018 (2018/840/EU, Commission, 2018), to include natural and synthetic estrogens, three macrolide antibiotics, amoxicillin, ciprofloxacin, and again in 2020 (2020/1161/EU, Commission Implementing Decision EU, 2020), when other antibiotics (sulfamethoxazole and trimethoprim) and pharmaceuticals (three azole compounds) were added to the list to be monitored. The US EPA has listed 12 PPCPs/EDCs in the Contaminant Candidate List 3 (CCL-3), which includes three pharmaceuticals and eight synthetic hormones among 97 chemicals or chemical groups (https:// www.epa.gov/ccl/). CCL-3 includes contaminants that are not currently subject to any proposed or promulgated national primary drinking water regulations, but can occur in public water systems or can require regulation under the Safe Drinking Water Act (SDWA). Unregulated Contaminant Monitoring Rule-3 (UCMR-3; https://www.epa.gov/dwucmr/third-unregulated-contaminantmonitoring-rule, 2012) required monitoring for 30 contaminants (28 chemicals and two viruses) between 2013 and 2015 and aimed at providing a basis for future regulatory actions to protect

Some organic compounds in potable water: the PFASs, EDCs and PPCPs issue 187 public health. In February 2015, the US EPA published the draft CCL-4, containing 100 chemicals (including compounds for sale publicly, pesticides, biological toxins, and PPCPs), that were proven or expected to occur in drinking water systems and thus to be considered for future regulation. UCMR-4 (https://www.epa.gov/dwucmr/fourth-unregulated-contaminantmonitoring-rule) was proposed in December 2016 and the monitoring of the contaminants in it is not yet concluded (2018 20). Moreover, in a recent study carried out by the EC and the World Health Organization (WHO) Regional Office for Europe under the “Drinking Water Parameter Cooperation Project,” many contaminants, including PPCPs, were considered but not recommended for inclusion in the related WHO Directive, since the data collected caused concern for health (WHO, 2017). Regarding PCPs, the data available are not enough to carry out a meaningful assessment of them in drinking water, but the information available from the literature does not suggest any urgent risk, although these contaminants remain an issue potentially requiring further investigation. PAHs and other persistent organic pollutants (POPs), such as polychlorinated biphenyls (PCBs), polychlorinated dibenzo-p-dioxins and furans (PCDD/Fs), have been included in EC Directives 98/83/EC and 2000/60/EC, respectively. In detail, among the PAHs of environmental interest, benzo(b)fluoranthene, benzo(k)fluoranthene, benzo(a)pyrene, benzo (g,h,i)perylene, and indeno(1,2,3-c,d)pyrene have been selected as markers for the control of PAH pollution, and limit values have been fixed both as a sum (0.1 μg/L) and as a single congener compound, where benzo(a)pyrene (0.01 μg/L) is considered as the PAH with the highest carcinogenic activity. In Italy, for instance, PAHs have been referred to throughout the legislation regarding water sources, from the transposition of the Directive 98/83/EC into the Legislative Decree No. 31/2001 (https://www.camera.it/parlam/leggi/deleghe/testi/ 01031dl.htm). In the Legislative Decree No. 152/2006, annex 5, part IV, table 2 (https:// www.camera.it/parlam/leggi/deleghe/06152dl.htm) threshold values for PAHs in groundwater have been set by including other compounds in addition to those of D.Lgs 31/ 2001 (i.e., dibenzo(a,h)anthracene, benzo(a)anthracene, chrysene, and pyrene, with limits at 0.01, 0.1, 5, and 50 μg/L, respectively), whilst the Legislative Decree No. 172/2015 (https:// www.gazzettaufficiale.it/eli/id/2015/10/27/15G00186/sg), which protects surface waters, mentions again the five PAHs previously considered in D.Lgs 31/2001. PCDD/Fs were included in Directive 2000/60/EC among the priority substances to be monitored in the environmental sector of potable water. In Italy, the transposition of Directive 2000/60/CE places a limit for these pollutants as regards surface water biota, while it did not set limits in water bodies. However, a limit was fixed in D.Lgs 152/2006 (https://www.camera.it/parlam/leggi/deleghe/06152dl.htm) relating to the quality of groundwaters, with limits for PCDD/Fs at 4 pg/L Toxic equivalent. Dioxin-like PCBs (dl-PCBs) are referred to in Directive 2000/60/EC as an aliquot to be considered in the calculation of the sum of PCDD/Fs. As regards the Italian legislation, they

188 Chapter 6 are referred to in D.Lgs 152/2006 (https://www.camera.it/parlam/leggi/deleghe/06152dl. htm), where their sum was set at 0.01 μg/L as a limit for groundwaters.

6.3 Sources, environmental dynamics, and final fate Over recent decades, the occurrence of organic micropollutants in aquatic ecosystems has become a worldwide issue of increasing environmental concern (Luo et al., 2014). Micropollutants include a wide array of anthropogenic and natural compounds, such as PPCPs, steroid hormones, industrial chemicals, pesticides, and several others, occurring in waters at concentration levels ranging from a few ng to μg/L. Since these contaminants occur simultaneously at low concentration levels, their detection, as well as the evaluation of their potential toxic effects on the environment, biota, and humans, are still important challenges. Fig. 6.1 shows a schematic representation of several sources of organic pollutants in the aquatic environment and highlights how they can reach drinking water reserves. In particular, the micropollutants considered can be divided into six categories, namely pharmaceuticals, PCPs, steroid hormones, surfactants, industrial chemicals and their byproducts, and pesticides. After the introduction into the environment of contaminant residues, their persistence depends on their intrinsic chemical and physical properties (i.e., Kow, Koc) and biotic (i.e., bacterial degradation) and abiotic (photolysis, thermal,

Households

Industries

Hospitals

Animal Farming

Direct discharge

Sewer

WWPTs

Biosolids

Aquaculture

Sepc tank

Soil

Landfills Surface water Groundwater

Drinking water

DWTs

Figure 6.1 Routes of drinking water contamination. DWTs, drinking water treatment plants; WWTPs, wastewater treatment plants.

Some organic compounds in potable water: the PFASs, EDCs and PPCPs issue 189 degradation) processes which can cause further structural transformations (Barra Caracciolo et al., 2018; Bu et al., 2013; Gurmessa et al., 2020; Ha¨der et al., 2020; Rauseo et al., 2019; Spataro et al., 2019). It is well known that WWTPs can be an important source for the release of conventional and emerging organic contaminants into the aquatic environment through their final effluents. The effectiveness of treatment technologies in EC removal is not fully understood (Wanda et al., 2017). Three main mechanisms control the abatement of most organic contaminants during wastewater treatment: volatilization, biodegradation, and sorption onto particulates. Nevertheless, there can be different mechanisms governing the different fates of the organic contaminants, thus making the identification of the dominant removal pathways crucial. The reported removal efficiencies widely varied depending on the operational parameters of the facility (e.g., hydraulic residence time, sludge age) and the seasonal fluctuations of the input loads, as well as the chemical properties of the target contaminants (Alvarino et al., 2018).

6.3.1 Pharmaceuticals Pharmaceuticals are usually composed of a mixture of medicinal ingredients (alone or combining small molecules with a range of molecular weights between 200 and 500 Da, and with different chemical and biological properties) specific to the treatment of diseases and several active substances, ranging from inorganic to organic, such as sugars, scents, pigments, and dyes, which are not harmful to the environment. Luo et al. (2014) reviewed the occurrence of micropollutants in the aquatic environment by collecting data from studies performed in several countries (Austria, China, EU-wide, France, Germany, Greece, Italy, Korea, Spain, Sweden, Switzerland, UK, US, and the Western Balkan Region) and showing that the main pharmaceutical therapeutic classes released into the aquatic environment are nonsteroidal antiinflammatory drugs (NSAIDs), lipid regulators, anticonvulsants, antibiotics, β-blockers, and stimulants (Table 6.1). The main classes of antibiotics used in livestock farming and by humans are aminoglycosides, β-lactams, fluoroquinolones, tetracyclines, macrolides, sulfonamides, and trimethoprim (Bu et al., 2013; Gurmessa et al., 2020; Tasho & Cho, 2016). Table 6.1 summarizes the main pharmaceutical classes detected in the environment. The occurrence of pharmaceuticals, including antibiotics, in the aquatic environment has been well documented in several studies conducted in different countries since the 1980s in sewages, lakes, rivers, and groundwaters, at concentration levels ranging from a few ng/L to several μg/L (Barber et al., 2015; Kim et al., 2007; Meffe and Bustamante, 2014; Patrolecco et al., 2015; Richardson & Bowron, 1985; Spataro et al., 2019; Simazaki et al., 2015; Ternes & Hirsch, 2000). In most cases, these contaminants come from municipal and industrial wastewater discharges, hospital effluents, and agricultural activities

190 Chapter 6 Table 6.1: Main pharmaceutical classes detected in the aquatic environment. Compound

CAS number

Therapeutic class

Log Kow References

17α-Ethinylestradiol (EE2) 17β-Estradiol (E2) Estrone (E1) Propranolol Bezafibrate Clofibric acid Gemfibrozil Carbamazepine Diazepam Diclofenac Ibuprofen Ketoprofen Naproxen Carbamazepine Sulfachloropyridazine Sulfadimethoxine

57-63-6

Synthetic estrogen

3.7 4.2 Lai et al. (2002)

50-28-2 53-16-7 525-66-6 41859-67-0 882-09-7 25812-30-0 298-46-4 439-14-5 15307-79-5 15687-27-1 22071-15-4 22204-53-1 298-46-4 80-32-0 122-11-2

Steroid hormone Steroid hormone β-Blocking Blood lipid regulator Blood lipid regulator Blood lipid regulator Antiepileptic Tranquilizer Antiinflammatory Antiinflammatory Antiinflammatory Antiinflammatory Anticonvulsant Sulfonamide antibiotic Sulfonamide antibiotic

3.1 3.9 De Mes et al. (2005) 3.1 3.4 De Mes et al. (2005) 0.7 Godoy et al. (2015)

3.26 2.25 0.3 1.6

Sulfadiazine

68-35-9

Sulfonamide antibiotic

20.1

Sulfamerazine Sulfamethiazole Sulfamethoxazole Sulfanilamide

127-79-7 144-82-1 723-46-6 63-74-1

Sulfonamide Sulfonamide Sulfonamide Sulfonamide

0.1 0.5 0.9 20.6

Sulfapyridine

144-83-2

Sulfonamide antibiotic

Sulfathiazole Ciprofloxacin

72-14-0 Sulfonamide antibiotic 85721-33-1 Fluoroquinolone antibiotic 93106-60-6 Fluoroquinolone antibiotic 112398-08- Fluoroquinolone 0 antibiotic 42835-25-6 Fluoroquinolone antibiotic 70458-96-7 Fluoroquinolone antibiotic 82419-36-1 Fluoroquinolone antibiotic 98105-99-8 Fluoroquinolone antibiotic 83905-01-5 Macrolide antibiotic 81103-11-9 Macrolide antibiotic 114-07-8 Macrolide antibiotic 23893-13-2 Macrolide antibiotic

Enrofloxacin Danofloxacin Flumequine Norfloxacin Ofloxacin Sarafloxacin Azithromycin Clarithromycin Erythromycin Erythromycin-H2O

antibiotic antibiotic antibiotic antibiotic

2.9 4.2 1.5 2.8 1.9 2.5

0.05 0.4

Scheytt et al. (2005) Wishart et al. (2006) Scheytt et al. (2005) Radovi´c et al. (2016) Scheytt et al. (2005) Scheytt et al. (2005) Jakimska et al. (2014) Araujo et al. (2011) Wang et al. (2018) Shelver et al. (2010) Thiele-Bruhm and Aust (2004) Thiele-Bruhm and Aust (2004) Shelver et al. (2010) Shelver et al. (2010) Radovi´c et al. (2016) Thiele-Bruhm and Aust (2004) Thiele-Bruhm and Aust (2004) Shelver et al. (2010) Tolls (2001)

1.1

Riaz et al. (2018)

1.85

Riaz et al. (2018)

1.7

Tolls (2001)

21.03

Riaz et al. (2018)

0.4

Tolls (2001)

0.4

Riaz et al. (2018) 4.0 3.16 3.1 3.06

Radovi´c et al. (2016) Wang et al. (2018) Radovi´c et al. (2016) Wang et al. (2018) (Continued)

Some organic compounds in potable water: the PFASs, EDCs and PPCPs issue 191 Table 6.1: (Continued) Compound Roxithromycin Tylosin Chlorotetracycline Doxycycline Oxytetracycline Tetracycline Tetracycline hydrochloride Amoxicillin Cefazolin Penicillin-G Penicillin-V

CAS number

Therapeutic class

Log Kow References

80214-83-1 1401-69-0 57-62-5 564-25-0 79-57-2 60-54-8 64-75-5

Macrolide antibiotic Macrolide antibiotic Tetracycline antibiotic Tetracycline antibiotic Tetracycline antibiotic Tetracycline antibiotic Tetracycline antibiotic

1.7 3.5 20.9 20.02 21.2 21.37 21.2

Wang et al. (2018) Tolls (2001) Wang et al. (2018) Radovi´c et al. (2016) Tolls (2001) Wang et al. (2018) Tolls (2001)

26787-78-0 25953-19-9 61-33-6 132-98-9

β-lactam β-lactam β-lactam β-lactam

0.91 20.58 1.76

Wang et al. (2018) Wang et al. (2018) Halling-Sørensen (2001)

antibiotic antibiotic antibiotic antibiotic

(Luo et al., 2014; Meffe and Bustamante, 2014) and enter the water cycle, where they reach drinking water supplies. Release of drugs into the environment is due to both the improper management of their disposal and their partial metabolization in the organism treated, causing their excretion through urine and feces in sewers as unaltered compounds or as a mixture of metabolites and/or conjugated compounds (Al Aukidy et al., 2012; Luo et al., 2014; Patrolecco et al., 2015; Spataro et al., 2019; Verlicchi et al., 2012). The amount excreted from the human body as unaltered compounds ranges between 5% and 95%, and this is a key parameter affecting the total load of pharmaceuticals introduced into raw wastewaters. Previous studies have shown that the concentrations of pharmaceuticals in hospital wastewaters exceed those recorded in municipal ones (Ku¨mmerer & Helmers, 2000; Schuster et al., 2008). However, other studies highlighted that the total load of pharmaceuticals in hospital wastewaters is diluted by municipal wastewaters by a factor of about 100 (Ku¨mmerer & Helmers, 2000). Treatment in wastewater plants can cause the partial degradation and transformation of pharmaceuticals through oxidation, reduction, hydrolysis, and conjugation reactions, forming new chemicals with potentially different properties which, in turn, can often be considered environmental contaminants (Al Aukidy et al., 2012; Ku¨mmerer, 2010; Loos et al., 2013; Luo et al., 2014). Other treatments, such as adsorption and complexation performed in WWTPs, allow more effective removal of pharmaceuticals, especially of antibiotics. Indeed, it was reported that although sorption on sludge removes only 5% of most antiinflammatories and β-blockers, it allows a removal of up to 90% of tetracyclines, because this class of compounds is characterized by the propensity to sorb to solid particles (Chevre, 2014; Verlicchi et al., 2012). However, knowledge of the adsorption and complexation mechanisms of pharmaceuticals in water or solid matrices is still very poor (Chevre, 2014).

192 Chapter 6 Another important source of pharmaceuticals in the aquatic environment is the use of veterinary antibiotics, the consumption of which is expected to increase globally by up to 100 thousand tons by 2030, due to the increase in the number of livestock (Gurmessa et al., 2020; Kuppusamy et al., 2018; Tasho & Cho, 2016). Several antibiotics are extensively used to prevent animal and human infections, promote growth, and treat diseases in animals. Since the antibiotics, as well as other pharmaceuticals, are only partially absorbed by the animal gut, a substantial amount ends up in manure (Kuppusamy et al., 2018). This causes concern when manure is used as fertilizer in soil for agriculture. Manure is also used to feed anaerobic digestion plants for the production of methane biogas (Gurmessa et al., 2020) and the antibiotics are not effectively removed during the anaerobic digestion processes (Jia et al., 2018; Liu et al., 2018; Mai et al., 2018). The presence of antibiotics in the digestate or manure amended soils is a risk for both food production and the aquatic compartment (trough leaching processes), and thus for drinking water production.

6.3.2 Personal care products PCPs include several classes of chemicals, such as disinfectants, fragrances, insect repellents, preservatives, and UV filters, used as ingredients for the production of lotions, toothpastes, fragrances, soaps, sunscreens, detergents, and cleaning products. PCPs are not directly introduced into the human body, as in the case of pharmaceuticals, but come into contact with it through external applications. Theoretically, they are not subject to metabolic transformations by the organism and are emitted into the environment unaltered (Brausch & Rand, 2011; Ternes et al., 2004). They are extensively used worldwide and previous studies have shown their occurrence in several environmental matrices, such as surface and groundwaters, soil, sediment, and living organisms, demonstrating their environmental persistence or pseudopersistence, bioactivity, and bioaccumulation potential (Ebele et al., 2020; Mackay & Barnthouse, 2010; Yang et al., 2017; Yin, Chen et al., 2017; Yin, Wang et al., 2017). Their release into the environment also occurs through industrial wastes and WWTPs, which are not able to completely remove them. Moreover, the application of sludge containing residual concentrations of these chemicals to soil ecosystems and landfill leaching are additional sources of contamination (Ebele et al., 2020; Vecchiato et al., 2018). The Water Safety Plan approach, a core pillar of the WHO Framework, suggests that a combination of actions such as the improvement of the effectiveness of WWTPs and the development of regulations for the production and marketing of these products is the best way for the management of the water cycle (Fawell & Ong, 2012). Among disinfectants, triclosan, its metabolite methyl-triclosan, and triclocarban are still included as ingredients in personal hygiene products because of their antimicrobial properties. Several studies have shown that triclosan and triclocarban are among the organic

Some organic compounds in potable water: the PFASs, EDCs and PPCPs issue 193 compounds most detected in wastewaters and surface waters, with average concentrations ranging from 0.1 to 6.7 μg/L (Brausch & Rand, 2011; Zhao et al., 2010). Lindstro¨m et al. (2002), monitored the occurrence of triclosan and methyl-triclosan in surface water and WWTPs in Switzerland, reporting their occurrence in the effluents of the plants at 650 and 11 ng/L, respectively, and in surface water at 74 and 2 ng/L, respectively. More recently, triclocarban has been detected in WWTPs and surface water at higher levels than triclosan or methyl-triclosan (Brausch & Rand, 2011; Coogan et al., 2007). All these contaminants are easily bioaccumulated in aquatic organisms in line with their lipophilic properties (Brausch & Rand, 2011). Fragrances have been widely researched because of their ubiquitous presence in the environment, reaching the most remote areas of the planet (Vecchiato et al., 2018; Xie et al., 2007). Synthetic musks, the fragrances most used for personal and household care, include both nitro musks (i.e., musk xylene and musk ketone) and polycyclic musks (Brausch & Rand, 2011; Xie et al., 2007). However, the high persistence and potential toxic effects of nitro musks has resulted in them being used less than polycyclic ones (Peck & Hornbuckle, 2006). Among polycyclic musks, galaxolide and toxalide are produced in large quantities, up to 450 tons per year, to the extent that they are included in the high production volume list by the US EPA (Peck, 2006). N,N-diethyl-m-toluamide (DEET), developed in the 1940s, is the most common active ingredient in insect repellents, with the property of inhibiting the ability of insects to detect lactic acid on hosts (Davis, 1985), and is routinely detected in the aquatic environment (Sui et al., 2015). DEET has been detected in WWTP effluents (Glassmeyer et al., 2005), ground (Sui et al., 2015) and surface waters (Brausch & Rand, 2011; Quednow & Puttmann, 2010), with concentrations ranging from a few ng/L to several μg/L. Although DEET is relatively persistent in the aquatic environment, its low bioconcentration factor suggests it tends to accumulate less in aquatic organisms than other PCPs, such as fragrances and UV filters (Costanzo et al., 2007). Parabens (alkyl-p-hydroxybenzoates) are used for their antimicrobial preservative properties. In particular, methyl- and propylparaben are the two compounds most used, alone or together, in cosmetics to increase preservative effects (Peck, 2006). Brausch and Rand (2011) reported a concentration range of 15 400 and 50 85 ng/L in surface water and WWTP effluents, respectively. Cosmetic products often contain a combination of UV filters, representing up to more than 10% of a product by mass (Brausch & Rand, 2011). UV filters include both inorganic micropigments reflecting UV radiation (e.g., zinc oxide or titanium dioxide) and organic compounds absorbing UV radiation (e.g., methyl-benzylidene camphor). Since these organic compounds are highly lipophilic (log Kow 5 3 7), they can bioaccumulate in aquatic organisms (Balmer et al., 2005; Mao et al., 2019; Poiger et al., 2004). Pegoraro et al. (2020)

194 Chapter 6 indicated that UV filters can also volatilize from aquatic and terrestrial surfaces. Their results showed that these chemicals occur in the atmosphere in both their gaseous and particulate phases, although they concluded that more information about their physicochemical properties and transformation rates and products were needed for a better evaluation of their environmental fate. UV filters can be directly released into the environment during their industrial production or from the human body during swimming and/or other recreational activities, while indirect emission occurs through WWTP effluents (Pegoraro et al., 2020). Their occurrence in different environments, including remote parts of the planet, has been documented (Amine et al., 2012; Pegoraro et al., 2020; Sa´nchez Rodrı´guez et al., 2015), suggesting their significative persistence. Balmer et al. (2005) found an input of 118, 49, 69, and 28 g per 10,000 people per day of 2-ethyl-hexyl-4trimethoxycinnamate (EHMC), 4-methyl-benzilidine-camphor (4MBC), benzophenone-3 (BP3), and octocrylene (OC), respectively, in Swiss WWTPs at peak usage times. 4MBC and BP3 were the most prevalent compounds in surface water, while EHMC and OC occurred at lower levels. Similar results were also obtained by Poiger et al. (2004) in Swiss lakes, who reported a UV filter input of up to 1263 mg per person/daily resulting in 966 kg of UV filters directly emitted into a small Swiss lake.

6.3.3 Alkylphenols and Bisphenol A APs and their polyethoxylated precursors (APEOs) deserve particular attention given their diffusion in all environmental compartments and their estrogenic potency (Jobling & Sumpter, 1993). They belong to the family of EDCs that produce adverse developmental, reproductive, neurological, and immune effects in humans, and abnormal growth patterns and neurodevelopmental delays in children (Monneret, 2017). The most known AP is NP, used mostly to produce NPEO surfactants for many industrial and consumer products: paints and latex paints, adhesives, inks, washing agents, pesticide formulations (emulsions), paper, textiles, leathers, petroleum recovery chemicals, metal working fluids, PCPs, cleaners, and detergents. Other commercially significant compounds are OP and octylphenol ethoxylates (OPEOs). NPEOs represent around 80% of APEOs, while OPEOs comprise the remaining 20%. As a consequence of NPEO use, discharge, and biodegradation, NP occurs ubiquitously in the environment. It has been detected in surface and groundwaters and other sources of potable water. NPEOs and OPEOs are unstable in the environment and both undergo the same processes of degradation to metabolites, which are generally more stable and thus more persistent. Discharge of effluents from sewage treatment plants from industrialized/ urban areas is the main source of NP in the aquatic environment (Soares et al., 2008). Depending on the treatment process unit employed, the efficiency of WWTPs in NP removal has been found to be highly variable, ranging from 11% to 99% (Berryman et al., 2004). The

Some organic compounds in potable water: the PFASs, EDCs and PPCPs issue 195 treatment process based on ozonation and activated carbon filtration with chlorination was the most effective (removal of 95% of NP; Petrovic et al., 2003). These compounds can also accumulate in WWTP sludge making the application of digested sludge as fertilizer in agricultural fields risky and a potential cause of soil and groundwater contamination (Olea et al., 1996). Concentrations of APEO metabolites in treated wastewater effluents, for example, in the United States, ranged from ,0.1 to 369 μg/L (Rudel et al., 1998), in Spain they were between 6 and 343 μg/L (Sole´ et al., 2000), with values of 330 μg/L, in the UK (Blackburn & Waldock, 1995), and between 0.4 and 205 ng/L in Italy (Spataro et al., 2019). Once in the environment, APs and APEOs tend to accumulate in sediments due to their physicochemical characteristics. In groundwater samples, AP concentrations are usually higher than those found in surface water, because their removal is very slow due to the chemical and biological characteristics of aquifers being less suitable to degradation processes, thus allowing contaminants to disperse up to several kilometers from the contamination source (Soares et al., 2008). BPA is used mainly in the manufacture of polycarbonate plastics and epoxy resins and is also found in many other products (polymer additives, flame retardants, thermal paper, etc.). It is an ubiquitous environmental contaminant in sludge and biosolids, with concentrations ranging from 10 to .100,000 μg/kg dry weight (Niu et al., 2015); such different concentrations depending on the characteristics of the influent source loading and effluent treatment processes involved (such as primary and secondary treatment). Staples et al. (2000) developed probabilistic exposure distributions for BPA in sewage sludge and proposed median (50th percentile) and 95th percentile values of 780 and 14,200 μg/kg for North America and 160 and 95,000 μg/kg for the EU.

6.3.4 PAHs, PBDEs, PCBs, and PCDD/Fs PAHs, together with several POPs, like polybrominated diphenyl ethers (PBDEs), PCBs, and PCDD/Fs, have been classed as highly toxic and EDCs. Besides their ascertained carcinogenic and mutagenic potential, these groups of ubiquitous chemicals are known to disrupt the hormonal system, affect fetal development, and have neurobehavioral effects in animals and humans (Bonefeld-Jørgensen et al., 2014; Gregoraszczuk & Ptak, 2013; Safe, 2003; Van den Berg et al., 2006). Their high persistence and resistance to the majority of degradation processes has resulted in a worldwide diffusion of these organic micropollutants in almost every environmental compartment, including various aquatic ecosystems, in which PAHs and POPs have been identified in both abiotic and biotic matrices, and in industrialized as well as remote areas (Capanni et al., 2020; Dong et al., 2018; Fuoco & Giannarelli, 2019; Inam et al., 2018; Khairy & Lohmann, 2020; Singare, 2016).

196 Chapter 6 The occurrence of PAHs and POPs in aquatic environments is mainly related to atmospheric deposition mechanisms, run-off and leaching from contaminated soils, and/or direct or accidental spills from industrial and densely populated areas. These organic micropollutants are characterized by a strong lipophilic behavior, which makes them prone to sorptive interactions with solid particle surfaces, and thus to an intense accumulation in the particulate phases of air, water, and sediments (Bianchi, 2007; Santschi et al., 1999; Venturini et al., 2015). The main sources of PAHs and PCDD/Fs are incomplete natural and industrial combustion processes of organic matter and emissions from land and ship traffic of people and goods. Once emitted in the atmosphere, these chemicals are subject to transport mechanisms, even long-range ones, and can reach aquatic resources through wet and dry depositions in surface water and large water supply basins (Birks et al., 2017; Castro-Jime´nez et al., 2008; Cohen et al., 2002; Fourati et al., 2018). However, other emission pathways, such as those of petrogenic origin for PAHs, should not be overlooked, since accidental spills of petroleum-related products into surface water, or their discharge through the sewage system can represent an important source of contamination of groundwaters feeding drinking water treatment plants (Sa´nchez-Avila et al., 2009; Ugochukwu & Ochonogor, 2018). On the other hand, the major inputs of PBDEs and PCBs into aquatic compartments are related to run-off and leaching mechanisms. Aquifers and groundwaters can act as a carrier of legacy contamination, leaching former inputs of pollutants that are no longer released into the environment, such as PCBs, from contaminated soils or river sediments (Sardin˜a et al., 2019; Urbaniak et al., 2016), while the main source of PBDE contamination can be traced back to the massive use and incorrect disposal of polymers-based products. Since PBDEs, as well as other BFRs, are simply blended with the polymers constituting a wide array of consumer goods, with the wearing of the latter they can be easily released into the environment (Alaee et al., 2003; De Wit, 2002; Rahman et al., 2001). These brominated substances could therefore be leached from contaminated soils into groundwaters, by which PBDEs can reach drinking water basins (Gorgy et al., 2012; Yang et al., 2015). Once PAHs and POPs reach the aquatic environment, the wastewater treatment processes for their removal are based on various methods/techniques. These include chemical oxidation, a process useful for decreasing the toxicity of recalcitrant organic compounds through potassium permanganate and sodium persulfate, and the Fenton process, which consists of the reaction between ferrous salt and hydrogen peroxide, generating hydroxyl radicals and oxidizing Fe21, in an acid solution (Chen et al., 2001). The percentages of removal of unwanted organic substances can vary from 30% to 70% depending on the dose of reactant and the micropollutant diffusion rate. Other techniques available are based on electrochemical, catalytic oxidation, and advanced oxidation processes (AOPs). In general, conventional techniques have the drawback of poor efficiency in the degradation and removal of high-molecular-weight compounds, which can usually be achieved in membrane

Some organic compounds in potable water: the PFASs, EDCs and PPCPs issue 197 bioreactors (Margot et al., 2015). AOPs based on various applications (UV/O3/H2O2, UV/ H2O2/TiO2, and UV/TiO2/Fe21), coupled or combined with conventional techniques (e.g., biological processes) can promote the high removal of organic pollutants (Miklos et al., 2018). However, further assessment of the processes/methods is needed to reduce costs and decrease the potential formation of more toxic by-products (Kumar Gaurav et al., 2020). For instance, PPCPs (e.g., triclosan) can be present in the environment, so that the assessment of AOP characteristics is important for preventing the potential formation of toxic secondary products such as PCDD/Fs, since some precursor compounds of these POPs are widespread in wastewaters (San-Roma´n et al., 2020).

6.3.5 Per- and polyfluoroalkyl substances PFASs have been in use industrially since the 1950s as raw materials, ingredients, intermediate products, and finished products in many technical and consumer applications. Among PFASs, the subclasses that have received the most attention are the perfluorinated carboxylic (PFCAs) and sulfonic (PFSAs) acids, collectively termed here perfluoroalkylacids (PFAAs), because they are the persistent final transformation products of many precursors used in industrial processes. Their widespread use is due to their fire- and oil-resistant and stain-, grease-, and waterrepellent qualities, so that they are commonly found in a range of industrial and consumer goods. Because of their persistency, toxicity, and ability to bioaccumulate, many long-chain PFAAs are found globally in various environments and trophic levels. PFAAs are still manufactured and used in the metal plating, photographic, fire-fighting foams, semiconductor, and aviation industries. 98% 100% of historical (1951 2002) PFOA emissions are attributed to direct releases during the life cycle of products containing PFOA, especially polytetrafluoroethylene polymers. An estimation of the production, use, and release of PFOS can be based on concentrations and water flux in rivers or WWTPs. For instance, Pistocchi and Loos (2009), estimated overall aqueous emissions of PFOSs from the European Continent by using measured concentrations of them in rivers. Due to their relatively high solubility, PFAAs can easily get diffused in water and subsequently enter other aquatic media: influents of WWTPs were usually identified as key confluences for PFAAs. They have been widely detected in surface waters, with concentrations ranging from pg/L to thousands of ng/L (Labadie & Chevreuil, 2011; Nguyen et al., 2017; Wang & Hopke, 2014; Yin, Chen et al., 2017; Yin, Wang et al., 2017). The concentrations of PFAAs in groundwater can reach μg/L or even mg/L levels at some contaminated sites, which can result in contamination of drinking water (Backe et al., 2013; Yin, Chen et al., 2017; Yin, Wang et al., 2017). In a 3-year monitoring campaign (2010 13), Castiglioni et al. (2015) investigated the occurrence of 12 PFAAs in the River

198 Chapter 6 Lambro basin in the most urbanized and industrialized area of Italy. Despite the ubiquitous contamination of groundwater by PFAAs, they were removed effectively during the drinking water treatments adopted in the city of Milan. The results of different studies on the main rivers in Northern Italy revealed that those in a large area of the Veneto Region in Northeast Italy were contaminated by PFASs, which were also found in drinking water samples (Bertanza et al., 2020; Mazzoni et al., 2015). Twelve PFASs were detected and the results led to identifying a production facility in that area, producing PFAS since the late 1960s, as the only likely source of the water contamination. Measurements of 152 drinking water samples collected in the summer months reported that the main compounds were PFOA (median 319 ng/L, maximum 1475 ng/L), perfluorobutanoic acid (median 123 ng/L, maximum 625 ng/L), and perfluorobutane sulfonic acid (PFBS; median 91 ng/L, maximum 765 ng/L). In the same period, the local water treatment plants were equipped with granular activated carbon (GAC) filters, which led to an abrupt reduction in PFAS concentrations in the drinking water distributed by public waterworks, and the effectiveness of the treatment continued to improve, so that by 2018 PFAS compounds were undetectable in the majority of samples (WHO, 2017).

6.4 Environmental and ecosystem effects From an environmental point of view, the organic molecules that are of greatest current concern are those which, either by their persistence and/or their accumulation ability, can have toxic or inhibitory effects on living organisms. Ecological risk assessment is often performed by comparing the measured (MEC) and predicted environmental concentrations of a target contaminant with a water quality criterion (WQC) considered safe for the ecosystem over a long period and used to estimate the predicted no-effect concentration (PNEC) for the most sensitive species. Several organisms, including plants, fish, crustaceans, and algae, and microorganisms, such as Vibrio fisheri photobacteria, are used to determine the toxic effects of these contaminants (Rosal et al., 2010). However, this approach suffers from large uncertainties depending on the differences among the species in terms of sensitivity, acute-to-chronic ratios, and laboratory-to-field extrapolations, so that a wide range of PNECs can be determined for the same contaminant (Chevre, 2014; Mortimer et al., 2020). The evaluation of risks associated with PPCPs or EDCs occurring in drinking water requires calculating acceptable daily intake (ADI) or TDI parameters, based on the minimum therapeutic dose or no-observed-adverse-effect-level/lowest-observed-adverse-effect-level in conjunction with an uncertainty factor, ranging from 1000 to 10,000. These parameters are useful for calculating a drinking water effect level (DWEL; https://www.wqa.org).

Some organic compounds in potable water: the PFASs, EDCs and PPCPs issue 199 Comparing the DWEL with available occurrence data (MEC) for a given chemical allows the calculation of the margin of safety (Table 6.2, https://www.wqa.org). Although, among pharmaceutical residues, antibiotics are detected at subtherapeutic concentration levels in the aquatic environment, they pose a potential risk to both human and natural ecosystems health (Mortimer et al., 2020). Specifically, antibiotics and their active ingredients and additives, pose a hazard to human microbiomes via ingested food or drinking water (Ben et al., 2019) and can exert selective pressure on the functioning and structure of natural nontarget microbial communities (Grenni et al., 2018; Xiong et al., 2015). Moreover, the simultaneous presence of pharmaceuticals with other xenobiotics can result in a synergistic or inhibitory effect (Aydin et al., 2015; Grenni et al., 2018; Yazan et al., 2018). There is increasing interest in the spread of antibiotic-resistant bacteria (ARB) and antibiotic resistance genes (ARGs) in aquatic ecosystems, which can themselves be considered ECs, with the potential to reduce antibiotic therapeutic effectiveness against human and animal pathogens (Ben et al., 2019; Mortimer et al., 2020). A recent work showed that high exposure to coastal waters (i.e., through human recreational exposure in coastal bathing waters and sport surf activities) is associated with higher human gut exposure to the ARB Escherichia coli, responsible for serious extraintestinal infections (Leonard et al., 2018). However, there are significant knowledge gaps in the human and environmental risk assessment of antibiotics and few data available on their concentrations inducing ARB or ARG spread into aquatic ecosystems (Murray et al., 2020). The Veterinary International Conference on Harmonization guidance (VICH, 2012) recommends calculating safe antibiotic levels in drinking water to protect against the increase of ARB. In this case, the ADI values are calculated based on the minimum inhibitory concentration for medically significant sensitive bacterial genera. The scientific community and industry Table 6.2: Examples of the margin of safety level calculated for selected pharmaceuticals and personal care products (PPCPs) and endocrine disrupting compounds (EDCs) based upon the corresponding drinking water effect level (DWEL) values. Compound

MEC in drinking water (ng/L)

Safety levels (DWEL)

Meprobamate Phenytoin Atenolol Carbamazepine Naproxen Bisphenol A Linuron Nonylphenol

3.8 42 2.3 1.2 18 6.3 0.052 25 6 6.2 100

6000 210 2700 670 40,000,000 72,000 8400 16,000

Maximum contaminant level assigned by Safe Drinking Water Act (SDWA; https://www.wqa.org). MEC, measured environmental concentration.

200 Chapter 6 stakeholders have made efforts to estimate antibiotic concentrations that, based on current empirical knowledge, should provide safety limits (PNECs) for protecting human health from the risks of antimicrobial resistance selection (Bengtsson-Palme & Larsson, 2016; Le Page et al., 2017; Mortimer et al., 2020). However, a wide dissimilarity between the PNEC values proposed for the same antibiotic in the various frameworks has arisen. For example, Le Page et al. (2017) suggested a single-value production discharge limit (in the mixing zone downstream from the point source discharge) of 100 ng/L, based on no observed effect concentrations of antibiotics for environmental bacteria and minimum selective concentrations for clinical bacteria, to protect ecosystems and curb antimicrobial resistance. More recently, Mortimer et al. (2020) calculated the highest acceptable human drinking water concentrations (HDWCs) based on ADI values and assuming that humans could be exposed to an antibiotic via drinking 2 L of water (for an adult) as well as eating an average of 17.5 g of fish from water near the drinking water intake, as reported in the US EPA Water Quality Criteria Guidance (https://www.epa.gov/wqc/national-recommendedwater-quality-criteria-tables). Table 6.3 reports the PNECs calculated for some antibiotics following the Bengtsson-Palme and Larsson (2016) and Le Page et al. (2017) approaches and the highest acceptable HDWCs in the VICH framework calculated by Mortimer et al. (2020). The risks associated with the occurrence of PPCPs in the environment are also related to their acute ecotoxicity, genotoxicity, and endocrine disruption (Rosal et al., 2010). Some PPCPs, such as steroids, and natural and synthetic hormones are endocrine disruptors affecting sexual functions and the hormonal and reproductive systems, causing adverse health effects in organisms, their progeny or subpopulations. Veterinary growth hormones, Table 6.3: Predicted no-effect concentrations (PNECs) and highest acceptable human drinking water concentrations (HDWCs) of some antibiotics, calculated following different approaches (Mortimer et al., 2020). Class of contaminants Quinolones

Antibiotic

Ciprofloxacin Levofloxacin Moxifloxacin Sulfonamides Sulfamethoxazole Diaminopyrimidines/ Trimethroprim sulfonamides β-Lactams Amoxicillin Cephalexin Tetracyclines Doxycycline Lincosamides Clindamycin Macrolides Azithromycin

PNEC (ng/L) (Bengtsson-Palme & Larsson, 2016)

PNEC (ng/L) (Le Page et al., 2017)

HDWC (ng/L) (Mortimer et al., 2020)

64 250 125 16,000 500

450 100 100 600 100,000

208 1490 272 1232 63,214

250 4000 2000 1000 250

100 80 100 100 20

552 76,350 984 290 10

Some organic compounds in potable water: the PFASs, EDCs and PPCPs issue 201 cleaning products, antimicrobials, food preservatives, phthalates, BPA, and NPs are some examples of EDCs (Dhodapkar & Gandhi, 2019; Wielogo´rska et al., 2015; Wilkinson et al., 2016). From the ecotoxicological point of view, NP is persistent in the aquatic environment, moderately bioaccumulative, and extremely toxic to aquatic organisms (David et al., 2009; Lozano et al., 2012; Soares et al., 2008). Though less toxic than NP, NPEOs are also highly toxic to aquatic organisms and degrade to more environmentally persistent NPs (Lozano et al., 2012). They have shown estrogenicity, with a wide variety of cell lines and receptors: human MCF7 cells, rainbow trout hepatocytes, and mouse and human estrogen receptors. Their estrogenic activity is due to para- and 4-substituted compounds and is dependent on the length of the ethoxy chain (Tollefsen et al., 2008). Besides, NP and OP can also act as androgen receptor antagonists (Xu et al., 2020). Biomonitoring data have shown that the general population is exposed to APs and APEOs (Ademollo et al., 2008; Ferrara et al., 2011). The main sources of human exposure are contaminated drinking water and food (Lu et al., 2007; Raecker et al., 2011) and/or through contact with PCPs and detergents (Brooke et al., 2005). BPA is also known to be an endocrine disruptor as shown by in vivo and in vitro studies (Vandenberg et al., 2007). BPA acts as an agonist for the estrogen receptor alpha, with a binding affinity three to four orders of magnitude lower than that of 17β-estradiol (Cabaton et al., 2009). Furthermore, antiandrogenic activity was also observed when BPA was exposed to mammalian CV-1 cell lines (Xu et al., 2005). In December 2002, the Organization for Economic Co-operation and Development classified PFOS as a PBT chemical (https://www.oecd.org/env/ehs/risk-management/ P PFC_FINAL-Web.pdf). The concentrations of PFAAs found in fish ranged from not detectable to ca. 700 ng/g wet weight (w.w.) in various tissues, while the highest were reported in blood plasma and liver (Li et al., 2021). For the purposes of human risk assessment, three major types of exposure to PFAAs have been distinguished: general human exposure, occupational exposure, and prenatal and neonatal exposure. Human exposure to perfluoroalkyl substances encompasses inhalation of outdoor and indoor air including suspended household dust, and oral exposure through drinking water and food consumption, with drinking water being the dominant PFAA transfer route. PAHs, PBDEs, PCBs, and PCDD/Fs are ubiquitous toxic pollutants that can negatively impact the environment with harmful effects on fauna and humans. Although many of these compounds have been outlawed in recent decades, they continue to be researched because they are widely found in different environmental compartments in both industrialized and urbanized areas and remote ones, showing a high biomagnification potential along aquatic food chains and still posing a potential threat to humans and ecosystems. PAHs and the organohalogen compounds mentioned are recognized for their teratogenic, carcinogenic,

202 Chapter 6 and mutagenic effects, showing particular toxicity for birds and aquatic organisms and a risk of cancer for the population exposed (Kim et al., 2013; Lauby-Secretan et al., 2013; Van den Berg et al., 2006; Cetin et al., 2018; Dunnick et al., 2018; Li et al., 2018). Human exposure can occur through various pathways, with inhalation, water consumption, and dietary intake representing the major ones. Unintentional ingestion of contaminated soil through the consumption of agricultural products and dermal contact can represent secondary human intake pathways (Harrad, 2001; Kro´l et al., 2013; Polachova et al., 2020). Due to their ability to affect the endocrine system of animals and humans, PAHs, PBDEs, PCBs, and PCDD/Fs are regarded as EDCs as they mimic or block the activity of endogenous hormones. Several bioassays such as animal/plant tests, and cell, microbial, and protein assays, have been carried out to study and understand the role and biological activities/effects of these organic micropollutants, showing they can suppress the immune system and interact with the hormone system (Ding et al., 2017; Lasserre et al., 2009; Legler & Brouwer, 2003; McGovern, 2006; Svobodova´ et al., 2009; Zhang et al., 2016). Their toxicity is strictly connected to their molecular structure, which determines the capacity of interaction with certain receptors, including the AhR aryl hydrocarbon receptor, during the DNA transcription. The planar structure of PCDD/Fs, non- or mono-orthosubstituted dl-PCBs, together with several PBDEs, promotes an extremely high binding affinity with the basic Helix Loop Helix AhR transcription factor, which regulates the hepatic MFO (mixed-function oxidase) enzymes, involving cytochromes P450 (Petriello et al., 2014). AhR normally deactivates xenobiotic toxic compounds, making them more soluble, and thus facilitating their excretion. However, in some conditions, it may also result in the production of reactive metabolites that are more toxic than the original chemicals, can be resistant to further degradation processes and are not excreted (Machala et al., 2004). As for PAHs, the presence in the molecule of the so-called bay region gives a high degree of biochemical reactivity to several PAH compounds. The priority metabolic pathway of this group of PAHs leads to the production by MFO of diol epoxide adducts, able to bind covalently to several guanine positions in DNA genes, causing genotoxic and carcinogenic effects (ATSDR, 2002).

6.5 Drinking water treatment plants Table 6.4 shows the concentration of several classes of organic compounds detected in drinking water and reported in the current literature. A wide range of drinking water treatment processes have been developed; however, none have been specifically designed for the reduction of organic micropollutants such as PPCPs and EDCs. For example, activated carbon filters (powdered and granular) have demonstrated effectiveness in reducing several PPCPs and EDCs, through both chemical adsorption and biodegradation (Halden, 2010; WHO, 2012). Carbon type, loading, and contact time are

Some organic compounds in potable water: the PFASs, EDCs and PPCPs issue 203 Table 6.4: Concentration of organic contaminants detected in drinking water. Class of contaminants

Compound

Concentration (ng/L) Country

Disinfectant

Triclosan

280 59.6 48.0

USA USA USA

Insect repellent Antifungal Antihistamine

DEET Fluconazole Loratadine Prednisone Betamethasone Carbamazepine

0.5 24.0 91 1200 17.0 98 2800 34 180 0.0 25.0 258.0 0.0 43.2 60.0 1.9

USA Brazil Brazil Brazil Brazil USA Canada France Germany Portugal

Dilantin

50.0 13.0

USA UK

Primidone Diazepam

40.0 49.0

Germany USA

Meprobamate

55.0

USA

Bleomycin Diatrizoate Iopromide

13.0 1.2 , 0.05

UK Germany Germany

Bezafibrate Clofibric acid

,5.0 50.0 13.0 0.0 2.3 49.0 8.0

Germany Germany Italy France USA Brazil

0.0 0.0 2.5 0.0 9.4 35.9

USA France USA Germany

0.1 10.2 8.5

USA Finland

Steroid medication Anticonvulsant

Antidepressant, antianxiety

Antineoplastic Iodinated x-ray contrast media Lipid regulator

Gemfibrozil

NSAID and analgesics Acetaminophen Diclofenac

Ibuprofen

References Loraine and Pettigrove (2006) Padhye et al. (2014) Vanderford and Snyder (2006) Padhye et al. (2014) Santos et al. (2020) Santos et al. (2020) Santos et al. (2020) Santos et al. (2020) Padhye et al. (2014) Stackelberg et al. (2004) Togola and Budzinski (2008) Heberer et al. (2004) de Jesus Gaffney et al. (2015) Vanderford and Snyder (2006) Mompelat et al. (2009) Heberer et al. (2004) Vanderford and Snyder (2006) Vanderford and Snyder (2006) Mompelat et al. (2009) ´ (2007) Pe´rez and Barcelo ´ (2007) Pe´rez and Barcelo Heberer et al. (2004) Heberer et al. (2004) Zuccato et al. (2000) Togola and Budzinski (2008) Vanderford and Snyder (2006) Santos et al. (2020) Padhye et al. (2014) Togola and Budzinski (2008) Padhye et al. (2014) Heberer et al. (2004) Padhye et al. (2014) Vieno et al. (2005) (Continued)

204 Chapter 6 Table 6.4: (Continued) Class of contaminants

Compound

Concentration (ng/L) Country

Naproxen

0.0 5.1 0.0 9.1 , 1.0

USA France Finland

Ketoprofen

8.0 0.0 3.0

Finland France

Psychostimulant

Phenazone Propyphenazone Caffeine

0.25 0.08 0.0 11.6 0.0 22.9 4.0

Germany Germany USA France Portugal

Macrolide antibiotic

Erythromycin

5.7 1.0 13.8

Portugal USA

Sulfonamide antibiotic

Clarithromycin 0.0 0.2 Sulfamethoxazole 0.0 12.7 54.0

USA USA USA

Diaminopirimidine antibiotic

Trimethoprim

0.0 19.8 50.0

USA USA

β-Blo|cker

Atenolol

0.2 0.0 34.1

Portugal USA

Phenolic compounds

BPA

0.0 44.3 58.0

USA USA

4-NP NPE P 2O NPEnO 6 PAHs 16 PAHs 16 PAHs

12.4 60.1 4.1 81 0.9 15 39 204 15 844

USA Italy Italy USA Poland China

Polychlorinated dibenzo-p-dioxins

2,3,7,8substituted, PCDDs 7 congeners

0.00005 0.0093 0.000001 4.059

China Taiwan

Padhye et al. (2014) Togola and Budzinski (2008) Vieno et al. (2005) Vieno et al. (2005) Togola and Budzinski (2008) Zu ¨hlke et al. (2004) Zu ¨hlke et al. (2004) Padhye et al. (2014) Togola and Budzinski (2008) de Jesus Gaffney et al. (2015) de Jesus Gaffney et al. (2015) Padhye et al. (2014) Padhye et al. (2014) Padhye et al. (2014) Vanderford and Snyder (2006) Padhye et al. (2014) Vanderford and Snyder (2006) de Jesus Gaffney et al. (2015) Padhye et al. (2014) Padhye et al. (2014) Vanderford and Snyder (2006) Padhye et al. (2014) Loos et al. (2008) Loos et al. (2008) Basu and Saxena (1978) Nowacka and WłodarczykMakuła (2013) Ma et al. (2008) Chen et al. (2008) Nguyen et al. (2017)

Polychlorinated dibenzofurans

2,3,7,8substituted PCDFs 10 congeners

0.00003 0.056 0.000001 0.2695

China Taiwan

Chen et al. (2008) Nguyen et al. (2017)

Polycyclic aromatic hydrocarbons

References

(Continued)

Some organic compounds in potable water: the PFASs, EDCs and PPCPs issue 205 Table 6.4: (Continued) Class of contaminants Polychlorinated biphenyl Polybrominated diphenyl ethers

Perfluoroalkyl substances

Compound

Concentration (ng/L) Country

References

dl-PCBs 12 congeners PBDEs 7 congeners PBDEs 8 congeners PBDEs 9 congeners P PFAA

0.00001 0.0025 0.000001 0.173 0.00848 0.2478 0.000017 0.00082 0.000045 0.000449

China Taiwan China Pakistan South Africa

Chen et al. (2008) Nguyen et al. (2017) Shao et al. (2018) Khan et al. (2016) Sibiya et al. (2019)

16 137

Italy

Castiglioni et al. (2015)

2 61 0.1 51 0.24 0.92 nd 15 nd 9.7 2.4 8.1 0.5 0.2 0.2 1.0 3.9 11.7 2.3 98.6 2.5 108

Italy Japan China China Australia Australia Italy Italy Italy Italy Italy Italy USA USA USA

Castiglioni et al. (2015) Harada et al. (2003) Zhang et al. (2011) Zhang et al. (2011) Thompson et al. (2011) Thompson et al. (2011) Loos et al. (2008) Loos et al. (2008) Loos et al. (2008) Loos et al. (2008) Loos et al. (2008) Loos et al. (2008) Dasu et al. (2017) Dasu et al. (2017) Dasu et al. (2017)

P PFAA PFOS PFOS PFOA PFOS PFOA PFOA PFOS PFNA PFDA PFUnA PFDoA PFBS PFOS PFOA

critical factors for effective removal of contaminants. Reverse osmosis (RO) has also proven to be effective (Halden, 2010). Chlorination, ozonation, and peroxidation are also effective in the oxidation of many PPCPs and EDCs. The effectiveness of oxidizing agents is highly dependent upon pH and dose (Halden, 2010; WHO, 2012). However, many studies aimed at evaluating the fate of PPCPs and EDCs in DWTPs are mainly focused on pharmaceuticals, and there continues to be a lack of knowledge about the removal of most PCPs. Even if disinfection processes using common oxidants, including chlorine, chlorine dioxide, and chloramine, are able to reduce PPCPs and EDCs in drinking water, there can be a formation of their halogenated or partly oxidized transformation products (Leusch et al., 2019). This finding was reported for acetaminophen (Zhang et al., 2016), BPA (Bourgin et al., 2013), carbamazepine (Soufan et al., 2013; Tran et al., 2018), estrone (Nakamura et al., 2007), 17αethinylestradiol (Nakamura et al., 2006), gemfibrozil (Bulloch et al., 2012), and triclosan (Ben et al., 2016). Moreover, some authors showed that the chlorination process can favor an increase in bacteria resistant to chloramphenicol, trimethoprim, and cefotaxime, and a spread in ARG (Shi et al., 2013; Xu et al., 2020; Zheng et al., 2018).

206 Chapter 6 Fu et al. (2019), investigated the occurrence and removal of PPCPs, including diclofenac, erythromycin, norfloxacin, roxithromycin, sulfamethoxazole, sulfamethazine, trimethoprim, BPA, triclosan and triclocarban, in two different DWTPs in China. Coagulation and sedimentation were applied in both plants, but the first plant also employed ozonation and GAC filtration processes, while the second one included anthracite and GAC filtration treatments. Sulfamethoxazole and erythromycin were found to be at high concentrations due to their extensive use in human and veterinary medicine. The removal efficiencies varied depending on the compounds and on the treatment process. Coagulation, filtration, and GAC processes were able to remove less than 50% of the PPCPs due to their hydrophilicity. Ozonation turned out to be more effective in reducing PPCPs (by more than 90%), even if partial mineralization and formation of by-products occurred. Similar results were reported by Padhye et al. (2014) for the insect repellent diethyltoluamide (DEET) and 4-NP in an urban DWTP in the Southeast United States. Riva et al. (2018) analyzed the occurrence of 21 ECs in the drinking water network of Milan (Italy), including antibiotic, anticancer, antiinflammatory, and illicit drugs, and evaluated the risks for humans. Their results showed that pharmaceuticals were among the most detected compounds, confirming that these chemicals are ubiquitous in the water cycle. However, the results obtained by their human risk assessment excluded any real risk for human health ascribable to these ECs. Ternes et al. (2002) performed laboratory and field studies to evaluate the removal of some pharmaceuticals, such as bezafibrate, clofibric acid, carbamazepine, and diclofenac, during drinking water treatment processes. The labscale experiments showed that the flocculation using the iron(III) chlorine process does not significantly remove the contaminants investigated. Ozonation instead effectively (90%) removed diclofenac and carbamazepine at an ozone concentration of 0.5 mg/L. Benzofibrate was 50% removed with an ozone dose of 1.5 mg/L, while the concentration of clofibric acid was constant even at 3 mg/L of ozone. The field measurements carried out by Ternes et al. (2002), confirmed the laboratory results and indicated that GAC filtration is very effective in pharmaceutical removal, except for clofibric acid. Rozas et al. (2017) performed batch experiments with ultrapure and natural water on the degradation of atrazine, carbamazepine, diclofenac, and triclosan by ozone and ozone/powdered activated carbon. Their results showed that carbamazepine, diclofenac, and triclosan, combined directly with ozone, were quickly oxidized, while the oxidation of atrazine occurred slowly, because in this case the process was driven by OH radicals. The authors also suggested the inclusion of powdered activated carbon to improve the removal of ECs in DWTPs (Rozas et al., 2017). HuertaFontela et al. (2010) studied the occurrence and removal of 15 pharmaceuticals, hormones, and metabolites through a drinking water treatment, focusing on the behavior of the target contaminants during each treatment, that is, prechlorination, coagulation, sand filtration, ozonation, GAC filtration, and postchlorination. These authors reported that the removal of the pharmaceuticals was .95%. Stackelberg et al. (2007) measured the concentration of

Some organic compounds in potable water: the PFASs, EDCs and PPCPs issue 207 113 organic pollutants, including pharmaceuticals, detergents, flame retardants, plasticizers, PAHs, and fragrances, in the water and sediment of a conventional DWTP. Their results indicated that the removal efficiencies achieved by GAC filtration, disinfection and clarification were on average 53%, 32%, and 15%, respectively. The effectiveness of these treatments was affected by the chemical properties of the contaminant class; in particular, hydrophobic compounds were strongly oxidized by free chlorine. Vieno et al. (2005) studied the removal of diclofenac, ibuprofen, bezafibrate, carbamazepine, and sulfamethoxazole by chemical coagulation in laboratory jar test experiments on surface water matrices using acid solutions in aluminum (pH 6) and ferric sulfate (pH 4.5). They showed that diclofenac, ibuprofen, and bezafibrate could be removed in the presence of dissolved humic matter by coagulation with ferric sulfate, with removal efficiencies of 77%, 50%, and 36%, respectively, while carbamazepine and sulfamethoxazole were not removed by this treatment. It should be noted that although several studies have been performed to evaluate the occurrence and removal of pharmaceuticals during drinking water treatments, current knowledge is certainly still incomplete and needs to be improved. In some drinking wells APE chemicals were detected at concentrations ranging from less than the limit of detection to 32.9 μg/L (Rudel et al., 1998). Padhye et al. (2014) collected water samples from drinking water supplies in the southeast United States at the river water pumping station (surface water), reservoir effluent, flocculation/sedimentation effluent, ozonation effluent, and in clearwell (i.e., drinking water) stages. The results indicated an NP concentration of 83 ng/L in surface water and 19 ng/L in drinking water and a BPA concentration of 13 ng/L in surface water and 2.7 ng/L after all the treatments. The authors remark that the removal of EDCs did not depend only on their physicochemical properties but also on the surface water characteristics, operational conditions, and treatment technologies used. Magi et al. (2010) analyzed NP and BPA in drinking waters collected by passive sampling deployed in both the inlet and outlet of a drinking water treatment plant. In the source waters, BPA was the most abundant compound, ranging from 17.0 to 56.4 ng/L, followed by NP (2.4 9.9 ng/L). Overall, the results showed a rather low level of contamination in the inlet, while concentrations of all the analytes were always below the limit of quantification (LOQ) in the outlet, indicating their removal by the water treatment plant. Benotti et al. (2009), measured EDC occurrence in US source water and subsequent drinking water after removal during chlorine or ozone oxidation treatment. NP had an average concentration in source water of 80 ng/L and dropped to 8 ng/L after treatment, while BPA had a median value of 5 ng/L and below the LOQ in drinking water. The growing attention to an efficient removal of PFASs from water resources is a consequence of the regulatory attention and general concern regarding exposure to PFASs (US EPA, 2016; ATSDR, 2018). From 2003 to 2017, perfluoroalkyl substances have been detected in drinking water in several places in the world: Japan (Harada et al., 2003), China

208 Chapter 6 (Zhang et al., 2011), Australia (Thompson et al., 2011), the European Union (Loos et al., 2008; WHO, 2017), and the United States (Dasu et al., 2017). Kabore´ et al. (2018) analyzed legacy and newly identified PFASs in drinking water samples from different countries around the world. The detection frequencies in tap water were high (64% 92%) for short-chain PFCAs/PFSAs and the regulated PFOS and PFOA did not exceed 5 ng/L across the 97 samples surveyed. A risk assessment approach performed by the authors suggested that the concentrations of PFOA and PFOS found in their study should not pose a health risk for drinking water consumers. Traditional water treatments demonstrated scarce removal efficiency for PFAAs, including flocculation, coagulation, sand-filtration, and ozonation. Eschauzier et al. (2012) reported that the treatment technology that has been proven to be efficient is GAC filtration (Kothawala et al., 2017; McCleaf et al., 2017). Nevertheless, the removal of PFAAs by GAC is usually PFAA-dependent and cocontaminants-dependent (Appleman et al., 2014). Short-chain PFAA (PFCAs with fewer than seven and PFSAs with fewer than sex fluorinated carbons) retention by activated carbon is less satisfactory as a result of lower hydrophobicity and higher mobility in the aqueous phase. Overall, improving the performance of GAC for PFAA removal is very important in water treatment (Meng et al., 2020). A promising technology consists of aeration and follow-up abstraction of generated aerosols or foams, based on the adsorption of PFASs at air water interfaces (Meng et al., 2018). The use of membrane technology, such as RO and nanofiltration, to remove PFAAs from water has been shown to be successful for PFAAs with an alkyl chain longer than perfluoropentanoic acid and perfluoropentane sulfonate (Eschauzier et al., 2012). PAHs and other POPs, such as PCDDFs, PCDFs, PCBs, and PBDEs, have been reported in drinking water sources, showing a widespread presence in different countries with concentration levels varying from sub pg/L to μg/L (Table 6.4). Several technologies have been developed in water and WWTPs for the quantitative removal of many persistent chemicals (Basile et al., 2011). For instance, the removal of PAHs from surface waters has been mainly carried out using chemical AOPs. In conventional drinking water systems, the most common technique is based on chlorination, but this can generate carcinogenic and mutagenic halogenated hydrocarbons (trihalomethanes and haloacetic acids) (Manoli & Samara, 2008). Other chemical processes are ozonation, direct photolysis, and the use of potassium permanganate (Bernal-Martinez et al., 2009; Brown et al., 2003; Sanches et al., 2011). Other AOPs, classified as photochemical and nonphotochemical techniques and using, for example, UV-VIS, H2O2, or O3, can be coupled with aerobic or anaerobic biological processes or other treatments and, by exploiting a combination of oxidants, energy sources, and catalytic action, can offer an effective solution for the removal of PAHs from drinking waters, groundwaters, and wastewaters (Gogate & Pandit, 2004; Matilainen & Sillanpa¨a¨, 2010; Vela et al., 2012). Several parameters, such as the oxidant dose and light intensity, together with pH, pollutant concentrations, and water matrix constituents, verify the efficiency of the oxidation process. Energy consumption and the

Some organic compounds in potable water: the PFASs, EDCs and PPCPs issue 209 cost of the chemicals still make these water treatments very expensive. Biological processes for water decontamination are found to be more reliable and economical, but they need a pretreatment step using chemical and/or physical techniques to make organic pollutants that are easily biodegradable for microorganisms that are usually sensitive to toxic compounds (Rubio-Clemente et al., 2014).

6.6 Conclusions and future trends Organic micropollutants are continuously entering the environment and water cycle due to anthropogenic emission and water use and reuse. Anthropogenic contaminants include most ECs and EDCs, which are generally not monitored, although they could have potential adverse health consequences. Since most of them enter ecosystems through urban wastewater, there is an accelerated and continuous discharge of these pollutants, without any regulation, into water resources, including groundwater, which poses a serious threat to both environmental and health safety conditions. In addition, the concentrations of most organic micropollutants in the aquatic environment are increasing because of their persistence, thus adversely affecting water resource availability and quality. The removal of micropollutants during drinking water production is a current key issue for future drinking water quality legislation. The use of proper techniques and the improvement of abatement technologies in treatment plants therefore has to be considered in order to optimize their removal, increase water supply quality, satisfy future directives and standards regarding potable water, and provide significant health benefits. Although an increasing number of different classes of organic micropollutants are being studied and characterized worldwide, several aspects still represent a challenge and require further research efforts: • •

•

•

lack of knowledge about the environmental and toxicological impacts of mixtures of organic micropollutants that could adversely affect aquatic life and human health; most ECs remain unregulated or in the process of regulation. Among these, PPCPs and EDCs are being continuously introduced into the environment at biologically active concentrations and are of particular concern for water quality; the development of new analytical techniques for detecting and quantifying mixtures of biologically active chemicals at extremely low concentrations in the aquatic environment need to be validated and harmonized, to ensure their continuous monitoring and control, with a view to better regulation of these contaminants in the near future; an urgent need to implement alternative water treatments, such as biological filters, advanced oxidation, and other new technologies ensuring the efficient elimination of organic micropollutants. The treatment and/or control procedures for the protection of the environment, ecology, and public health need to be defined, with access to appropriate information on the potential associated risks.

210 Chapter 6 Water resources protection is the first step in protecting drinking water quality. The planning and implementation of protection measures will require working together with many sectors, such as national and local authorities; agricultural, industrial and other commercial entities, and communities. An economic evaluation of water ecosystem “services” should be well-thought-out in order to lay the basis for correct future actions and proper governability of hydric resources. A holistic approach, based on scientific research, appropriate policies, the sustainable management of water resources, and technically advanced monitoring programs can address the complexity of human environmental systems, by introducing regulations in support of water governance for a sustainable development based on water availability and demand. In this context, scientific research plays an essential role to fill knowledge gaps regarding the environmental occurrence and dynamics of organic pollutants in aquatic ecosystems and their ecotoxicological and toxic implications, with a view to providing important tools in the planning for their control and treatment, all crucial aspects for the protection of the environment, biota, and human health. Particular attention must be paid to the presence of ECs, about which the knowledge up to now gained is not enough for the correct management of the overall contamination of water resources.

Acknowledgments The authors would like to thank Dr. Pierfrancesco Gigliucci, Acea Engineering Laboratories Research Innovation Acea Elabori SpA, Rome (Italy) for providing some technical information on DWTPs.

List of acronyms Acronyms ADI AOPs ATSDR APs APEOs ARB ARGs BP3 BPA CCL DEET dl-PCBs DWEL DWTs EC ECs EDAhR EDCs

Term Acceptable Daily Intake Advanced Oxidation Processes Agency for Toxic Substances and Disease Registry Alkylphenols Alkylphenol Ethoxylates Antibiotic-Resistant Bacteria Antibiotic Resistance Genes Benzophenone-3 Bisphenol A Contaminant Candidate List N,N-Diethyl-m-Toluamide Dioxin-like PCBs Drinking Water Effect Level Drinking Water Treatment Plants European Commission Emerging Contaminants Aryl Hydrocarbon Receptor Endocrine Disrupting Compounds

Some organic compounds in potable water: the PFASs, EDCs and PPCPs issue 211 EFSA EHMC EQSs EU GAC HDWCs MEC 4MBC MTD MFO NP NPnEOs OC OP OPEOs PAHs PBDEs PBT PCBs PCDDs PCDFs PCPs PFAA PFASs PFBS PFCAs PFHxS PFNA PFOA PFOS PFSAs PNECs POPs PPCPs REACH SVHCs TDI UCMR US EPA VICH WFD WHO WWTPs

European Food Safety Agency 2-Ethyl-Hexyl-4-Trimethoxycinnamate Environmental Quality Standards European Union Granular Active Carbon Human Drinking Water Concentrations Measured Environmental Concentrations 4-Methyl-Benzilidine-Camphor Minimum Therapeutic Dose Mixed-Function Oxidase Nonylphenol Nonylphenols Ethoxylates Octocrylene Octylphenol Octylphenol Ethoxylates Polycyclic Aromatic Hydrocarbons Polybrominated Diphenyl Ethers Persistent, Bioaccumulative, and Toxic Polychlorinated Biphenyls Polychlorinated Dibenzo-p-Dioxins Polychlorinated Dibenzofurans Personal care Products Perfluoroalkyl Acid Poly- and Perfluoroalkyl Substances Perfluorobutane Sulfonate Perfluoroalkyl Carboxylic Acids Perfluorohexane Sulfonate Perfluorononanoic Acid Perfluorooctanoic Acid Perfluorooctane Sulfonate Perfluoroalkane Sulfonate Predicted No-Effect Concentrations Persistent Organic Pollutants Pharmaceuticals and Personal Care Products Registration, Evaluation, Authorization and Restriction of Chemicals Substances of Very High Concern Tolerable Daily Intake Unregulated Contaminants Monitoring Rule United States Environmental Protection Agency Veterinary International Conference on Harmonization guidance Water Framework Directive World Health Organization Wastewater Treatment Plants

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CHAPTER 7

Current nanocomposite membranes as a tool for organic compounds remediation in potable waters ˜oz1,2 Roberto Castro-Mun 1

Department of Sanitary Engineering, Faculty of Civil and Environmental Engineering, Gdansk University of Technology, Gdansk, Poland, 2Tecnologico de Monterrey, San Antonio Buenavista, Toluca de Lerdo, Mexico

7.1 Introduction Membrane technologies, microfiltration, ultrafiltration, nanofiltration, reverse osmosis (Cassano et al., 2018; Castro-Mun˜oz et al., 2016; Coday et al., 2014; Pichardo-Romero et al., 2020), pervaporation (Castro-Mun˜oz, 2020a; Galiano et al., 2019), membrane distillation (Gontarek-Castro et al., 2022; Wang et al., 2016), membrane bioreactors (Lay et al., 2010), membrane contactors (Klaassen et al., 2005), membrane crystallization (Pramanik et al., 2016), and membrane gas separation (Castro-Mun˜oz, Agrawal, et al., 2020; Castro-Mun˜oz, Ahmad, et al., 2020) are promising unit operations which satisfy the current requirements to carry out selective separations in different chemical, food, biotechnological, and environmental applications. Generally, such membrane-based technologies use a so-called membrane as the primary tool of separation. A typical membrane is defined as a permselective barrier that permits the separation of different molecules in a liquid or gas state according to their molecular weight, size, shape, and other physicochemical properties. To date, membranes are mainly manufactured using polymers, such as polyvinylidene fluoride (PVDF) (Ekambaram & Doraisamy, 2017), polyimide (Castro-Mun˜oz, Ahmad, et al., 2020; Castro-Mun˜oz, Fila et al., 2019), polyamide (Shen et al., 2016), poly(vinyl alcohol) (Castro-Mun˜oz, Buera-Gonza´lez et al., 2019), polyvinyl acetate (Majumdar et al., 2020), cellulose acetate (CA) (Martin-Gil et al., 2019), and biopolymers (such as chitosan, sodium alginate, poly lactic acid) (Castro-Mun˜oz, Gonza´lezValdez, et al., 2020; Galiano et al., 2018), to mention just a few. In general, polymeric membranes are today the most cost-effective for membrane processes due to their multiple advantages over ceramic ones, such as good selectivity, easy processability, and costeffectiveness (Favvas et al., 2018), while their main drawbacks are easy fouling, chemically Current Trends and Future Developments on (Bio-) Membranes. DOI: https://doi.org/10.1016/B978-0-12-824103-5.00003-6 © 2023 Elsevier Inc. All rights reserved.

229

230 Chapter 7 nonresistant, limited operating in terms of temperature and pressure, and short lifetime (Castro-Munoz, 2022). Additional enhancements to polymeric membranes also involve robustness to handle aggressive aeration and cleaning conditions. At this point, inorganic materials (such as carbon nanotubes, zeolites, silicas, graphene-based materials, metal organic frameworks, among others) tend to offer strong chemical cleaning, with the possibility of being sterilized, operating at high operating temperature (over 300 C) and chemical resistance, along with characteristic pore-structure stability and defined molecular sieving, and long lifetime (Bowen et al., 2004; Castro-Mun˜oz & Fı´la, 2018; Fard et al., 2018). Therefore, a current trend in membrane fabrication is the combination of inorganic (i.e., nanofillers) and organic materials (i.e., polymers) to generate nanocomposite membranes. In theory, nanocomposite membranes, together with the so-called mixed matrix membranes (MMM), are tailored to merge the features of both types of membranes (i.e., inorganic and polymeric) to substantially achieve a superior liquid separation performance (Ahmad et al., 2021; Castro-Munoz et al., 2018). In addition to this, the aim of a nanocomposite membrane is also focused on improving the physicochemical properties of the pristine materials, such as enhanced antifouling, and better mechanical, chemical, physical, and thermal characteristics. Depending on the types of filling materials, the composite membranes can also display bactericidal properties (Castro-Mun˜oz, 2020b) and enhanced heavy metal ion and pollutants removal (Castro-Mun˜oz, Gontarek, et al., 2020; Ursino et al., 2018) when dealing with water treatment and water disinfection approaches. Importantly, both applications are the main core researches of the nanocomposite membranes; this is due to the current global water scarcity (Manju & Sagar, 2017). It is known that conventional water resources in many regions are not sufficient in meeting the water quality requirements of growing populations, hence water reuse is growing in acceptance as a promising alternative to satisfy the water supply (Warsinger et al., 2018). Importantly, nanocomposite membranes have met the requirements to separate various organic molecules and pollutants from water. Hence, the objective of this chapter is to introduce and elucidate the recent developments (over the last 5-year period) in preparing nanocomposite membranes for the remediation of potable waters using membrane processes. A brief background in terms of membrane technologies used in water remediation is also given.

7.2 Background of membrane technologies used in water remediation As mentioned previously, membrane processes are categorized by the use of a semipermeable barrier (i.e., membrane) and a driving force implied in the membrane operation (CastroMun˜oz, Boczkaj, et al., 2020; Van Der Bruggen et al., 2003). Within the different membrane operations, the driving force can be categorized as a difference in pressure, temperature, concentration, and electric potential. In theory, the membrane operations driven by a pressure gradient, including micro, ultra (UF), and nanofiltration (NF) processes, have been the most

Current nanocomposite membranes as a tool for organic compounds remediation 231

Figure 7.1 Membrane-based processes, membrane’s pore sizes, molecular weight cut-off (MWCO) of the membranes, as well as molecular weight of compounds, solutes, and particles separated via membranes (Warsinger et al., 2018).

explored in terms of water filtration using nanocomposite membranes. For example, Fig. 7.1 shows the pore size range of such membranes. In principle, the pore size is the main parameter used to differentiate the aforementioned operations. Based on the membrane’s pore size, the membranes are able to separate various high- and low-molecular-weight solutes in water systems. Particularly, NF membranes offer the suitable characteristics for water softening, while tight UF membranes offer the ability in separating low-molecular-weight solutes (including sugars, phenolic compounds, flavonols, flavonones, secoiridoids, pectins, proteins, etc.). Typically, as the membrane’s pore sizes decreases, a higher driving force (i.e., pressure) will be needed (see Fig. 7.2). Fundamentally, the separation ability of any membrane operation strongly depends on the different operating parameters, such as pressure, temperature, feed flow rate, as well as the intrinsic properties of the resulting nanocomposite membrane. However, the physicochemical composition of water bulk solutions also determines the separation performance of a membrane. When dealing with the physicochemical composition of potable water, different volatile organic compounds, together with heavy metal ions (Joshi et al., 2020), and toxic substances produced by blue green algae and metabolites (Bla´ha et al., 2009) can be contained in water streams, such as benzene, toluene, xylene, dichloroethane, trichloroethylene,

232 Chapter 7

Figure 7.2 Graphical depiction of MF, UF, NF, and RO technologies in separating a wide variety of compounds from water (Liang et al., 2019).

tetrachloroethylene, 1,1,1-trichloroethane, and carbon tetrachloride (Wang et al., 2019), to mention just a few. For example, Table 7.1 lists some common volatile organic compounds contained in water areas and their guideline values to produce drinking water, as suggested by the World Health Organization (WHO). To produce drinking water, pressure-driven membrane techniques are fundamental in removing most of the common organic solutes presented in water. Fig. 7.2 displays a graphical depiction of the ability of NF and RO technologies for the purification of water for water treatment. Both technologies are suitable for rejecting specific submolecule organic compounds and divalent ions (Liang et al., 2019). To date, plenty of review papers on polymeric membranes have been documented in the literature. A general list of the most common polymeric materials used in membrane fabrication, together with their properties and advantages/disadvantages, is presented in Table 7.2. As can be seen, most of these materials possess feasible properties for water

Current nanocomposite membranes as a tool for organic compounds remediation 233 Table 7.1: Guideline values of volatile organic compounds for drinking water purposes according to WHO (Tsuchiya, 2010). Compound

Value (µg/L)

Remark

2 20 30 2000a

For excess risk of 1025

Chlorinated alkanes Carbon tetrachloride Dichloromethane 1,2-Dicholoroethane 1,1,1-Trichloroethane Chlorinate ethenes Vinyl chloride 1,1-Dicholoethene 1, 2-Dicholoethene Trichloroethene Tetrachloroethene Aromatic hydrocarbons Benzene Toluene Xylene Ethylbenzene Styrene Benzo(a)pyrene Chlorinated benzenes Monochlorobenzene 1, 2-Dichlorobenzene 1, 4- Dichlorobenzene Trichlorobenzenes Epichlorohydrin a

5 30 50 70a 40 10 700 500 300 20 0.7

For excess risk of 1025

For excess risk of 1025

300 1000 300 20 0.4a

Provisional guideline value.

purification; however, their weakness and disadvantages have led to improvement of their features by using inorganic nanomaterial blending. Therefore, the following section addresses the latest concepts of nanocomposite membranes based on previous polymers with the target of removing different organic compounds from water systems.

7.3 Recent developments in novel nanocomposite membrane for organic compounds and pollutants removal from water Over the last decade, the research community has been working in-depth on the developments of MMMs and nanocomposite membranes through the incorporation or coating of various inorganic nanomaterials. The embedding or coating of the inorganic material in a polymer phase depends fundamentally on the purpose and type of membrane concept as well as the fabrication procedure used. To sum up, Table 7.3 reports a number of studies dealing with the implementation of nanosized materials in polymer membranes for water treatment approaches using membrane operations, including reduced chemical

234 Chapter 7 Table 7.2: Common polymeric-based membranes employed in membrane technologies driven by a pressure difference for water treatment applications (Warsinger et al., 2018). Polymeric material

Membrane process used

Polysulfone (PSF)

MF/UF

Polyethersulfone (PES) Polyacrylonitrile (PAN) Polyvinylidiene fluoride (PVDF) Polyethylene (PE)

MF/UF

MF

Polypropylene (PP)

MF

Polyvinyl chloride (PVC)

MF/UF (occasionally)

Cellulose acetate (CA) Polyamide (PA)

MF/UF/RO

Renewable source

RO (as thin film composite) MF/UF (occasionally)/NF

Small pores, excellent rejection, selectivity

MF/UF MF/UF

Advantages

Disadvantages

Good mechanical strength Chemically resistant Rigid, compaction resistant, highly permeable, oxidant tolerant, narrow pore size distribution Very oxidant tolerant, chlorine resistant High resistance to organic solvents, low cost, oxidant tolerant High resistance to organic solvents, decent mechanical strength

Broader pore size distribution Poor thermal properties, Weaker fouling resistance Low fouling resistance, not oxidant tolerant Poor thermal stability, not oxidant tolerant Low permeability in RO Low permeability/ dense

oxygen demand, removal of heavy metal ions, salt removal, and water purification. It is important to highlight that the filling loading in such membranes is relatively low. Most of the studies attend to the removal of humic acid since it is well-known that humic substances, primarily humic acids, are the main fraction contained in natural organic matter (NOM) in water systems (Dobranskyte et al., 2006). The authors have paid great attention to removing such compounds since humic acids are based on aromatic and aliphatic groups, together with plenty of negatively charged carboxylic acid groups (Sauvant et al., 1999). Such a negative charge allows the formation of highly stable complexes with metal cations (Pandey et al., 2000). For example, copper is generally contained in freshwater bound to humic-based molecules, displaying a stability three orders of magnitude greater than complexes with the bicarbonate ion (CO32). Therefore, if humic acids are removed from the water, a great effect can be achieved for the removal of other substances. Very recently, Tizchang and coworkers developed polysulfone (PSF) membranes filled with chemically functionalized nanodiamond, in which the nonsolvent induced phase separation (NIPS) method was selected as the membrane preparation technique. The authors later tested them to remove humic acid from water (Tizchang et al., 2019). According to the authors, the use

Table 7.3: Reported mixed matrix and nanocomposite membranes using various nanosized materials for water treatment. Filling inorganic Membrane nanomaterial technology

Approach

Polymer

Filler loading

References

ZnO

UF

Removal of humic acid

PES

3.6 wt.%

UF

Removal of humic acid Removal of salt Evaluation of antifouling properties in composite membranes for water treatment. Mixture model: Bovine serum albumin Evaluation of antifouling properties in composite membranes for water treatment. Mixture model: Bovine serum albumin Removal of micelle from aqueous solutions Removal of pollutants sodium alginate, bovine serum albumin and humic acid Evaluation of antifouling properties in composite membranes for water treatment. Mixture model: Bovine serum albumin Evaluation of antifouling properties in composite membranes for water treatment. Mixture model: Bovine serum albumin Treatment of wastewater Bacterial removal from aqueous solutions Evaluation of antifouling properties in composite membranes for water treatment. Mixture model: Bovine serum albumin Removal of humic acid Water purification (removal of humic) Removal of salt and metal ions (Zn21, Cd21, Pb21, Mn21, Ni21, Fe21, Al31, Sb31, Sr31) Separation of Rhodamine B Removal of humic Removal of inorganic salts and humic

PSF PA PVDF

0.1 wt.% 0.003 0.009 g 1g

Ahmad, Abdulkarim et al. (2016) Chung et al. (2016) Ghoul et al. (2017) Jia et al. (2016)

PES

0.5 2 wt.%

Dipheko et al. (2017)

0 10 wt.% 0.25 0.75 wt.%

Jo et al. (2016) Li et al. (2015)

0.4 g

NF

Removal of humic acid Removal of salts (model MgSO4)

FO RO

Desalination and water treatment Removal of salt, bivalent ions (Ca21, SO422and Mg21), monovalent ions (Cl2 and Na1), and bacterial retention

PES-PVA

0.04 1.3 g

Escobar & Bruggen (2015) Zhao et al. (2015)

PSF PVC

0.1 1 wt.% 0.7 mg 3 wt.%

Pintilie et al. (2017) Ronen et al. (2013) Rabiee et al. (2015)

PES PVP CA

0.035 4 wt.% 100 mg 0.02 0.05 g

Balta et al. (2012) H. Bai et al. (2012) Bahadar et al. (2015)

CTA PSF PVDF

0.6 g 2 wt.% 0 0.2 wt.% 1 wt.% 1.5 wt.%

Akin and Ersoz (2017) Tao et al. (2017) Ekambaram and Doraisamy (2017) Li et al. (2017) Li et al. (2016)

0 8 wt.% 0.005 0.4 wt.%

Zhao et al. (2017) Isawi et al. (2016)

Poly (piperazine amide) PVDF PA

(Continued)

Table 7.3: (Continued) Filling inorganic Membrane nanomaterial technology

Approach

Polymer

Filler loading

References

GO

Treatment of effluents with high dyes content

PSF

0.75 2.5 wt.%

Filtration of wastewaters Evaluation of antifouling properties in composite membranes for water treatment Mixture model: Bovine serum albumin Evaluation of antifouling properties in composite membranes for water treatment Mixture model: Bovine serum albumin Evaluation of antifouling properties in composite membranes for water treatment Mixture model: Bovine serum albumin Natural organic matter removal Evaluation of antifouling properties in composite membranes for water treatment Mixture model: Bovine serum albumin Natural organic matter removal Wastewater treatment Degradation of organic pollutants in salty water

PVDF PSF

3 wt.% 0.025 0.15 wt.%

Badrinezhad and Ghasemi (2017) Zhao et al. (2014) Zhao et al. (2013) and Zhao, Xu, et al. (2013)

PVP-PVDF

0 0.50 wt.%

Chang et al. (2014)

PVDF

2.5 g/mL

Wu et al. (2014)

0.1 1 wt.% 0 2 wt.% 0.004 0.012 wt.% 0.02 0.39 wt.% 2 g/L

Xia et al. (2015) Zhao et al. (2013) and Zhao, Xu, et al. (2013) Xia et al. (2015) Lee et al. (2013) Mahmoudi et al. (2015)

0.5 1 wt.% 2000 ppm 5 mg/mL 0.05 0.5 wt.% 0.25 1 g/L 0.1 1 wt.% 100 400 mg/L 5 76 ppm 0.005 0.3 wt.% 100 300 ppm 1.5 wt.% 0.1 2 wt.% 0.864 µg/mL 0.5 wt.%

Kiran et al. (2016) Ganesh et al. (2013) Goh et al. (2015) Yang et al. (2017) Zhang, Wei et al. (2017) Zinadini et al. (2014) Wang, Zhao et al. (2016) Chae et al. (2015) He et al. (2015) Ali et al. (2016) Shen et al. (2016) Crock et al. (2013) Han et al. (2013) Zhang et al. (2012)

0 0.05 0.1 2.5 5 10 wt. %

Alpatova et al. (2013)

MF

UF

NF

RO

Graphene

FO UF NF UF

Cu nanoparticles Ag MF /UF nanoparticles

Treatment of distillery effluent Na2SO4 rejection from water streams Water softening production Treatment of effluents with high dyes content Treatment of solutions with high dyes content Evaluation of dye removal capacity for water treatment Water purification Desalination: Salt removal (NaCl) Desalination: Salt removal (NaCl, CaCl2, and Na2SO4) Desalination: Salt removal (NaCl) Possible prospect for desalination of sea water Wastewater treatment Water purification Evaluation of antifouling properties in composite membranes for water treatment. Mixture model: Bovine serum albumin Evaluation of antifouling properties in composite membranes for water treatment. Mixture model: Bovine serum albumin

PA PSF Cellulose ester PES PSF PAI-PEI PMIA PAN PES PPA PA PSF PA PSF PVDF PSF

UF

DCMD

PRO/RO

PRO

bio-Ag0

UF

NF

UF UF

NF

RO

Water purification Evaluation of antibacterial properties and removal of salt (NaCl). Model bacteria: Escherichia coli, Bacillus subtilis Evaluation of antibacterial properties Model bacteria: E. coli, B. subtilis

PES PA/PSF/PET

0 0.32 0.64 wt.% 4 g/L

Rehan et al. (2016) Yang et al. (2016)

PVDF

1 wt.%

Ahmad, Abdulkarim et al. (2016), Ahmad, Jamshed et al. (2016) Liao et al. (2013)

Deposition of silver nanoparticles layers to optimize surface roughness and enhance membrane hydrophobicity. Desalination of seawater. Model water: NaCl 3.5 wt.% Evaluation of antifouling and antibacterial properties in composite membranes for water treatment. Model bacteria: E. coli. Mixture model: Bovine serum albumin Evaluation of antifouling and antibacterial properties in composite membranes for water treatment. Model bacteria: E. coli, B. subtilis Mixture model: Comamonas testosteroni

PES

40 g/L

Zhang et al. (2013)

PAN

0.01 0.02 0.05 0.10 wt.%

Liu, Foo et al. (2016)

Evaluation of antifouling and antibacterial properties in composite membranes for water treatment. Model bacteria: E. coli, P. aeruginosa Evaluation of antibacterial properties and removal of salt (Na2SO4). Model bacteria: E. coli, Pseudomonas aeruginosa Evaluation of antibacterial properties and removal of salt (Na2SO4). Model bacteria: P. aeruginosa Evaluation of antifouling and antibacterial properties in composite membranes for water treatment. Model bacteria: P. putida. Mixture model: Bovine serum albumin Evaluation of antifouling and antibacterial properties in composite membranes for water treatment. Model bacteria: E. coli. Mixture model: Humic acid Treatment of wastewaters (sludge filtration) and evaluation of antifouling properties in composite membranes for water treatment. Mixture model: Bovine serum albumin Evaluation of antifouling and antibacterial properties in composite membranes for water treatment. Model bacteria: E. coli. Seawater softening, removal of salt (SO421, Mg21, Na1, Cl2). Evaluation of antibacterial properties in composite membranes for water treatment. Model bacteria: E. coli Evaluation of antibacterial properties and removal of salt (NaCl). Model bacteria: E. coli Evaluation of antifouling and antibacterial properties in composite membranes for water treatment. Model bacteria:

PES

0.1 0.3 0.5 1 wt.%

Zhang et al. (2014)

PA

0.1 mM 40 mL

Liu et al. (2015)

PSF

0.005 0.025 0.05 wt.%

Liu, Zhang et al. (2016)

3.6 g

Hoek et al. (2011)

PAN/PEI

1000 mg/L

Xu et al. (2012)

PES

0.002 0.01 0.03 0.05 wt. %

Akar et al. (2013)

PSF

3.2 g

Kar et al. (2011)

PAN/PEI

0 0.4 g

Xu et al. (2015)

PA

50 mM

Ben-Sasson et al. (2016)

30 mL

Zhang, Zhang et al. (2017)

CA

(Continued)

Table 7.3: (Continued) Filling inorganic Membrane nanomaterial technology

Approach

Polymer

Filler loading

References

50 mL

Ben-Sasson et al. (2014)

0.05 wt.% 0.1 g/L

Madaeni et al. (2011) Teow et al. (2012)

0.5 1 wt.%

Rajaeian et al. (2015)

0 0.15 0.3 0.45 1.5 3 6 wt.% 0 1.5 wt.% 0 7 wt.%

Shi et al. (2012)

E. coli. Mixture model: Bovine serum albumin

MF TiO2 nanoparticles UF

FO MF/ MBR

CNTs

MBR NF NF NF UF NF NF NF NF NF UF

Evaluation of antibacterial properties in composite membranes for water treatment and removal of salt (NaCl). Model bacteria: E. coli, P. aeruginosa, Staphylococcus aureus. Evaluation of antifouling properties using whey solution Evaluation of antifouling properties in composite membranes for water treatment. Mixture model: Humic acid Evaluation of antifouling properties in composite membranes for water treatment. Mixture model: PEG and MgSO4 Treatment of wastewaters Evaluation of UV-cleaning properties Evaluation of UV-cleaning and antifouling properties. Mixture model: BSA Evaluation of antifouling properties. Mixture model: BSA and Lys Evaluation of antifouling properties and removal of salt (NaCl). Mixture model: BSA and pepsin Water treatment Evaluation of UV-cleaning properties and antifouling properties. Mixture model: red dye and bovine serum albumin. Evaluation of removal of salt (NaCl). Evaluation of removal of salt (NaCl). Evaluation of antifouling properties. Mixture model: PEG and MgSO4 Algal membrane bioreactor evaluation Wastewater treatment application Evaluation of antifouling and removal of salts (NaCl, Na2SO4). Drinking-water purification Water treatment and biofouling control application Wastewater treatment application Water treatment Metal removal (Cr(VI), Cd(II)) Water treatment for salt removal (NaCl, Na2SO4). Evaluation of antifouling properties in composite membranes for water treatment. Water treatment for UF applications

PVDF

Ngang et al. (2012) Me´ricq et al. (2015)

PP PSF

0.1, 0.25 and 0.5 wt.%.

CA PA

0 25 wt.% 10 80 ppm

PSF

0.01, 0.05, and 0.1 wt./v% 0 0.5 0.75 0.99 wt.%

Amini et al. (2016) Emadzadeh et al. (2014) Moghadam et al. (2011)

PES PSF Nitrocelullose PES PES PA PSF PMMA Polyimide 84

5wt.% 0.125 g 5 wt.% 3 wt.% 0 4 wt.% 0.1 wt.% 5 wt.% 0.1 1 wt.% 0.67 wt.% 0.1 1 wt.%

Hu et al. (2015) Sotto et al. (2011) Kim et al. (2012) Ahmed et al. (2013) Celik et al. (2011) Daraei et al. (2013) Kim et al. (2013) Shah and Murthy. (2013) Shen et al. (2013) Grosso et al. (2014)

PSF

0.1 0.5 wt.%

Sianipar et al. (2016)

PVDF

Pi et al. (2016) Mollahosseini and Rahimpour. (2014) Abedini et al. (2011) Ngo et al. (2016)

Current nanocomposite membranes as a tool for organic compounds remediation 239 of 1 wt.% of the inorganic material enhanced different properties in the obtained composites, such as hydrophilicity, porosity, and water flux; this latest property was enhanced up to 905 kg/m2 h. In general, all composite formulations, containing 0.5 1.5 wt.% nanodiamond loading, showed an exceptional humic acid rejection of over 96%. Importantly, the reduced contact angle by incorporating the nanodiamond phase can be interpreted as an enhancement of the hydrophilic nature of the membranes. From the operation point of view, this is beneficial since the membranes tend to suffer less from the fouling phenomenon. In fact, it is documented that hydrophilic membranes are less prone to biofouling compared to hydrophobic membranes (Castro-Mun˜oz, 2019; Ursino et al., 2018). Similarly, Etemadi et al. (2017) also created CA/nanodiamond membranes for water treatment. Unlike Tizchang’s study, Etemadi and coworkers obtained less water permeation flux (up to 120 L/m2 h) in CA/ND-COOH membranes (containing 0.5 wt.%) than nanodiamond/PSF membranes with 1 wt.%. These particular membranes correspond to the ones which were functionalized using heat treatment. Despite this permeation rate, the CA/ND-COOH membranes loaded with 0.5 wt.% provided a humic acid rejection rate of over 99%. Cheshomi et al. (2018) have prepared and fully characterized hybrid TiO2/Pebax/(PSF-PES) thin-film nanocomposite membranes. When using 0.03 and 0.01 wt.% TiO2 loadings, the composites demonstrated 98% and 99% humic acid rejection, respectively. Moreover, the authors found out that humic acid rejection was improved from 96% to 99% by increasing the feed concentration from 10 to 30 ppm. The study also proved that the hydrophilic properties and membrane roughness were enhanced by embedding the TiO2 nanoparticles. Differently, Shawky et al. (2011) synthesized multiwall carbon nanotube (MWCNT) and subsequently merged them into aromatic polyamide (PA) polymer membranes for humic acid removal. Today, there is a great interest in using 2D materials in polymer membranes due to the fact that they can confer excellent water permeability and chemical resistance to the membranes (Safaei et al., 2020). At this point, Shawky and coworkers indicated that the resulting composite membranes displayed an enhanced rejection rate towards salt and organic matter in comparison with pristine unfilled membrane, for example, the composite filled with 15 mg/g MWCNT in a 10% PA membrane removed NaCl and humic acid by factors in the order of 3.17 and 1.67, respectively, while the permeability loss was about 6.5%. As mentioned previously, another important aspect of the interest in nanocomposite membranes relies on their capacity to eliminate metal ions from contaminated water (Joshi et al., 2020; Qdais & Moussa, 2004). Recently, Castro-Mun˜oz et al. have reviewed the progress and latest breakthroughs in the field of novel nanocomposite membrane fabrications for heavy metal uptake, including new composite materials that have not been implemented in membranes but are promising candidates in the field due to their tremendous metal ions adsorption capacity (Castro-Mun˜oz et al., 2021). Thanks to the enhanced adsorption capacity given by inorganic materials, composite membranes can offer 100% removal of heavy metals, along with

240 Chapter 7 unprecedented permeation rates (from 80 up to 1300 L/m2 h). As a recent development work, a rejection of up to 98% for cadmium (Cd21) was reported by Ounifi et al. (2020), who utilized CA NF membranes. Such results were obtained after testing the membranes for the filtration of three kinds of cadmium salts, including CdCl2, Cd(NO3)2, and CdSO4. Using the same polymer (i.e., CA), Sabeti Dehkordi et al. (2015) evaluated the influence of filling organically modified montmorillonite (OMMt) into the polymer. The outcomes showed that the pure water permeation rate was meaningfully raised from 3.8 3 1025 to 6.6 3 1025 m3/m2
s by varying OMMt loading from 0 to 5 wt.%. By raising the OMMt loading, the rejection minimally decreased from 94% in pristine CA membrane to 92% in OMMt/CA nanocomposite membrane filled with 2 wt.%; the highest rejection (ca. 95%) was seen in the 5 wt.% OMMt/CA formulation. Lately, exfoliated molybdenum disulfide (eMoS2) nanosheets were proposed for enhancing the permeability and antifouling features of poly(ether imide) UF membranes (Saraswathi et al., 2018). After testing, the composite membrane (with 1 wt.% eMoS2) exhibited an increased pure water permeation of 52 L/m2 h and water content (ca. 74.8%), together with hydraulic resistance (1.85 kPa/L m2 h). Resistance to fouling performance of such a membrane formulation was obvious from the flux recovery ratio values of 95.3% and 90.2%, while the rejection values were 94.5% and 92.4% for bovine serum albumin and humic acid, respectively. Based on the author’s concluding remarks, among all the prepared membrane formulations, the one containing 1 wt.% eMoS2 possessed the best hydrophilicity and antifouling properties, which were attributed to the favorable surface and bulk features (Saraswathi et al., 2018). As a current trend in nanocomposite fabrication, scientists have initiated the incorporation of more than one inorganic phase into the polymer phase to generate hybrid nanocomposites. This is the case documented by Kumar et al. (2016), who fabricated a hybrid material based on graphene oxide (GO) and TiO2 synthesized using in situ sol gel reaction, as illustrated in Fig. 7.3A. In this study, the authors strategically used GO nanosheets dissolution and titanium isopropoxide precursor; once the synthesis was successfully performed, the generated composite was subsequently embedded into PSF to prepare UF membranes. According to the author’s analysis, GO TiO2 composite was strongly entrapped into the polymer phase thanks to the hydrogen bonding interactions among the O5S5O groups (present in PSF) and the COOH groups in GO TiO2 (see Fig. 7.3B). Due to the NIPS preparation protocol, the membranes displayed an asymmetric structure, enhanced surface roughness, and hydrophilic nature. When filtrating 10 ppm of humic acid aqueous solutions, the water permeation and antifouling capacity in resulting composite membranes were found to be dependent on the GO TiO2 loading content from 1 to 2 wt.%. Interestingly, the nanocomposite membranes presenting 2 wt.% of composite exhibited a water permeation up

Current nanocomposite membranes as a tool for organic compounds remediation 241

Figure 7.3 (A) Synthesis route of GO-TiO2 composite by means of sol gel reaction (at pH 5 2, 60 C); (B) interaction between PSF polymer and the composite (Kumar et al., 2016).

to 135 L/m2 h from 105 L/m2 h determined in the unfilled polymer membrane. Besides, the nanocomposite membranes exhibited a better antifouling profile for humic acid solutions; this allowed irreversible humic acid fouling mitigation, and it was further reduced by increasing the composite loading. In a different approach, Mahmoudi et al. (2015) once again proposed PSF as a continuous phase to incorporate a composite obtained by combining silver (Ag) nanoparticles on GO nanoplates (named as Ag-decorated GO). The hydrophilicity, pure water flux, and rejection have been improved by incorporating nanohybrid material. By varying the Ag-decorated GO concentration (between 0.1 and 1 wt.%), the formulation filled with 0.5 wt.% was found to be optimum, showing a lower contact angle (ca. 58 degrees) together with higher water permeation (around 59 L/m2 h) and porosity (over 60%). In addition, this membrane also presented high bovine serum albumin rejection (over 80%). The nanohybrid membranes also presented excellent antibacterial characteristics (against Gram-negative bacteria Escherichia coli), this could contribute to mitigate the biofouling as well. Very recently, Chai and coworkers also decorated GO with

242 Chapter 7 iron oxide (Fe3O4) and thus utilized it to prepare Fe3O4/GO-PSF MMMs (Chai et al., 2020). In this study, Fe3O4/GO amount was evaluated from 0 to 1 wt.%, analyzing porosity, pore size, contact angle, water flux, and Congo red rejection, among other properties. It was concluded that the composite, loaded with 0.6 wt.% Fe3O4/GO, exhibited modified hydrophilicity which increased by 11.42%, from 78.8 to 69.8 , associated with the filling hydrophilic hybrid material. This can give an idea that such resulting material can facilitate the permeation of water molecules across the membrane. The same composite membrane also demonstrated higher permeation flux (ca. 87 L/m2 h) and Congo red rejection (of about 98%) than the pristine membrane, having a permeation of 52 L/m2 h and 87% rejection. Considering the hydrophilicity obtained in the composite membrane, the authors also noted improved antifouling at a high flux recovery ratio of 95%, from 87% in the unfilled membrane. Furthermore, the 0.6 wt.% Fe3O4/GO membrane offered better stability in longterm testing over 120 min, observing a lower flux decline at 23% when compared with the pristine membrane at 41%. The production of nanocomposite membranes using more than one dispersing phase (i.e., filler) may offer the possibility of performing the simultaneous removal of several polluting compounds at once. This was documented by Mahmoudi et al. (2020). Herein, the researchers carried out the simultaneous elimination of Congo red and a heavy metal ion, like cadmium(II), from aqueous model solutions via GO silica composite. At this point, the nanohybrid material was only assayed as a multifunctional adsorbent, showing an adsorbent capacity for the efficient separation of Cd(II) and Congo red of about 43.45 and 333.33 mg/g, respectively. As a conclusion, the authors highlighted the potential of such a hybrid nanocomposite to control water pollution and the removal of hazardous species. Also, according to the relevant insights, such a composite could be implemented in membranes and thus in membrane processes to evaluate its potentiality in filtration systems. To mitigate the fouling provoked by NOM, cellulose nanocrystals (CNCs) have been embedded into another hydrophobic polymer, such as polyethersulfone (PES) (Bai et al., 2020). Initially, the porosity and zeta potential of nanocomposite membranes were higher than pristine PES membranes. Within the filtration of water systems, different water pollutants were considered, including humic acid, bovine serum albumin, and sodium alginate. The removal rates of both hydrophobic humic acid and bovine serum albumin were significantly increased by the developed membranes. The CNC loading was varied from 0.3 to 5 wt.% in nanocomposite membranes. Particularly, the membranes, having 2 wt.% CNC, revealed the maximum water permeability (ca. 485 L m2 h/bar) with 72% overall porosity. In terms of pure water fluxes, this membrane formulation offered about 291 L/m2 h (at pressure 60 kPa). The NOM removal (over 80%) was unchanged in composites in comparison to the pristine PES membrane, while the bovine serum albumin increased as a function of CNC loading, for example, B90% NOM removal in 2 wt.% CNC composite from B70% in unfilled PES membrane. However, the greater changes were obtained during the removal of humic acid; for

Current nanocomposite membranes as a tool for organic compounds remediation 243 instance, a humic removal of 70% was documented by incorporating the nanocrystals from 30% obtained in the pristine membrane. Additionally, the nanocomposite membranes also displayed better anti-NOM fouling properties, together with enhanced cleaning efficiency and efficient control for fouling (reversible and irreversible) (Bai et al., 2020). In the light of more efficient composites for contaminated water treatment, Zhang et al. (2020) have proposed the preparation of polydopamine-coated ferroferric oxide (Fe3O4@PDA) nanoparticles in PES polymer. The synthesized filler (i.e., Fe3O4@PDA) was proposed for the simultaneous degradation of organic contaminants (methylene blue) and adsorption of heavy metal ions (Pb21). In general, the permeation rates of the resulting composite were strongly enhanced by adding the hybrid filler since the hydrophilic property of the Fe3O4@PDA allowed production of a microporous structure between the polymer and the filler. Experimentally, the composite containing 20 wt.% Fe3O4@PDA showed high water permeation of 2,640 L/m2 h bar; such a value was six times higher than that of PES unfilled membrane. The composites demonstrated an efficient performance with excellent reproducibility for the adsorptive removal of Pb21 from 80% to 100%. Importantly, the hybrid filler presented a negatively charged surface that is suitable to adsorb cations. Furthermore, the functional groups on the surfaces of Fe3O4@PDA are able to chelate metal ions (Ye et al., 2011). At this point, PDA has been recognized for its binding to various multivalent metal ions, including Fe31, Mn21, Zn21, Cu21, among others. The metal ion bonding is associated with plenty of functional groups in PDA, such as o-quinone, carboxy, amino, imine, and phenol groups (Liu et al., 2014). Regarding the degradation of pollutants, catalytic degradation based on the mechanism of Fenton-like reaction was provided by the Fe3O4@PDA. This new composite with multifunction tasks in terms of catalytic degradation and adsorption opens the possibility to strategically synthesize synergistic materials. According to Zhang’s conclusion, these composite membranes could be involved in the treatment of specific wastewaters derived from papermaking, leather, and textile printing/dyeing industries.

7.4 Conclusion and future trends By reviewing the current research, polymeric membranes (such as CA, PES, PSF, PVDF, etc.) implemented in membrane processes have demonstrated their ability to remove organic compounds and pollutants (humic-based substances, metal ions, NOM, etc.) from water systems. Fortunately, both embedding and coating of inorganic materials into polymer have allowed the fabrication of the next generation of membranes, the so-called “nanocomposites.” Due to the high adsorption capacities and features of the inorganic nanoparticles, nanocomposites offer substantially enhanced removal rates for such compounds. To date, the embedding of nanosized filling materials (including silver, zinc, copper nanoparticles, GO, TiO2, carbon nanotubes, among other interesting materials) has

244 Chapter 7 been deeply explored, obtaining great advances in the field of water treatment. It is likely that new composite materials, such as the combination of more than one inorganic phase (e.g., metal-decorated GO), will be explored in the near future. The smart merging of more than one filler is allowing the simultaneous removal of several molecules and pollutants species from water. As a perspective in the field, the chemical functionalization of nanostructured particles is a promising way of improving the adsorption capacity of the hybrid materials together with enhanced compatibility with polymer phases. For example, deep eutectic solvents (DES) are today proposed for the functionalization of different nanoparticles (Hayyan et al., 2015; Ojala et al., 2018; Shaabani & Afshari, 2018). Very recently, the functionalization of CNT with DES based on tetra-n-butyl-ammonium-bromide has resulted in enhanced adsorption efficiency in the produced chemically functionalized CNT (Rahmati et al., 2021). Also, composite membranes offer the possibility to perform the simultaneous degradation of contaminants and adsorption of metal ions (Zhang et al., 2020). In this way, the ongoing research has a clear target of the purification of drinking water by means of strategically new composites.

Acknowledgments R. Castro-Mun˜oz acknowledges the financial support from Polish National Agency for Academic Exchange (NAWA) under Ulam Programme (Agreement No. PPN/ULM/2020/1/00005/U/00001).

List of acronyms CA CNC CTA DES eMoS2 GO MF MWCNT MWCO NF NIPS NOM OMMt PA PAN PDA PE PEI PES PET PMMA

cellulose acetate nanocrystals cellulose triacetate deep eutectic solvent exfoliated molybdenum disulfide graphene oxide microfiltration multi-wall carbon nanotube molecular weight cut-off nanofiltration non-solvent induced phase separation natural organic matter organically modified montmorillonite aromatic polyamide polyacrylonitrile polydopamine polyethylene poly(ether imide) polyethersulfone polyester poly(methyl methacrylate)

Current nanocomposite membranes as a tool for organic compounds remediation 245 PP PSF PVA PVC PVDF RO UF

polypropylene polysulfone poly(vinyl alcohol) polyvinyl chloride polyvinylidene fluoride reverse osmosis ultrafiltration

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Current nanocomposite membranes as a tool for organic compounds remediation 251 Mollahosseini, A., & Rahimpour, A. (2014). Interfacially polymerized thin film nanofiltration membranes on TiO2 coated polysulfone substrate. Journal of Industrial and Engineering Chemistry, 20(4), 1261 1268. Available from https://doi.org/10.1016/j.jiec.2013.07.002. Ngang, H. P., Ooi, B. S., Ahmad, A. L., & Lai, S. O. (2012). Preparation of PVDF-TiO2 mixed-matrix membrane and its evaluation on dye adsorption and UV-cleaning properties. Chemical Engineering Journal, 197, 359 367. Available from https://doi.org/10.1016/j.cej.2012.05.050. Ngo, T. H. A., Nguyen, D. T., Do, K. D., Minh Nguyen, T. T., Mori, S., & Tran, D. T. (2016). Surface modification of polyamide thin film composite membrane by coating of titanium dioxide nanoparticles. Journal of Science: Advanced Materials and Devices, 1(4), 468 475. Available from https://doi.org/ 10.1016/j.jsamd.2016.10.002. ¨ sterberg, M., Sirvio¨, J. A., & Liimatainen, H. (2018). Emulsion Ojala, J., Visanko, M., Laitinen, O., O stabilization with functionalized cellulose nanoparticles fabricated using deep eutectic solvents. Molecules, 23(11). Available from https://doi.org/10.3390/molecules23112765. Ounifi, I., Ursino, C., Santoro, S., Chekir, J., Hafiane, A., Figoli, A., & Ferjani, E. (2020). Cellulose acetate nanofiltration membranes for cadmium remediation. Journal of Membrane Science and Research, 6(2), 226 234. Available from https://doi.org/10.22079/JMSR.2020.120669.1336. Pandey, A. K., Pandey, S. D., & Misra, V. (2000). Stability constants of metal-humic acid complexes and its role in environmental detoxification. Ecotoxicology and Environmental Safety, 47(2), 195 200. Available from https://doi.org/10.1006/eesa.2000.1947. Pi, J. K., Yang, H. C., Wan, L. S., Wu, J., & Xu, Z. K. (2016). Polypropylene microfiltration membranes modified with TiO2 nanoparticles for surface wettability and antifouling property. Journal of Membrane Science, 500, 8 15. Available from https://doi.org/10.1016/j.memsci.2015.11.014. Pichardo-Romero, D., Garcia-Arce, Z. P., Zavala-Ramirez, A., & Castro-Mun˜oz, R. (2020). Current advances in biofouling mitigation in membranes for water treatment: An overview. Processes, 8, 182. Pintilie, S.C., Tiron, L.G., Birsan, I.G., Ganea, D., & Balta, S. (2017). Influence of ZnO nanoparticle size and concentration on the polysulfone membrane performance, 30 32. Pramanik, B. K., Thangavadivel, K., Shu, L., & Jegatheesan, V. (2016). A critical review of membrane crystallization for the purification of water and recovery of minerals. Reviews in Environmental Science and Biotechnology, 15(3), 411 439. Available from https://doi.org/10.1007/s11157-016-9403-0. Qdais, H. A., & Moussa, H. (2004). Removal of heavy metals from wastewater by membrane processes: A comparative study. Desalination, 164(2), 105 110. Available from https://doi.org/10.1016/S0011-9164(04) 00169-9. Rabiee, H., Vatanpour, V., Hossein, M., Abadi, D., & Zarrabi, H. (2015). Improvement in flux and antifouling properties of PVC ultrafiltration membranes by incorporation of zinc oxide (ZnO) nanoparticles. Separation and Purification Technology, 156, 299 310. Available from https://doi.org/10.1016/j. seppur.2015.10.015. Rahmati, N., Rahimnejad, M., Pourali, M., & Muallah, S. K. (2021). Effective removal of nickel ions from aqueous solution using multi-wall carbon nanotube functionalized by glycerol-based deep eutectic solvent. Colloid and Interface Science Communications, 40(December 2020), 100347. Available from https://doi. org/10.1016/j.colcom.2020.100347. Rajaeian, B., Heitz, A., Tade, M. O., & Liu, S. (2015). Improved separation and antifouling performance of PVA thin film nanocomposite membranes incorporated with carboxylated TiO2 nanoparticles. Journal of Membrane Science, 485, 48 59. Available from https://doi.org/10.1016/j.memsci.2015.03.009. Rehan, Z. A., Gzara, L., Khan, S. B., Alamry, K. A., El-Shahawi, M. S., & M. H. A. (2016). Synthesis and characterization of silver nanoparticles-filled polyethersulfone membranes for antibacterial and antibiofouling application. Recent Patents on Nanotechnology, 10, 1 21. Ronen, A., Semiat, R., & Dosoretz, C. G. (2013). Impact of ZnO embedded feed spacer on biofilm development in membrane systems. Water Research, 47(17), 6628 6638. Available from https://doi.org/10.1016/j. watres.2013.08.036.

252 Chapter 7 Sabeti Dehkordi, F., Pakizeh, M., & Namvar-Mahboub, M. (2015). Properties and ultrafiltration efficiency of cellulose acetate/organically modified Mt (CA/OMMt) nanocomposite membrane for humic acid removal. Applied Clay Science, 105 106, 178 185. Available from https://doi.org/10.1016/j.clay.2014.11.042. Safaei, J., Xiong, P., & Wang, G. (2020). Progress and prospects of two-dimensional materials for membranebased water desalination. Materials Today Advances, 8, 100108. Available from https://doi.org/10.1016/j. mtadv.2020.100108. Saraswathi, M. S. S. A., Rana, D., Nagendran, A., & Alwarappan, S. (2018). Custom-made PEI/exfoliated-MoS2 nanocomposite ultrafiltration membranes for separation of bovine serum albumin and humic acid. Materials Science and Engineering C, 83(October 2017), 108 114. Available from https://doi.org/10.1016/ j.msec.2017.11.015. Sauvant, M. P., Pepin, D., & Guillot, J. (1999). Effects of humic substances and phenolic compounds on the in vitro toxicity of aluminium. Ecotoxicology and Environmental Safety, 44(1), 47 55. Available from https://doi.org/10.1006/eesa.1999.1799. Shaabani, A., & Afshari, R. (2018). Magnetic Ugi-functionalized graphene oxide complexed with copper nanoparticles: Efficient catalyst toward Ullman coupling reaction in deep eutectic solvents. Journal of Colloid and Interface Science, 510, 384 394. Available from https://doi.org/10.1016/j.jcis.2017.09.089. Shah, P., & Murthy, C. N. (2013). Studies on the porosity control of MWCNT/polysulfone composite membrane and its effect on metal removal. Journal of Membrane Science, 437, 90 98. Available from https://doi.org/ 10.1016/j.memsci.2013.02.042. Shawky, H. A., Chae, S. R., Lin, S., & Wiesner, M. R. (2011). Synthesis and characterization of a carbon nanotube/polymer nanocomposite membrane for water treatment. Desalination, 272(1 3), 46 50. Available from https://doi.org/10.1016/j.desal.2010.12.051. Shen, J. N., Yu, C. C., Ruan, H. M., Gao, C. J., & Van der Bruggen, B. (2013). Preparation and characterization of thin-film nanocomposite membranes embedded with poly(methyl methacrylate) hydrophobic modified multiwalled carbon nanotubes by interfacial polymerization. Journal of Membrane Science, 442, 18 26. Available from https://doi.org/10.1016/j.memsci.2013.04.018. Shen, L., Xiong, S., & Wang, Y. (2016). Graphene oxide incorporated thin- film composite membranes for forward osmosis applications. Chemical Engineering Science, 143, 194 205. Available from https://doi. org/10.1016/j.ces.2015.12.029. Shi, F., Ma, Y., Ma, J., Wang, P., & Sun, W. (2012). Preparation and characterization of PVDF/TiO2 hybrid membranes with different dosage of nano-TiO2. Journal of Membrane Science, 389, 522 531. Available from https://doi.org/10.1016/j.memsci.2011.11.022. Sianipar, M., Kim, S. H., Min, C., Tijing, L. D., & Shon, H. K. (2016). Potential and performance of a polydopamine-coated multiwalled carbon nanotube/polysulfone nanocomposite membrane for ultrafiltration application. Journal of Industrial and Engineering Chemistry, 34, 364 373. Available from https://doi.org/ 10.1016/j.jiec.2015.11.025. Sotto, A., Boromand, A., Balta, S., Kim, J., & Van der Bruggen, B. (2011). Doping of polyethersulfone nanofiltration membranes: Antifouling effect observed at ultralow concentrations of TiO2 nanoparticles. Journal of Materials Chemistry, 21, 10311. Available from https://doi.org/10.1039/c1jm11040c. Tao, Y., Mahmoudi, E., Wahab, A., Benamor, A., Johnson, D., & Hilal, N. (2017). Development of polysulfone-nanohybrid membranes using ZnO-GO composite for enhanced antifouling and antibacterial control. DES, 402, 123 132. Available from https://doi.org/10.1016/j.desal.2016.09.030. Teow, Y. H., Ooi, B. S., Ahmad, A. L., & Lim, J. K. (2012). Mixed-matrix membrane for humic acid removal: Influence of different types of TiO2 on membrane morphology and performance. International Journal of Chemical Engineering and Applications, 3(6), 374 379. Available from https://doi.org/10.7763/IJCEA.2012. V3.222. Tizchang, A., Jafarzadeh, Y., Yegani, R., & Shokri, E. (2019). Polysulfone nanocomposite membrane embedded by silanized nanodiamond for removal of humic acid from water. Journal of Water and Environmental Nanotechnology, 4(3), 213 226. Available from https://doi.org/10.22090/JWENT.2019.03.004.

Current nanocomposite membranes as a tool for organic compounds remediation 253 Tsuchiya, Y. (2010). Organical chemicals as contaminants of water bodies and drinking water. Water Quality and Standards, II, 150 171. Ursino, C., Castro-Mun˜oz, R., Drioli, E., Gzara, L., Albeirutty, M., & Figoli, A. (2018). Progress of nanocomposite membranes for water treatment. Membranes, 8(2), 18. Available from https://doi.org/ 10.3390/membranes8020018. Van Der Bruggen, B., Vandecasteele, C., Van Gestel, T., Doyen, W., & Leysen, R. (2003). A review of pressure-driven membrane processes in wastewater treatment and drinking water production. Environmental Progress, 22(1), 46 56. Available from https://doi.org/10.1002/ep.670220116. Wang, J., Zhao, C., Wang, T., Wu, Z., & Li, J. (2016). Nano filtration membrane for improving flux and antifouling in water purification. RSC Advances, 82174 82185. https://doi.org/10.1039/C6RA17284A. Wang, Q., Li, N., Bolto, B., Hoang, M., & Xie, Z. (2016). Desalination by pervaporation: A review. Desalination, 387, 46 60. Available from https://doi.org/10.1016/j.desal.2016.02.036. Wang, Y., Yu, R., & Zhu, G. (2019). Evaluation of physicochemical characteristics in drinking water sources emphasized on fluoride: A case study of Yancheng, China. International Journal of Environmental Research and Public Health, 16(6), 1 16. Available from https://doi.org/10.3390/ijerph16061030. Warsinger, D. M., Chakraborty, S., Tow, E. W., Plumlee, M. H., Bellona, C., Loutatidou, S., Karimi, L., Mikelonis, A. M., Achilli, A., Ghassemi, A., Padhye, L. P., Snyder, S. A., Curcio, S., Vecitis, C. D., Arafat, H. A., & Lienhard, J. H. (2018). A review of polymeric membranes and processes for potable water reuse. Progress in Polymer Science, 81, 209 237. Available from https://doi.org/10.1016/j.progpolymsci.2018.01.004. Wu, T., Zhou, B., Zhu, T., Shi, J., Xu, Z., Hu, C., & Wang, J. (2014). Facile and low-cost approach towards a PVDF ultra fi ltration membrane with enhanced hydrophilicity and antifouling performance via. RSC Advances, 5, 7880 7889. Available from https://doi.org/10.1039/C4RA13476A. Xia, S., Yao, L., Zhao, Y., Li, N., & Zheng, Y. (2015). Preparation of graphene oxide modified polyamide thin film composite membranes with improved hydrophilicity for natural organic matter removal. Chemical Engineering Journal, 280, 720 727. Available from https://doi.org/10.1016/j.cej.2015.06.063. Xu, J., Feng, X., Chen, P., & Gao, C. (2012). Development of an antibacterial copper (II)-chelated polyacrylonitrile ultrafiltration membrane. Journal of Membrane Science, 413 414, 62 69. Available from https://doi.org/10.1016/j.memsci.2012.04.004. Xu, J., Zhang, L., Gao, X., Bie, H., Fu, Y., & Gao, C. (2015). Constructing antimicrobial membrane surfaces with polycation-copper(II) complex assembly for efficient seawater softening treatment. Journal of Membrane Science, 491, 28 36. Available from https://doi.org/10.1016/j.memsci.2015.05.017. Yang, M., Zhao, C., Zhang, S., Li, P., & Hou, D. (2017). Preparation of graphene oxide modified poly (m-phenylene isophthalamide) nanofiltration membrane with improved water flux and antifouling property. Applied Surface Science, 394, 149 159. Available from https://doi.org/10.1016/j.apsusc.2016.10.069. Yang, Z., Wu, Y., Wang, J., Cao, B., & Tang, C. Y. (2016). In situ reduction of silver by polydopamine: A novel antimicrobial modification of a thin-film composite polyamide membrane. Environmental Science and Technology, 50(17), 9543 9550. Available from https://doi.org/10.1021/acs.est.6b01867. Ye, Q., Zhou, F., & Liu, W. (2011). Bioinspired catecholic chemistry for surface modification. Chemical Society Reviews, 40(7), 4244 4258. Available from https://doi.org/10.1039/c1cs15026j. Zhang, A., Zhang, Y., Pan, G., Xu, J., Yan, H., & Liu, Y. (2017). In situ formation of copper nanoparticles in carboxylated chitosan layer: Preparation and characterization of surface modified TFC membrane with protein fouling resistance and long-lasting antibacterial properties. Separation and Purification Technology, 176, 164 172. Available from https://doi.org/10.1016/j.seppur.2016.12.006. Zhang, C., Wei, K., Zhang, W., Bai, Y., Sun, Y., & Gu, J. (2017). Graphene oxide quantum dots incorporated into a thin film nanocomposite membrane with high flux and antifouling properties for low-pressure nano filtration. https://doi.org/10.1021/acsami.6b12826. Zhang, L. P., Liu, Z., Zhou, X. L., Zhang, C., Cai, Q. W., Xie, R., Ju, X. J., Wang, W., Faraj, Y., & Chu, L. Y. (2020). Novel composite membranes for simultaneous catalytic degradation of organic contaminants and adsorption of heavy metal ions. Separation and Purification Technology, 237(August 2019), 116364. Available from https://doi.org/10.1016/j.seppur.2019.116364.

254 Chapter 7 Zhang, M., Field, R. W., & Zhang, K. (2014). Biogenic silver nanocomposite polyethersulfone UF membranes with antifouling properties. Journal of Membrane Science, 471, 274 284. Available from https://doi.org/ 10.1016/j.memsci.2014.08.021. Zhang, M., Zhang, K., De Gusseme, B., & Verstraete, W. (2012). Biogenic silver nanoparticles (bio-Ag 0) decrease biofouling of bio-Ag 0/PES nanocomposite membranes. Water Research, 46(7), 2077 2087. Available from https://doi.org/10.1016/j.watres.2012.01.015. Zhang, S., Qiu, G., Ting, Y. P., & Chung, T. S. (2013). Silver-PEGylated dendrimer nanocomposite coating for anti-fouling thin film composite membranes for water treatment. Colloids and Surfaces A: Physicochemical and Engineering Aspects, 436, 207 214. Available from https://doi.org/10.1016/j. colsurfa.2013.06.027. Zhao., et al. (2013). Improving the antifouling property of polysulfone ultrafiltration membrane by incorporation of isocyanate-treated graphene oxide. Physical Chemistry Chemical Physics, 15, 9084 9092. Zhao, C., Xu, X., Chen, J., & Yang, F. (2013). Journal of Environmental Chemical Engineering Effect of graphene oxide concentration on the morphologies and antifouling properties of PVDF ultrafiltration membranes. Biochemical Pharmacology, 1(3), 349 354. Available from https://doi.org/10.1016/j. jece.2013.05.014. Zhao, C., Xu, X., Chen, J., & Yang, F. (2014). Optimization of preparation conditions of poly (vinylidene fl uoride)/ graphene oxide micro fi ltration membranes by the Taguchi experimental design. DES, 334(1), 17 22. Available from https://doi.org/10.1016/j.desal.2013.07.011. Zhao, S., Yan, W., Shi, M., Wang, Z., & Wang, J. (2015). Improving permeability and antifouling performance of polyethersulfone ultra fi ltration membrane by incorporation of ZnO-DMF dispersion containing nanoZnO and polyvinylpyrrolidone. Journal of Membrane Science, 478, 105 116. Available from https://doi. org/10.1016/j.memsci.2014.12.050. Zhao, X., Li, J., & Liu, C. (2017). Improving the separation performance of the forward osmosis membrane based on the etched microstructure of the supporting layer. Desalination, 408, 102 109. Available from https://doi.org/10.1016/j.desal.2017.01.021. Zinadini, S., Akbar, A., Rahimi, M., & Vatanpour, V. (2014). Preparation of a novel antifouling mixed matrix PES membrane by embedding graphene oxide nanoplates. Journal of Membrane Science, 453, 292 301. Available from https://doi.org/10.1016/j.memsci.2013.10.070.

Further reading Jia, H., Wu, Z., & Liu, N. (2016). Effect of nano-ZnO with different particle size on the performance of PVDF composite membrane. Plastics, Rubber and Composites, 8011(December). Available from https://doi.org/ 10.1080/14658011.2016.1245032. Escobar, I.C., Bruggen, B. (n.d.). Special Issue: Microfiltration and Ultrafiltration Membrane Science and Technology. 1. Available from https://doi.org/10.1002/app.42002. Liu, S., Zhang, M., Fang, F., Cui, L., Wu, J., Field, R., & Zhang, K. (2016). Biogenic silver nanocomposite TFC nanofiltration membrane with antifouling properties. Desalination and Water Treatment, 57(23), 10560 10571. Available from https://doi.org/10.1080/19443994.2015.1040854. Morales-torres, S., Pastrana-martı, L. M., Figueiredo, L., Faria, J. L., & Silva, A. M. T. (2015). Graphene oxide based ultrafiltration membranes for photocatalytic degradation of organic pollutants in salty water. Water Research, 7. Available from https://doi.org/10.1016/j.watres.2015.03.014. Xia, S., & Ni, M. (2015). Preparation of poly (vinylidene fluoride) membranes with graphene oxide addition for natural organic matter removal. Journal of Membrane Science, 473, 54 62. Available from https://doi.org/ 10.1016/j.memsci.2014.09.018.

CHAPTER 8

Membranes for air cleaning ˜oz2,3, Francesca Russo1, Matteo Manisco1, Adolfo Iulianelli1, Roberto Castro-Mun 1 1 Francesco Galiano and Alberto Figoli 1

Institute on Membrane Technology, National Research Council of Italy (ITM-CNR), Rende, CS, Italy, 2Department of Process Engineering and Chemical Technology, Faculty of Chemistry, Gdansk University of Technology, Gdansk, Poland, 3Tecnologico de Monterrey, San Antonio Buenavista, Toluca de Lerdo, Mexico

8.1 Introduction Nowadays, one of the most relevant issues that the world is facing deals with the pollution of natural sources including water and air (Ursino et al., 2018). Air pollution implies the presence of various chemical agents, volatile organic compounds (VOCs), particulate matter (PM), among others, that decrease the air quality, affecting several environmental cycles and contributing to climate change (Van Tran et al., 2020). Furthermore, polluted air can directly harm the health of humans, animals, and plants (Manisalidis et al., 2020). In humans, such polluting compounds can be transported through the respiratory system by means of inhalation, provoking respiratory and cardiovascular diseases, reproductive and central nervous system dysfunctions, and severe forms of cancer (Kelishadi & Poursafa, 2010; Mannucci et al., 2017). The main contaminants related to such chronic diseases are CO and CO2, SO2, nitrogen oxides (NO and NO2), VOCs, suspended PM (soot, dust, asbestos, lead, etc.), photochemical oxidants (ozone O3), and radioactive substances (Amano, 2010; Castro-Mun˜oz, Gontarek et al., 2019; Miller, 2017). In developed countries, the air quality has deteriorated rapidly in recent decades as consequence of a complex interaction between natural and anthropogenic environmental conditions (Mayer, 1999). Inherently, air pollution in developed cities represents a serious environmental issue. The air pollution of the urban atmosphere relies on the emission and transmission of air pollutants. For instance, Fig. 8.1 illustrates the main sources of contaminants and polluting compounds of the air in an urbanized area. Since most of these human primary activities cannot be banned, there is a strong need of attending to such a worldwide issue with the proposal of suitable treatment techniques for removing such pollutants from the air (Rashidi et al., 2012). To date, several separation techniques have been proposed including absorption, adsorption, incineration (or combustion), and their Current Trends and Future Developments on (Bio-) Membranes. DOI: https://doi.org/10.1016/B978-0-12-824103-5.00010-3 © 2023 Elsevier Inc. All rights reserved.

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256 Chapter 8 Fuel Combuson 6%

Miscellaneous 12%

Industrial Process 4%

on-road vehicles 56% Non-road vehicles& Enqines 22%

Figure 8.1 Main sources of contaminants in air pollution (Rashidi et al., 2012).

possible coupling. Such processes are mainly used for the removal of gaseous pollutants, along with VOCs and other fine chemicals. When dealing with the removal of particles or suspended solids from the air, conventional filters seem to be enough for their abatement to enhance indoor air quality. Very recently, emerging separation techniques, such as membrane technologies, have been also pointed out as potential candidates for the separation and removal of pollutants in the air. Membrane technologies use a perm-selective barrier (well-known as a membrane) to split selectively various compounds present in a gas or liquid mixture. Such technologies can be generally classified according to the driving force entering into play: pressure-driven processes (e.g., microfiltration, ultrafiltration, reverse osmosis), concentration-driven processes (e.g., dialysis, pervaporation), and temperature-driven processes (e.g., membrane distillation). Membrane technologies are becoming relevant and exploited by the research community since they own several advantages in terms of (Criscuoli & Carnevale, 2015; Woo et al., 2016): • • • • • •

low-energy demand; high separation rates; easy scale-up; simple operation and control of parameters; high productivity (i.e. permeation fluxes); and no additional phases needed.

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These features have allowed the expansion of these processes to a plethora of different applications in different sectors including water treatment (Van Der Bruggen et al., 2003), seawater desalination and water purification (Gontarek et al., 2021; Gontarek-Castro et al., 2021; Yusuf et al., 2020), chemical purification (Castro-Mun˜oz, Galiano, et al., 2019; Mishra & Kaistha, 2018), azeotropic solvent separations (Castro-Mun˜oz et al., 2018; Pereiro et al., 2012), hydrogen purification, biogas upgrading (Castro-Mun˜oz, Fı´la, Martin-Gil et al., 2019; Iulianelli et al., 2021; Yusuf et al., 2020), CO2 capture (Grosso et al., 2014; Russo, Galiano, et al., 2020; Steeneveldt et al., 2006), and biomolecules production (Cassano et al., 2019; Conidi et al., 2020; Mansourpanah & Emamian, 2020). Here, due to their high productivity in terms of permeate fluxes and separation efficiency (selectivity), membranes are a promising tool for the cleaning and upgrading of air, showing the ability to separate VOCs, CO, CO2, sulfur oxides, NO and NO2, etc. This chapter will provide an overview on the use of membranes, and related processes, in the field of air cleaning. Particularly, the techniques employed for the preparation of polymeric membranes (e.g., phase inversion, electrospinning) will be introduced and presented along with the materials (e.g., polymers, additives) that are traditionally used for the preparation of membranes intended for this application. The application of membranes in the air cleaning field will be then thoroughly discussed. Now more than ever, the use of membrane filters in protective personal devices (e.g., face masks employed against COVID-19) is of huge interest. Moreover, the application of membranes in air-conditioning systems and in the recovery of VOCs is gaining an increasing attention for the improvement of the indoor and outdoor air quality, as well as for the remediation of environmental problems. Important outcomes and insights from current development works are highlighted together with the conclusions.

8.2 Membranes for air cleaning Membranes can be designed in different module configurations, such as hollow fibers, flat sheet, tubular, spiral-wound, for subsequent testing in air cleaning. In light of air cleaning, most of the research is focused on separating VOCs, vapors of organic compounds, SO2, NOx, CO2, NH3, H2S, CH4, among others, in which the membranes can be implemented into specific membrane processes for successful separation, as specified in Table 8.1. Membrane processes include the permeation of vapors, pervaporation, liquid membranes, gas separation, and membrane reactors. Recently, membrane contactor was also included as a new technology where the membrane is completely in contact with two phases and integrated with conventional operations such as extraction or absorption (Klaassen et al., 2005). As an example, polymer membranes have been extensively evaluated for their ability to separate CO2 from different gas mixtures (Favvas et al., 2018); for instance, Table 8.2 lists a few examples of polymer membranes aimed at separating CO2 from CH4. In general, it

258 Chapter 8 Table 8.1: Membrane-based technologies involved in air cleaning and purification (Bernardo et al., 2009; Bodzek, 2000). Chemical compound

Membrane process

Vapors of organic compounds (halogen-derived hydrocarbons, aromatic compounds) SO2, NOx, CO2 (combustion products) NH3 H2S

Permeation of vapors, pervaporation, membrane contactors Liquid membranes, membrane contactors Liquid membranes, membrane contactors Membrane gas separation, liquid membranes, membrane contactors, membrane reactors Membrane gas separation

CH4, CO2 (biogas)

Table 8.2: Performance of various polymer membranes for CO2 and CH4 separation. Polymer

CO2 permeability (barrer)

CO2/CH4 selectivity

Silicone rubber Polyimide Poly(ether imide) Cellulose acetate Polytrimethylosiliolopropyne Polystyrene Polyamide Polycarbonate Polylactic acid Natural rubber

3200 0.2 1.5 6.2 33100 11 0.16 10 70 130

3.4 64 45 31 2.0 8.5 11.2 26.8 285 4.6

can be seen that most of the membranes display a good performance toward such a binary mixture (Ahmad et al., 2020). Of course, they may still present a perm-selectivity limitation, which is currently a research scope in the field of membrane gas separation. Very recently, many other polymer membranes have been proposed for such a purpose, for example, Matrimid/PEG 200 blend membranes in flat sheet configuration have shown a CO2 permeability of over 27 Barrer and a CO2/CH4 separation factor of 24 (Castro-Mun˜oz, Fı´la, et al., 2019), while crosslinked 6FDA-ODA exhibited interesting CO2/CH4 separation efficiency (over 37) (Ahmad et al., 2018). Among biopolymeric based membranes, polylactic acid Easy Fil-White membranes were synthesized with the purpose of separating CO2, reaching a CO2/CH4 selectivity of 285 with a CO2 permeability of 70 Barrer, well overcoming the related Robeson’s upper bound (Iulianelli et al., 2019). Toward the purification of air, the separation of other gases and vapors involves CO2/CH4 in biogas and natural gas: in this application, polymer membranes are likely to be the most widely investigated membranes for gas separation due to the interest in methane upgrading. Natural gas is usually employed in several sectors and its global demand corresponds to power generation that represents around 40% of the total consumption, followed by the usage in the industry (B24%) and as fuel and commercial uses (B22%) (Martin-Gil et al.,

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2019). In polymer membranes for CO2 separation from CH4, many reviews and development works are available in the literature addressing their success for such molecular separations (Castro-Mun˜oz et al., 2018; Mondal et al., 2012; Norahim et al., 2018; Robeson, 2008). 1. H2 or He from other gases: the importance of He separation relies on its high-added value, since such an inert gas is mainly obtained from natural gas fields. Prof. Scholes studied the possibility of He recovery from natural gas using membrane technologies evaluating the economical and process design points of view (Scholes & Gosh, & Ho, 2017). Nowadays, several commercial membranes for example, SEPURAN from Evonik or GENERON membrane from IGS, focused on He enrichment applications are available (Scholes & Ujjal, 2017). 2. H2S/CH4—natural gas: the separation of these mixtures has been proposed using commercial PPO hollow fiber and PEUU flat membranes. In Niknejad’s work, for instance, the H2S concentration was varied from 100 to 5000 ppm in CH4 binary synthetic gas mixtures (Niknejad et al., 2017), where the membranes provided an H2S/CH4 separation factor of 1.3
3.1. 3. O2/N2—oxygen enrichment of air and vice versa: in this approach, membranes are used for the production of oxygen-enriched air (Belaissaoui et al., 2014). Various membrane materials and operating conditions can be implemented to produce oxygen concentrations between 25% and 35%; for example, polyphenylene oxide membranes can offer a %O2 of up to 50% (Matson et al., 1986). 4. H2O—drying of gases: in this application, two membrane materials, such as block copolymer, (PEBAX 1074 from Atofina/Arkema) and SPEEK (sulfonated PEEK from Victrex (United Kingdom)) were used for the fabrication of hollow fibers for flue gas dehydration. Additionally, such membranes demonstrated their capacity in the transport and separation of other gases (Sijbesma et al., 2008), as presented in Table 8.3: 5. SO2—desulfurization of gases: here, the researchers have initiated the development of flue gas desulfurization by means of membrane gas absorption (Klaassen et al., 2005). For this, a model gas of SO2 in nitrogen was subjected into a lab-scale module with 0.6-mm fibers-based nonpolar polymers, such as polypropylene, polyethylene, and Table 8.3: Permeance and selectivity for PEBAX 1074 and SPEEK hollow fiber membranes (Sijbesma et al., 2008). Gas Water N2 α(CO2/N2) α(O2/N2)

Permeance (GPU) SPEEK 28,700 0.03 # 37 # 13

PEBAX 1074 33,100 0.45 # 48 # 3.0

260 Chapter 8 Teflon, for the aqueous absorption of liquids. The experimental outcomes with only 25-cm length showed SO2 recoveries as high as 99%. 6. Vapors of organic compounds—removal from the air and from industrial waste flows: in this approach, the removal of organic compounds from the air is not the only issue. Generally, the removal of hydrocarbons is required in order to skip their condensation in pipelines and damage facilities in natural gas upgrading. As an example, rubber polymers exhibit good properties for gaseous alkanes separation (Grinevich et al., 2011), while PTMSP, evaluated in 2/98 vol./vol. n-C4H10/CH4 mixed gas conditions, revealed a high permeability for n-C4H10 with values of 53,500 Barrer and high selectivity of 30 (Pinnau & Toy, 1996). As a current trend in the field, the physicochemical properties of the membranes can be improved through the incorporation of inorganic materials in order to achieve a better molecular sieving effect in gas separation and to promote the selective transport of vapor molecules. For example, the functionalization of NFMs is a prevailing and promising pathway to fabricate highly efficient air filters for high-precision filtration. In this regard, Chen and coworkers developed graphene oxide-functionalized PVDF nanofibrous membranes for efficient PM removal (Chen et al., 2021). The resulting composite membranes exhibited a higher PM2.5 removal efficiency of 99.31% and better reusability than the pristine PVDF NFMs (93.7%) and GO@PVDF NFMs (95.4%). PM2.5 are fine inhalable particles, with diameters that are generally 2.5 μm or smaller (US EPA). The authors suggested that such a composite could be a promising material for high-efficiency air cleaning (Chen et al., 2021).

8.3 Polymeric membrane preparation for air cleaning Polymeric and MMMs membranes for air cleaning can be fabricated using different techniques, such as phase inversion, electrospinning, stretching, interface polymerization, and extrusion (Figoli et al., 2016), selected on the basis of the desired membrane configuration.

8.3.1 Phase inversion Phase inversion is the most used technique to produce symmetric or asymmetric membranes with sponge-like and/or finger-like morphology. It consists of a demixing process where a homogeneous liquid solution, composed of a polymer, a solvent, and, possibly, additives, changes into a solid state in the presence of a nonsolvent. It is an extremely versatile technique due to the facility to prepare membranes from several polymers, as long as the polymer is soluble in the chosen solvent. The different morphologies that can be obtained depend on the exchange rate between solvent and nonsolvent. Phase inversion may be achieved through different techniques such as EIPS, NIPS, VIPS, and TIPS.

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8.3.1.1 EIPS technique EIPS is the simplest method employed to prepare dense anisotropic membranes; the polymer is solubilized in a volatile solvent or a mixture of volatile solvents in order to obtain a homogenous solution before being cast on a suitable support. The membrane is formed by demixing, which takes place through the solvent evaporation. The morphology is controlled by several factors such as: 1. the properties of the solvent (e.g., boiling point) and the rate of evaporation (Lalia et al., 2013); 2. polymer and nonsolvent concentration (Dı´ez & Rosal, 2020); and 3. casting conditions such as temperature, humidity, and pressure. 8.3.1.2 NIPS technique NIPS is based on the immersion precipitation method, where a homogenous solution, composed of a polymer and a solvent (with or without additives), is cast on an inert support or spun and immersed in a coagulation bath made up of a nonsolvent, generally water. The exchange rate between solvent and nonsolvent and the following polymer precipitation results in the formation of the membrane. Fig. 8.2 reports the schematic representation of a nascent membrane at the bath interface. The solvent migrates into the coagulation bath at flux JS, while the nonsolvent diffuses into the nascent membrane at flux JNS until the system becomes thermodynamically unstable and the precipitation of the polymer takes place (demixing) (Lalia et al., 2013). Depending on the exchange rate, two types of demixing can occur: delayed or instantaneous demixing that influence the final morphology of the membrane. The instantaneous demixing is generally characterized by finger-like morphology with macrovoids (Fig. 8.3A), while the

Figure 8.2 The schematic representation of nascent membrane/bath interface. Adapted from Lalia, B., Singh, V., Kochkodan, R., Hashaikeh, & Hilal, N. (2013). A review on membrane fabrication: Structure, properties and performance relationship. Desalination, 326, 77
95.

262 Chapter 8 delayed demixing can form a sponge-like structure with a relatively dense top layer (Fig. 8.3B). 8.3.1.3 VIPS technique The VIPS method consists of preparing porous membranes under controlled atmosphere. The casting solution is exposed to nonsolvent vapor, generally water, in a climatic chamber at different contact times. The highly porous membranes can be obtained owing to a slower phase inversion that can be completed by immersion precipitation in a coagulation bath. The porous surface also depends on the exposure time of humidity. 8.3.1.4 TIPS technique TIPS is a method for producing membranes at high temperature using a suitable solvent. The cooling of casting solution induces phase separation, thus allowing the precipitation of the polymer and the formation of the membrane. Generally, the solvents used have high boiling point, low molecular weight, and low volatility. The typical morphology produced by TIPS is represented by a spherulitic-like porous structure that depends on temperature gradient, cooling rate, and use of additives.

8.3.2 Electrospinning technique Electrospinning is a simple, economical, versatile, and environment-friendly technique, used to produce uniform nanofibers membranes by means of high voltage, intended for several applications, including desalination, wastewater treatment, and air cleaning (Henning et al., 2021). By this technique, a high potential is applied between the polymer solution and a metal collector. When the surface tension of the polymer solution is overcome, a charged liquid jet, which generally forms a Taylor cone, starts to deposit and produce nanofibers on the metal collector, as shown in Fig. 8.4. Their average pore size diameters may range from

Figure 8.3 Membrane formation via NIPS: (A) rapid demixing; (B) delayed demixing (Marshall et al., 2021).

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10 to a few hundred nanometers as the submicron range is preferred for air cleaning. Uniform nanofibers depend also on the material properties used for the polymeric solution and on the operation conditions of the adopted technique. The solvent plays an important role in the production of two-dimensional (2D) and three-dimensional (3D) networks of nanofibers. As shown in Table 8.4, different factors in electrospinning are responsible for the variations in pore diameters and morphology of the nanofibers. This includes solution, process, and ambient parameters (Islam et al., 2019). Major solution parameters for producing uniform nanofibers membranes without the presence of beads are high dialectic property, low surface tension, and an optimum

Figure 8.4 Electrospinning technique (Russo, Ursino, et al., 2020).

Table 8.4: Parameters affecting electrospinning. Solution parameters

Process parameters

Ambient parameters

Dielectric constant of solvent Surface charge density Surface tension Solution viscosity Molecular weight of the polymer Concentration of chemicals

Voltage Flow rate Type of collector Distance between needle and collector

Temperature Humidity

264 Chapter 8 viscosity, ranging from 1 to 200 poise. The dialectic property can be improved by the presence of some solvents, such as acetone, chloroform, and ethyl acetate, which can produce a higher net charge density obtaining a thinner fiber diameter. The major advantage of the electrospinning technique lies in the possibility of producing nanofibers with a small diameter and a large specific surface area. In order to reduce the surface tension of the solution, chemicals (solvents, additives, etc.) with low surface tension can be adopted. From the process parameters point of view, the voltage influences the fluid jets, leading to the formation of a 3D network of nanofibers with a small diameter. The average nanofibers diameters may be decreased by increasing the distance between the needle and the collector plate. Ambient parameters such as temperature and humidity can also influence the viscosity of the solution and the morphology of the nanofibers.

8.3.3 Polymeric coating Polymeric coating is a method that involves the deposition of a polymeric layer on the membrane surface or a polymeric support. The main goals of this technique are the improvement of the mechanical properties and/or the surface properties of the membranes, such as hydrophilicity or hydrophobicity, adhesion, etc. Generally, hydrophilic coated membranes present active groups on their surface. They have the ability to form hydrogen bonds with water, while hydrophobic coated membranes are characterized by a lower affinity with water. Coating methods can be subdivided into two categories: solution casting and polymerization reactions. The solution casting method is widely adopted due to its simplicity and includes dip, spin, casting, and spray coatings (Figoli et al., 2021) (Fig. 8.5). Dip coating consists of a method where the membrane is immersed in an appropriate solution for a fixed time. Subsequently, the membrane is dried or exposed to different treatments such as UV, IR radiation, etc. Spin coating produces uniform and low-cost membranes; it is characterized by the deposition of the solution on a support, the rotation speed, and the solvent evaporation. Spray coating is a nebulization process with low solution viscosity. The casting coating relies on the casting of the solution on the membrane by using a casting knife. Recently, dip and spray coating methods were used to cover nonwovens supports such as PET and textile supports with aluminum or silver nanoparticles (NPs), or GO, obtaining membranes with high filtration efficiency (Bodzek, 2000). The major techniques of polymerization reactions are interfacial, in situ, and plasma polymerizations and grafting as well. The interfacial polymerization consists of a reaction between two reactive monomers at the interface of two insoluble liquids, while for the in situ polymerization technique, the reactive monomer is in contact with the membrane. Plasma coated membranes are obtained by the ionization of a gas in the reactor, while grafted membranes use different chemical groups, maintaining the chemical stability thanks to the formation of covalent bonds.

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Figure 8.5 (A) Dip coating, (B) spray coating, (C) spin coating, and (D) casting coating methods. Adapted from Figoli, A., Ursino, C., & Galiano, F. (2021). Innovative coating membranes for water treatment. Functional Nanostructured Membranes, 345
384.

8.4 Membrane materials for air cleaning The choice of the membrane materials is fundamental for the fluid dynamics of the dope solution system and for the filtration efficiency of the membrane. The properties of the dope solution, such as viscosity, surface tension, and conductivity, have also a control on the preparation parameters of the membrane. The dope solution consists of polymers and/or biopolymers, organic and/or inorganic additives in the appropriate solvent. In the following, the membrane materials for air cleaning are presented and discussed.

8.4.1 Polymeric and biopolymeric materials Polymers are likely to be the primary materials for membrane fabrication. Polymeric membranes may be derived by different sources: fossil-based or traditional synthetic

266 Chapter 8 polymers and biopolymers from raw materials (biomass or chemical synthesis). The choice of the polymers together with the appropriate solvent and additives is fundamental for the thermodynamic and kinetic aspects of dope solution preparation (surface tension, viscosity, and conductivity) and also plays an important role on the final membrane performance. The flexibility of the polymer chains and their mobility are correlated to the type of polymer: high degree of chain mobility for rubbery state and high rigidity for glassy state (Russo, Galiano, et al., 2020). Sometimes, the polymers are blended with other polymers or functionalized with inorganic materials in order to achieve suitable properties. The traditional polymers have many advantages in terms of physical, chemical, and thermal stability for producing membranes under different configurations (hollow fibers, flat sheet, nanofibers, etc.). The most relevant polymers for polymeric membranes preparation that are suitable for air cleaning are PAN (Wang et al., 2012), PP (Watanabe et al., 2011), fluoropolymers such as PVDF and PTFE (Huang et al., 2017), PEO (Kadam et al., 2018), PES (Homaeigohar et al., 2010), nylon-6 (Gupta et al., 2009), and PS (Ke et al., 2016). Fluoropolymers are thermoplastic materials, made up of two main units such as carbon CH2 and fluorine CF2 in the polymer chain, and exhibit excellent properties depending on the degree of crystallinity, the molecular weight (.100,000 Da), and the crystal polymorph (α, β, γ, δ, and ε). The main properties of fluoropolymers are: 1. 2. 3. 4. 5.

high thermal stability; high chemical stability; good resistance to oxidation reactions; high melting point; and low surface tension.

Available commercial fluoropolymers and their structure
property correlations are listed in Table 8.5. The most used polymers for membrane preparation with fluoropolymeric properties are based on PVDF, which is characterized by the alternate CH2 and CF2 groups in the structure (Drobny, 2020b). The degree of crystallinity can vary from 35% to more than 70% and influences the mechanical strength as well as the temperature resistance. The density of PVDF depends on the degree of crystallinity form, ranging from 1.68 g/cm3 for the amorphous form to 1.98 g/cm3 for the crystalline form. It exhibits outstanding chemical resistance to different inorganic acids, halogens, oxidizing agents, whereas it has a good solubility for dipolar aprotic solvents, acetone and esters due to the presence of the dipole created by the alternating groups of CH2 and CF2. These units in the structure are also responsible for the high dielectric constant. For its high strength and low air resistance, PVDF was well studied for new electret fiber filters for long-term aerosol filtrations (Sun & Leung, 2019). PTFE is a well-known polymer requiring high temperatures to become flexible. The PTFE molecule is a twisting helix characterized by the presence of CF2 atoms in the chemical structure. It exhibits a high degree of

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Table 8.5: Commercial fluoropolymers and structure
property correlations. Flexural modulus (MPa)

Maximum service temperature ( C)

Fluoropolymers

Abbr.

Degree of Degree of crystallinity fluorine

Elongation at break (%)

Polyvinylidene fluoride

PVDF

Crystalline

50

1750

130

300

1200

150

220

1550

130

440

250

260

400

250




325

600

200

300

600

260

Copolymer of ethylene and tetrafluoroethylene Copolymer of ethylene and chlorotrifluoroethylene Polytetrafluoroethylene Polychlorotrifluoroethylene Fluorinated ethylene propylene Copolymer of tetrafluoroethylene and perfluoropropylvinylether

Partially fluorinated ETFE Crystalline Partially fluorinated ECTFE Crystalline Partially fluorinated PTFE Crystalline Totally fluorinated PCTFE Amorphous Totally fluorinated FEP Crystalline Totally fluorinated PFA Crystalline Totally fluorinated

Source: Adapted from Drobny, J. G. (2020a). Commercial grades of fluoropolymer films. In Applications of fluoropolymer films (pp. 177
233). Elsevier.

crystallinity that results in poor solubility in common solvents and requires high temperatures to be processed. On the contrary, FEP and PFA, which are copolymers of TFE, have a reduced degree of crystallinity for the presence of methyl groups that causes defects in the crystallites of the structure, reducing also the melting point (Drobny, 2020a). Furthermore, the PTFE polymer is characterized by the chlorine atom in the structure that promotes the attractive forces between molecular chains. The PTFE polymer has good stability in air with high stability below 440 C and low wettability from the permeation properties point of view. In fact, gases pass through PTFE much slower than other polymers. It absorbs small amounts of liquids at room temperature and atmospheric pressure. The rate of permeation is controlled by the crystallinity: the higher the crystallinity degree the lower the permeability. The permeability increases with increasing the temperature (Hao et al., 2004; Ranjbarzadeh-Dibazar et al., 2017). For its properties, PTFE is a good candidate for the preparation of highly efficient air filtration fibers at high temperature. Generally, the filtration of aerosol particles with PTFE nanofibers is about 98%, with a relative low pressure drop of 90 Pa. The main drawback is the fouling phenomena that occur at the surface of the nanofiber’s membrane. Many researchers investigated the cleaning methods to regenerate the system, such as adsorption, photochemical catalysis, or passive cleaning with carbon particles (Xu et al., 2019).

268 Chapter 8 PAN is a polymer with no significant degradation below 300 C and it is resistant to acids and organic solvents. It has good mechanical stability and high efficiency of filtration (between 95% and 100%) under extreme hazardous air-quality conditions; for example, in the presence of a PM2.5 index above 300 (H. Zhang, Xie et al., 2021). The PAN polymer used for the preparation of air cleaning filters is characterized by good thermal and chemical stability combined with high humidity resistance (Galiano et al., 2018). The filtration efficiency for PA nanofibers is in the range of 84.9% to 90.9% (Matulevicius et al., 2014). Current trends in industrial and laboratorial research on new polymers (biopolymers) based on biosources are the result of a challenging process. The properties of biopolymers encompass the low environmental impact, the high biocompatibility, the biodegradability, and the compostability (Russo, Galiano, et al., 2020). The most relevant biopolymers used for air cleaning are PLA, PU, PAA (Zhu et al., 2018), PEO, PVA, PGA (Matulevicius et al., 2016), EVOH, PHAs, CHT, and PCL (Russo, Galiano, et al., 2020). PLA is a thermoplastic polyester from biomass, produced by the polymerization of lactic acid and/or ring-opening polymerization of cyclic lactide. PLA presents two forms of L isomer-lactic acid or D isomer-lactic acid or a combination of both isomers. The grade of crystallization can influence the percentage of each different form as well as the Tg of the polymer, which ranges from 50 C to 65 C and represents the behavior of the material (Russo, Galiano, et al., 2020, Russo, Ursino et al. 2020). Due to its stability at room temperature (25 C), it has been used in gas separation (Iulianelli et al., 2019; Russo, Galiano, et al., 2020, Russo, Ursino et al. 2020). PVA is a semicrystalline biopolymer derived from synthetic raw materials. It has high solubility in water and possesses good gas barrier properties (Huang et al., 2017). PHAs are derived from the fermentation of microorganisms and are characterized by the high processability in different solvents. PU is a hydrophilic material and presents a good capacity of absorption of VOCs (Galiano et al., 2018).

8.4.2 Additives and advanced materials Additives are often employed in the formulation of polymer dope solutions in order to impart, to the final membrane, specific and unique properties. They can facilitate, for instance, the preparation procedure of polymeric membranes by modifying the characteristics of dope solution, as well as the thermodynamic and kinetic parameters of preparation methods. Moreover, they can promote the formation of particular membranes architectures (e.g., sponge-like or finger-like structures) or improve membrane pore size and porosity. Common additives include: 1. polymer additives such as PEG and PVP (Dı´ez & Rosal, 2020); 2. salts such as LiCl (Russo, Ursino, et al., 2020; Santoro et al., 2017), TEAB (Yalcinkaya et al., 2015), NaNO3, NaCl, CaCl2 (Qin et al., 2007);

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3. two-dimensional materials such as GO, MOF, MWCNTs, HNTs, etc. (Chen et al., 2021); 4. metal oxides or inorganic NPs such as TiO2, Al2O3, SiO2, BaTiO3 and Fe3O4 (Kadam et al., 2018); and 5. starch products such as cyclodestrin (CD) (Kadam et al., 2018). The use of PEG and PVP may improve the porosity and pore dimensions of the membranes. Both additives are hygroscopic agents and absorb water vapor during the phase inversion process (Russo et al., 2021). LiCl and TEAB have similar electrical conductivity and high solubility in aprotic solvents; they can modify the conductivity of polymeric solutions, improving the charge of the jet during the electrospinning technique. GO, a 2D material with sp2 hybridization of carbon atoms, has high thermal conductivity but poor structural stability that can be improved with interactions by means of chemical cross-linking or in combination with NPs and polymer carriers (Han et al., 2021). It is possible to produce GO membranes by an electrospinning coating method with a higher QF, between 0.47 Pa21 and 0.75 Pa21 for PM2.5 pollutants removal. QF is correlated to the efficiency that can be used to evaluate the performance of the air filter. The removal mechanism of PM2.5 by GO membranes is based on the formation of different transport channels through the membrane at micron level, increasing the pore size selection. Furthermore, the preparation of GO nanofibers membranes increases the surface area of filtration and facilitates the adsorption of pollutants (Henning et al., 2019). GO membranes were also studied for the preparation of PAN composite membranes via electrospinning by using DMF as a solvent. The results confirmed a high filtration effect of PM2.5 (efficiency of 99.97%) with a low pressure drop (Li et al., 2018). The NPs were incorporated in dope solutions for recent preparation of nanofibers for air filtration in order to: 1. 2. 3. 4.

increase the viscosity of the solution and reduce the pore dimension; increase the porosity or the surface roughness; improve the chemical resistance; and release negative ions.

Due to the presence of NPs, an increase of conductivity of the dope solution is noticeable as well as the viscosity that becomes significant at a high concentration of NPs. Their presence, therefore, tends to be critical for the solution spinnability in the electrospinning technique (Henning et al., 2019). TiO2 as well as Ag NPs can be also considered as antimicrobial agents and are able to improve the efficiency of air filtration. CDs were also used for nanofibers preparation for removing with high efficiency the aerosol particles from 0.3 to 5 μm. Common organic additives that improve the membrane performance include PVP and PEG. They are pore-forming agents with hydrophilic properties. Due to their molecular weights and/or their concentration in the dope solution, membrane morphology can change from a finger-like to spheres or sponge-like structure.

270 Chapter 8

8.5 Membrane technology applications in air cleaning Among the most recent developments of technologies for the environmental protection, membrane engineering offers excellent prospects in this field, thanks to its multidisciplinary applications, since is based on different principles of separation, as well as on a wide range of membrane types present on the market, and it can be applied particularly in two environmental fields: water and air pollution (Zhang et al., 2012). Of course, the different applications will affect the choice of the most adequate membrane materials and the related process for removing the specific contaminant. At the same time, also the type of membrane structure is strongly related to the required separation process (Mulder, 1994). In the following, the application of porous and nonporous membranes to air cleaning is presented and discussed.

8.5.1 Air transport mechanism in membranes The performance evaluation in membrane science is most commonly associated with two parameters: permeability and selectivity. Nonporous membranes are able to separate molecules of the same size and the transport mechanism through the membrane may be represented by solution-diffusion (Fig. 8.6): adsorption of the permeable component into the membrane surface, permeation by diffusion through the membrane matrix, and desorption at the low pressure side of the membrane (Bernardo et al., 2009).

Figure 8.6 Schematic representation of the solution-diffusion mechanism in a dense polymeric membrane. Reprint from Iulianelli, A., &Drioli, E. (2020). Membrane engineering: Latest advancements in gas separation and pre-treatment processes, petrochemical industry and refinery, and future perspectives in emerging applications. Fuel Processing Technology with the permission of Elsevier.

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Separation by nonporous membranes depends on the difference in permeability of the gaseous species passing through the membrane. This transport through the membrane is described by the first law of Fick (Eq. 8.1), where the flux J is defined as: J 52D 

dC dx

(8.1)

where: J 5 flux through the membrane; D 5 diffusion coefficient in the membrane; 5 concentration gradient; C 5 concentration; and x 5 membrane thickness.

dC dx

As mentioned above, different membranes with respect to a given gas mixture are available, and permeability P is an important parameter that allows comparison of the separating properties of different membranes. The gas permeability is a property of the material and is evaluated (Eq. 8.2) as the product between solubility S and the diffusion coefficient D. It depends on the operating temperature: P5D  S

(8.2)

where: P 5 permeability; D 5 diffusion coefficient in the membrane; and S 5 solubility. On the other hand, the typical mechanisms that are useful to describe the gas transport in porous membranes are: molecular diffusion and viscous flow, capillary condensation, Knudsen diffusion, surface diffusion, and molecular sieving (Iulianelli & Basile, 2018). The contributions of these different mechanisms depend on the properties of the membrane and the gas under the operating temperature and pressure. The variety of these mechanisms, which can also coexist (depending on the size of the pores, tortuosity, temperature, pressure, nature of the membrane, and the permeating molecules), make this type of membrane much more versatile than dense ones, mainly because they are capable of being permeated by a greater number of compounds. The viscous flow, also known as Poiseuille flow, takes place when the average pore diameter is much larger than the average free path of the molecules, and it occurs if a pressure gradient is applied to this pore regime. The ratio between the average pore diameter and the average free path of the molecules usually must be greater than 3. Hence, the collisions between the different molecules are more frequent than those between molecules and walls. Here, the permeating flux can be described by the Hagen
Poiseuille equation (Eq. 8.3): J52

r 2 pdp 8μRTdx

(8.3)

where: p 5 gas pressure; T 5 Temperature; r 5 pore radius; R 5 gas constant; μ 5 dynamic viscosity; and dp dx 5 pressure gradient.

272 Chapter 8 The mechanism predominant in macroporous and mesoporous membranes depends on the parameter r/λ, which represents the ratio between the average pore diameter and the free path of the molecule. When it is # 0.05, the molecules collide more frequently with the pore wall than with each other and Knudsen diffusion occurs under a pressure gradient. In this case, the permeating flux through a capillary pore can be described by the Knudsen equation (Eq. 8.4):   2 8RT 0:5 r dp J52 (8.4) 3 μM RT dx where: M 5 molecular weight of the gas; T 5 Temperature; r 5 pore radius; R 5 gas constant; μ 5 dynamic viscosity; and dp dx 5 pressure gradient. The surface flow occurs when the gas molecules are strongly adsorbed on the pore walls and migrate along the pore surface. Usually, this is the case with gases which condense rather easily at moderate temperature
pressure conditions. The flux is generally described by a Fick’s law and surface diffusion can occur parallel to Knudsen transport (Kapoor et al., 2008). Capillary condensation occurs when the pores are small enough and the gas is a condensable vapor, so that the entire pore is filled with liquid. To happen, capillary forces are needed that are strong enough only at relatively low temperatures and in the presence of small pores. The last case is molecular sieving that, in terms of pore diameter, acts when the pore diameter is small enough to allow only the smallest molecules to permeate, while the larger ones are excluded from entering the pores. This type of process is often referred to as selective diffusion.

8.5.2 Individual protection devices The expression “individual protection devices” (international acronym PPE) refers to all the implemented devices able to safeguard the human health and safety risks (Fig. 8.7). The application areas are different and range from working and sports, to medical and domestic (Departement of Labor, 2003). The devices are distinguished under different types, linked to the final use, and among them, the respiratory tract protections are particularly relevant. The former devices may be represented by the facial mask, which creates a physical barrier between the mouth and nose of the wearer and potential contaminants in the environment, protecting from potentially harmful substances.

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Figure 8.7 Face masks and nanotechnology (Palmieri et al., 2021). Reprint from Palmieri, V., Maio, F. D., Spirito, M. D., & Papi, M. (2021). Face masks and nanotechnology: Keep the blue side up. Nano Today, 37, 101077 with the permission of Elsevier.

In addition to facial masks, there are also respirators that are indicated as personal air purifiers, used to protect the operators in environments with high concentrations of dangerous or infectious substances. Structurally, they are made up of the whole or part of filter material, which can be constituted by nanofibers. The nanofiber membranes possess a high specific surface area per mass units, a low weight, high permeability, good interconnectivity of pores, and potential to incorporate active chemistry; all excellent properties that may improve the efficiency of filtering for a wide range of filtration applications, especially for smaller particles such as viruses and bacteria, or particles from anthropological activities, such as dust and various pollutants, due to small pore sizes (Matsumoto & Tanioka, 2011). The filters are evaluated based on three parameters: filter life time, pressure drop, and air filtration efficiency (Akduman & Akcakoca Kumbasar, 2018). According to the former parameters, the application of nanofibers shows greater efficiency of the filter as well as a greater pressure drop. Some examples of research activities are reported in Table 8.6. Li and Gong (2015) studied a mask filtration material made of polysulfone nanofibers prepared by electrospinning, observing that it was efficient in filtering the PM2.5 particles while preserving good breathability. As already reported in Section 8.3.2, electrospinning is a versatile processing technique for preparing uniform nanofiber filters from different polymer solutions, by applying a highvoltage charge to that solution and using the charge to draw the solution from the source to

Table 8.6: Summary of membrane-based processes used for individual protection devices. Membrane

Production technique

Technical production parameters

Polysulfone 1.8 g/polyethylene oxide 0.018 g

Electrospinning at three times: 15, 30, 60 min

Voltage: 13 kV; Distance: 13 cm; Humidity: 53%; Flow rate: 0.4 mL/h.

PMIA/PAN

Electrospinning

Polylactic acid-activated charcoal at four different compositions: 0% (45 min solution mixing time), 1% (50 min), 5% (55 min), and 8% (55 min) A.C.

Electrospinning

Voltage: 55 kV Distance: 18 cm Voltage: 25.8430 kV; Distance: 15 cm; Flow rate: 2.543.0 mL/h.

Polyvinyl alcohol (PVA) with ZnO and CuO nanoparticles

Electrospinning

Voltage: 25 kV; Flow rate: 1 mL/h; Distance: 10 cm.

Nanofiber parameters

Application

References

Diameter: 500
800 μm; Interdistance among the nanofibers: 1
3 μm: High PM2.5 rejection of 90%. Diameter: 100 μm; Filtration efficiency: 99%. Diameter: 804550 nm; Mat thickness: 0.2740.33 mm; Tensile strength: 26460 MPa; Bacterial filtration efficiency (BFE): $98%. Diameter: 2004250 nm.

Mask filtration to prevent inhaling PM2.5 particles from haze pollution

Li and Gong (2015)

H. Zhang, Xie et al. (2021) Ideal mask filtration in Bulu¸s et al. the COVID-19 (2020) pandemic process

Air filtration

Medical and personal Alshabanah et al. protection (2021) applications: AntiCOVID-19 and antimultidrug resistant bacteria evaluation

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a grounded collector (Hutten & Wadsworth, 2007) (Fig. 8.8). It is also the most widely used technique for the production of nanofibrous membranes for air filtration (Akduman & Akcakoca Kumbasar, 2018). The electrospun nanofibrous membranes with fine diameter, high porosity, and high surface-to-volume ratio can significantly intercept the fine particulate, contributing to high air filtration efficiency and low pressure drop (Ju et al., 2021). In the aforementioned study, the electrospinning parameters were 13 kV as a voltage and 13 cm as the distance between the needle and the aluminum foil. The polymer solution was fed at a constant rate of 0.4 mL/h. The collective time of nanofibers was 15, 30, and 60 min, thus getting different thicknesses. In this regard, this nanofiber-based material was transformed into the comfortable and effective mask to prevent the inhalation of harmful particles in atmospheric pollution. The nanofibrous masks of this study showed a high efficiency of 99.4%, evaluated as rejected particles/total particles in air, at the rank of 60 min. Zhang, Xie et al. (2021) focused on the preparation of new air nanofiber filters, that is, PMIA/PAN composite nanofiber membranes, possessing high efficiency of filtration, an excellent mechanical property, and high temperature resistance. The nanofibers were produced by electrospinning with a voltage of 55 kV, where PMIA/PAN nanofibers were collected by a rotating metal roller, at 70 r/min and the distance between the pyramid nozzle and the receiving device was 18 cm. At the best mass ratio of 9/1, PMIA/PAN nanofiber membranes showed a filtration efficiency above 99%, which proves that the filtration performance of the obtained nanofiber membranes is greatly stable after a series of heat treatments.

Figure 8.8 (A) Schematic illustration of the electrospinning apparatus and process. (B) Photo of PMIA/PAN nanofiber membrane. Reprint from Zhang, H., Xie, Y., Song, Y., & Qin, X. (2021). Preparation of hightemperature resistant poly (m-phenylene isophthalamide)/polyacrylonitrile composite nanofibers membrane for air filtration. Colloids and Surfaces A: Physicochemical and Engineering Aspects, 624,126831 with permission from Elsevier.

276 Chapter 8 Recently, various pandemic infectious diseases have become urgent current problems, caused by various coronaviruses, including severe acute respiratory syndromes such as SARS-CoV-2 and SARS-CoV (Ju et al., 2021). This issue is prompting the discovery and development of the nanofiber membranes with good antimicrobial and antiviral property, applied to personal protection device to fight against the spread of the COVID-19. Zhang et al. (Zhang, Ji et al., 2021) explained how face masks are essential tools to reduce the spread of SARS-CoV-2 from human to human, specially masks composed of ultrafine fibers with diameter down to 10 nm that have the potential to physically block viruses. They highlighted how electrospinning is one of the most versatile and viable techniques for generating ultrafine fibers, because electrospun ultrafine fibrous filters have shown high filtering efficiency of fine particles and aerosols. For the future, they affirm that electrospun ultrafine fibrous filters have great potential in reusable applications and personal protective devices by incorporating appropriate fibers/polymers with functional materials. In the study of (Bulu¸s et al., 2020), 1%, 5%, and 8% activated charcoal (A.C.)-reinforced PLA nanofiber membranes were produced by the electrospinning technique, obtaining ideal filtration membranes for long-term use, particularly indicated for healthcare workers, as protective equipment, especially in the COVID-19 pandemic. The membranes showed a value $ 98 in terms of BFE showing that these materials have excellent properties that can be preferred in the production of protective equipment and filtration applications in the COVID-19 pandemic control process. Alshabanah et al. (2021) studied biodegradable nanofibrous hybrid membranes of PVA loaded with ZnO and CuO NPs, which were manufactured by electrospinning, evaluating their anti-COVID-19 and antimultidrug-resistant bacteria activities. The morphological structures of these nanofibers membranes were observed by SEM, showing a homogenous pattern of the developed nanofibers, with an average fibrous diameter of 200
250 nm. The antiviral and antibacterial potential capabilities of the nanofibrous membranes were tested in blocking the viral diffusion of SARS-COV-2 and for their activity against a variety of bacterial strains. The results revealed that ZnO loaded nanofibers were more potent antiviral and antibacterial agents than their CuO analogs. This antiviral and antibacterial function is explained by the fact that inorganic metallic compounds have the ability to extract hydrogen bonds with viral proteins, causing viral rupture or morphological changes. The results of the antiviral and antibacterial tests showed the effectiveness of such nanofibrous formulas, not only for medical applications, but also to produce personal protection equipment, such as gowns and textiles.

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8.5.3 Recovery of vapors of organic substances from the air The volatile organic compounds (so-called “VOCs”) are all those liquids that possess a high steam pressure at room temperature (for the Italian law, at 293.15K, steam pressure .0.01 kPa (Dlgs 152/20061—Norme in materia ambientale, 2006)), that is, a boiling point from 50 C to 260 C. From an environmental point of view, their free emissions into the atmosphere must be well attempted and mostly regulated by legal limits, since they have been recognized as contributors to the generation of polluted waste gas flows, as they affect plants, the health of humans, and all animals (Ministero della Salute, 2015), and because in presence of sunlight they react with NOx forming ozone, which is particularly harmful for the atmosphere. Among the most common VOCs, methane, ethane, tetrachloroethane, BTX, formaldehyde, acetaldehyde, and acetone represent the atmospheric pollutants most emitted by chemical and petrochemical industries (Khan & Ghoshal, 2000). Therefore, the control of their emissions is of great concern. In addition to being dangerous to the environment, VOCs also possess a certain economic value linked to the recovery of substances and energy, and for these reasons their recovery by chemical industries is a very important issue (Bodzek, 2000). There are various techniques used for VOCs recovery. They are classified mainly in two macro areas (Fig. 8.9): process and equipment modification, and add-on-control techniques (Khan & Ghoshal, 2000). The substantial difference between the two macro areas is that the first macro area uses techniques that vary the layout of the process, substituents, specific machinery, or raw materials used and give the best results. Nevertheless, they are not always applicable, as it is not always possible to change the layout of a process. The second macro area techniques are easier to be implemented because they are easily applicable and can be used to destroy or retrieve outgoing VOCs. Conventional technologies, currently used in VOCs removal from gases, are the thermal and catalytic oxidation and activated carbon systems. According to the concentration of VOCs in the stream to be treated, different technologies are applied: (1) between 700 and 10,000 ppm, gaseous streams are treated by activated carbon process; (2) for concentrations higher than 20 ppm up to 20% of the lower explosion limit of the gas, the thermal oxidation process results are more suitable (Iulianelli & Drioli, 2020). Unfortunately, these processes do not work well in the case of containing chlorinated compounds, since if not completely burned, they produce toxic gases (Alqaheem et al., 2017).

278 Chapter 8

Figure 8.9 Classification of VOCs control techniques. Reprint from Khan, F. I. & Ghoshal, A. K. (2000). Removal of volatile organic compounds from polluted air. Journal of Loss Prevention in the Process Industries, 13 (6), 527
545 with permission of Elsevier.

Among the techniques of the second macro area related to the recovery of VOCs, membrane engineering represents an important option for the separation of VOCs from gaseous streams. This is allowed by the high chemical stability of specific membranes, which allows separations also for currents in the presence of chlorinated compounds, and works at room temperature, constituting a great advantage in terms of energy saving (Alqaheem et al., 2017). The basic principle is that the VOCs are recovered by membranes for gas separation, using particularly the polymeric membranes characterized by a high permeability to VOCs, but being impermeable to air (Bodzek, 2000). Among the different types, there are nanofibrous membranes that, due to their specific characteristics, can remove micron and submicron particulates, which are particularly suitable for vapor permeation membrane, membrane contactor, and membrane gas separation for VOCs removal from air (Bodzek, 2000). The basic elements of a VOCs membrane-based removal process involve the use of a membrane module, a vacuum pump, and a condensation unit. The use of an vacuum pump

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helps to maintain low VOCs partial pressures on the permeated side, facilitating passage through the membrane, and creating an adequate training force for continuous transfer. After that, the permeate is subject to cooling and condensation to obtain liquid VOCs, allowing the recycling of the gas flow, after separating the rich liquid part of VOCs (Fig. 8.10). Regarding the release, that is, purified air, it is released into the atmosphere, or sent to further purification treatments, based on the level of purity required. The enrichment in VOCs will depend on the nature of the compounds to be separated, on the selective level of the membrane, and on the operating conditions. Theoretically for a given system, enrichment decreases with an increase in permeated side pressure. This is why it is industrially preferred to use a permeated side vacuum pump. Therefore, if the goal is to maintain an important permeating flow, any decrease in the flow through the membrane caused by an increase in permeated pressure must be offset by an increase in the transfer area, a condition that will imply greater costs. The silicone rubber membranes, PDMS, are the most tested for the removal of VOCs such as acetone, toluene, and xylene from air or N2. PDMS has a selectivity from 11 to 25 (Alqaheem et al., 2017; Kimmerle et al., 1988) for acetone removal, while for toluene, the selectivity is around 84 (Alqaheem et al., 2017; Paul et al., 1988). Beyond these, even glassy polymers like PI are also designed to remove VOCs. A polyimide-based membrane produced by Upjohn, PI 2080, was used for several VOCs removal and showed the maximum separation selectivity (460) for p-xylene. PI 2080 has also doubled toluene/air selectivity over the PDMS membrane. As for the removal of methanol and ethanol, the selectivity is higher than 200 (Alqaheem et al., 2017). Purified gas flux Membrane Gas flux with vapours of organics module permeate

Recirculaon

Vacuum pump

Organics aer condensaon

Condensaon unit

Figure 8.10 Membrane separating process for VOCs recovery.

280 Chapter 8 From the cost point of view, membrane-based recovery includes moderate starting costs, due to the purchase of membranes, pumps, etc. The operating costs are lower than other operational technologies, where in this case operating costs are mainly due to the type and life cycle of the membrane used in the process (Khan & Ghoshal, 2000). Nippon Kokan Corp. tested a spiral wound membrane module for gasoline vapor separation and recovery, to reduce the concentration of the gasoline vapor below 5% when released into the atmosphere (Matsumoto et al., 1991). Scholten et al. (2011) developed electrospun polyurethane fibers for the removal of VOCs from air with VOCs absorption and desorption, by demonstrating that PU fibers showed completely reversible absorption and desorption, with desorption obtained from a simple purge with N2 at room temperature. The selectivity of PU fibers toward different vapors, together with ease of regeneration, makes them attractive materials for VOCs filtration. Rebollar-Perez et al. (2011) studied the use of PDMS/α-alumina membrane for vapor permeation, developing a laboratory scale system to remove VOCs from air currents. The membrane would reduce 95% of the content of the VOCs introduced into real concentration conditions, used in the oil industry with a feed pressure equal to 3 bar at operative temperature equal to 21 C. Another type of membrane operation for the application of membrane contactors for gas and VOCs removal from air, which is purely used to capture various polluting emissions through physical or chemical adsorption, is achieved by combining membrane separation technology and chemical absorption technology (Komaladewi et al., 2019). The typical principles of membrane contactors are schematically shown in Fig. 8.11.

Figure 8.11 Schematic drawing of the membrane contactor for the preparation of SLN (Charcosset et al., 2005). Reprint from Charcosset, C., El-Harati, A., & Fessi, H. (2005). Preparation of solid lipid nanoparticles using a membrane contactor. Journal of Controlled Release, 108(1), 112
120 with permission of Elsevier.

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As for the recovery and removal of VOCs at an industrial level through the aid of polymeric membranes, Membrane Technologies and Research Inc. (MTR) implemented a chlorinated VOCs-recovery approach based on a spiral-wound membrane module in a soil vapor extraction demonstration plant (Report-DOE/EM-0614 USA, 2001). GKSS also developed a spiral-wound membrane module for VOCs removal a (Iulianelli & Drioli, 2020).

8.5.4 Air conditioners In order to have an optimal human comfort within living and working spaces, there is a need for environmental conditions such as humidity and temperature within spaces to be controlled. This means that the air inside a building should receive energy to heat the air inside, or that this air should be cooled, in addition to the level of humidity needing to be controlled. This approach can be encompassed in the acronym HVAC—heating, ventilation and air-conditioning. The relevance of HVAC is not only important from a comfort point of view of the single human within a space, but also from an environmental point of view, since it is evaluated that the building sector alone is responsible for about 40% of the energy demand, a percentage of which also includes the energy demands of chillers and air conditioners installed for each construction, that is, it is responsible for almost 40%
50% of the world’s greenhouse gas emissions (Hughes et al., 2011). From an environmental point of view, this is a huge problem because with the increase in the world population, an increase in demand from inhabitants and working spaces is also expected, with the consequent demand of more and more chillers and air conditioners, and thus more energy. Another phenomenon closely linked to the impact of air conditioners in large cities is the so-called “urban heat island” effect. This is a serious issue from an environmental point of view, because it is responsible for the formation of a sort of warm hood over the cities causing thermal inversion, and hence pollution stagnation. The hood is produced by the hot air conditioners, and the hot air, in turn, is reused by the same air conditioners, leading to greater energy consumption in a vicious cycle (US EPA, 2008). Over the past 15
20 years, the research in the field of HVAC has increased significantly with the aim of developing new techniques requiring a lower energy load. Among them, membrane technology has made much progress in this area. This is because the membranes, which function like selective barriers that allow the separation of a species from another, are able to promote the selective permeation of water vapor, a principle that can be used to permit air cooling in the interior of buildings. Among the advantages of membrane technology are compactness, low energy consumption, no phase change, and no need for regeneration phases. For an industrial application, however, membranes with low permeability but very high selectivity are not used practically, since high permeability is a key factor in removing water vapor from a humid air stream on a large scale (Abdollahi et al., 2021).

282 Chapter 8 The main membrane HVAC processes are different, including vacuum membrane dehumidification and membrane evaporative cooling and humidification, where each process has different inlets and outlets, and the membranes used are different as well (Woods, 2014). In the membrane-based air dehumidification process (Fig. 8.12), the driving force is the vapor pressure difference between the feed and permeate sides, with the help of dense-type hydrophilic membrane. The feed is wet air, while the final product is the refrigerated air sent to the conditioned environments. The initial humid air is dehydrated by contact with the membrane, and the permeated water vapor is then released into the atmosphere. To facilitate the separation, a compressor or a vacuum pump is installed on the permeated side so that a low-pressure zone is created. This increases the driving force between the feed and the permeated side, thus increasing the efficiency of the membrane separation. Scovazzo and Scovazzo (2013) suggested a novel isothermal system for removing water vapor from gases using water-selective membranes. The efficiency of the system was more than 200%. Membrane evaporative cooling (Fig. 8.13) is a very promising technology regarding the application of evaporative cooling as a method to cool the environments, maintaining the

Figure 8.12 Schematic of membrane vacuum drying. Reprint from Woods, J. (2014). Membrane processes for heating, ventilation, and air conditioning. Renewable and Sustainable Energy Reviews, 33, 290
304 with permission from Elsevier.

Figure 8.13 Membrane humidification or evaporative cooling. Reprint from Woods, J. (2014). Membrane processes for heating, ventilation, and air conditioning. Renewable and Sustainable Energy Reviews, 33, 290
304 with permission of Elsevier.

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temperature, and operating as a low-cost and energy-efficient technique with a low environmental impact. Membrane evaporative humidification is a technique that is used to control humidity within rooms through the aid of membranes (Woods, 2014). In traditional configurations, evaporative cooling requires the use of stagnant water or recirculation of the same water. However, this condition, without appropriate and constant maintenance, may favor the proliferation of bacteria since the water is in direct contact with the external air (Johnson et al., 2003). For this reason, as an alternative to traditional configurations, hollow fiber membranes employed as wet surfaces present numerous advantages. These membranes, unlike conventional methods, do not allow contact between the stagnant water cited before and the air, thanks to the fact that this interaction takes place through the pores of the membrane, and thus it does not allow the passage of microbes and bacteria due to the small size of the pores (less than 0.1 μm). This means that the aforementioned configurations is much more hygienic than traditional configurations, eliminating the addition of health additives, thus containing management costs. In another work, Johnson et al. (2003) performed an, evaluation of the effectiveness of hollow-fiber membranes for evaporative cooling and showed that a reasonable number of fibers and the membrane surface can provide a cooling efficacy comparable to conventional evaporation cooling equipment. Since many people spend from 70% to 90% of their time in indoor environments and since the internal air quality is from two to five times lower than the external air, it is essential to develop new filtration systems for air purification in closed spaces, especially in recent years because of the COVID-19 pandemic (US EPA, 2015). Ju et al. (2021) produced polyamide-6 electrospun nanofibers with silver NPs through hydrogen-bonds, focusing on air filter membranes with antibacterial and antiviral properties for high-efficiency PM removal. This membrane exhibited high PM2.5 filtration efficiency of 99.99%, simultaneously removing multiple aerosol pollutants, bacteria as Escherichia coli and Staphylococcus aureus, and showing antiviral activity. The electrospinning parameters evaluated were the distance between needle and sample collector (18 cm), the voltage (18 kV), the processing temperature (40 C), and the average flow rate (0.5 mL/h). Shen et al. (2021) with the aim of addressing the challenge of the airborne transmission of SARS-CoV-2, fabricated photosensitized electrospun nanofibrous membranes to effectively capture and inactivate coronavirus aerosols. From tests carried out, with an ultrafine fiber diameter of B200 nm and a small pore size of B1.5 μm, the optimized membranes caught 99.2% of the aerosols of the murine hepatitis virus MHV-A59, a coronavirus surrogate for SARS-CoV-2. The membranes were produced through electrospinning, where the solution

284 Chapter 8 feeding rate, electric field, and electrospinning duration were kept at 0.4 mL/h, 1 kV/cm, and 30 min, respectively. Furthermore, rose bengal (4,5,6,7-tetrachloro-20 ,40 ,50 ,70 tetraiodofluorescein) was used as a photosensitizer for the membranes because of its excellent reactivity in virucidal generation. The membranes were, thus, able to rapidly inactivate 98.9% of MHV-A59 in virus-laden droplets after only 15 min irradiation of simulated reading light. No efficiency reduction for filtering MHV-31 A59 aerosols was observed after the membranes were exposed to both indoor light and sunlight for days. Leung et al. (2020) studied a PVDF multilayer nanofiber filter for simulated airborne novel coronavirus (COVID-19) using ambient nanoaerosols. The nanofiber production technique employed was electrospinning, thanks to its ability to produce better filter media for the filtration of small aerosols by diffusion and interception (Hung et al., 2011). The main parameters studied were high voltage supply (20 kV), distance of the ground collector from the syringe tip (15 cm), and PVDF solution flow rate (0.9 mL/h). The results of this study demonstrated that the produced nanofiber filter qualified as a “N98 respirator” (98% capture efficiency for 300-nm NaCl aerosols) but with a pressure drop that was 1/10 below the conventional N95. PVDF nanofiber filter was revealed to provide good personal protection against the airborne COVID-19 virus and nanoaerosols from pollution based on the N98 standard, and at the same time was 10 times more breathable than a conventional N95 respirator. In another work within the mTAP project (Cordis EU, 2020), an innovative filtration system for internal air purification was proposed. The approach aimed to purify the air by employing microporous ceramic membranes (the method of fabrication was patented) assembled in a filtration unit such as air conditioners. Specifically, these ceramic “smart membranes” can be tailored on the basis of the customers’ needs by modification with specific nanofilms or by changing membrane properties such as the shape, the size, the diameter, or thickness of the pores. Thanks to their properties the resulting membranes are ideal in applications related to filtration/purification of particles and microfiltration.

8.6 Conclusions and future trends Air pollutants are classified as gaseous and particulate substances originating from different sources that cause serious risks for the human health and contribute to climate change. Air cleaning using polymeric, mixed matrix, and inorganics membranes can be applied in a wide range of applications with the aim of improving the quality of air through the filtration mechanism. Membranes present a series of advantages such as high active surface area, tunable morphology, chemical properties, and a wide range of pore structures, thus making the final filtration system highly selective too. In this chapter, the main membranebased technologies for air cleaning and purification as well as the main methods of

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polymeric membranes preparation have been discussed, along with the importance in the selection of the proper membrane materials. The principal applications of membranes related to air cleaning, such as the individual protection filters, air conditioners, and the recovery of vapors of organic substances from the air, have been presented and discussed. Membrane technology is expanding thanks to its flexibility and efficiency and it perfectly fits in facing some of the main issues of the modern society, such as control of environmental pollution. In particular, membrane technology offers many possibilities both as a clean technology and as a cleaning technology. There is still room for improvement and not all the opportunities which membrane processes can offer are fully exploited on a very large scale, undoubtedly membranes will play a pivotal role in addressing the upcoming environmental challenges. In this scenario, nanofibers membranes have gained a huge interest in the field of air filtration thanks to their excellent properties, such as high-specific substitute for mass units, high porosity, and very high filtration efficiency. This chapter clearly evidenced that membranes operations are already a consolidated reality in air purification from polluting substances such as VOCs, COx, NOx, and sulfur compounds, and in the medical/health field for the removal/inactivation of microorganisms such as COVID-19 and bacteria dispersed in the air, especially in closed environments where there is no air recirculation. In addition to air filters, in air-conditioning systems, the research is focused on the engineering development of new configurations in the nanofibrous membranes, especially for applications such as facial masks with antibacterial properties, in a period where the use of masks, due to COVID-19, is practically obligatory, making this research area very attractive and topical (Kumar et al., 2021). Future works and the improvements in the field of air filtration membranes also concentrate on new manufacturing methods aiming at reducing the use of hazardous and dangerous chemicals (Komaladewi et al., 2019). In this direction, many efforts have been put in place by the research community to find new benign chemicals (e.g., biopolymers, green solvents) that will allow the total redesign, in a much more sustainable way, of the production steps of polymeric membranes by phase inversion techniques and by electrospinning. Specifically, in masks and air filter, in addition to possible future green production processes, their future development will play a crucial role in protecting against epidemics like COVID-19. Among the future implications there are the possibilities of reusable masks, antiviral masks, and biodegradable masks. As for each new technology, the economic aspect is the largest brake for a large-scale development, but the advent of new materials, and the shift toward very efficient and modern preparation techniques, such as electrospinning, will more and more foster the implementation of membrane processes on a larger scale in the air-cleaning sector (Zhang, Ji et al., 2021).

286 Chapter 8

List of acronyms A.C. Ag NP BFE CD CHT Covid-19 CTFE DMF ECTFE EIPS ETFE EVOH FEP GO HNT HVAC IGS IR MMM MOF MWCNT NFM NIPS NP PA PAA PAN PCL PCTFE PDMS PEG PEO PES PET PEUU PFA PGA PHA PI PLA PM PM2.5 PMIA PP PPE ppm PPO PS

Activated Charcoal Silver Nanoparticle Bacterial Filtration Efficiency Cyclodestrin Chitosan Coronavirus Disease 19 Chlorotrifluoroethylene Dimethylformamide Copolymer of Ethylene and Chlorotrifluoroethylene Evaporation-Induced Phase Separation Copolymer of Ethylene and Tetrafluoroethylene Poly(Ethylene-Co-Vinyl Alcohol) Fluorinated Ethylene-Propylene (Copolymer of Tetrafluoroethylene and Hexafluoropropylene) Graphene Oxide Halloysite Nanotubes Heating, Ventilation and Air-Conditioning Innovative Gas Systems Infrared Light Mixed-Matrix Membrane Metal
Organic Frameworks Carbon Nanotubes Nanofibrous Membrane Nonsolvent-Induced Phase Separation Inorganic Nanoparticle Polyamide Poly(Acrylic Acid) Polyacrylonitrile Polycaprolactone Polychlorotrifluoroethylene Polydimethylsiloxane Polyethylene Glycol Polyethylene Oxide Polysulfones Polyethylene Terephthalate Poly(Ester Urethane) Urea Copolymer of Tetrafluoroethylene and Perfluoropropylvinylether Polyglycolic Acid Polyhydroxyalkanoate Polyimide Poly lactic Acid Particulate Matter Particulate Matter with Diameters that are Generally 2.5 Micrometers and Smaller Poly(m-Phenylene Isophthalamide) Polypropylene Individual Protection Devices Parts-Per-Million Polyphenylene Oxide Polystyrene

Membranes for air cleaning PTFE PTMSP PU PVA PVDF PVP QF SEM SLN SPEEK TEAB TFE TIPS UV VIPS VOC

287

Polytetrafluoroethylene Polytrimethylsilylpropyne Polyurethane Poly(Vinyl Alcohol) Polyvinylidene Fluoride Poly(Vinyl Pyrrolidone) Quality Factor Scanning Electron Microscope Solid Lipid Nanoparticles Sulfonated Poly(Ether Ether Ketone) Tetraethylammonium Bromide Tetrafluoroethylene Temperature-Induced Phase Separation Ultraviolet Light Vapor-Induced Phase Separation Volatile Organic Compound

List of symbols C D Da J JNS JS M P p r R S T Tg x α λ μ

Concentration Diffusion coefficient in the membrane Dalton or unified atomic mass unit Flux or permeation rate through the membrane Nonsolvent flux Solvent flux Molecular weight Permeability Pressure Pore radius Universal gas constant Solubility Temperature Glass transition temperature Membrane thickness Ideal separation factor or selectivity Free path of the molecule Dynamic viscosity

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13645. Yalcinkaya, F., Yalcinkaya, B., & Jirsak, O. (2015). Influence of salts on electrospinning of aqueous and nonaqueous polymer solutions. Journal of Nanomaterials. Yusuf, A., Sodiq, A., Giwa, A., Eke, J., Pikuda, O., Luca, G. D., Salvo, J. L. D., & Chakraborty, S. (2020). A review of emerging trends in membrane science and technology for sustainable water treatment. Journal of Cleaner Production, 266, 121867. Zhang, H., Xie, Y., Song, Y., & Qin, X. (2021). Preparation of high-temperature resistant poly (m-phenylene isophthalamide)/polyacrylonitrile composite nanofibers membrane for air filtration. Colloids and Surfaces A: Physicochemical and Engineering Aspects, 624, 126831. Zhang, T. C., Roa, Y. S., Vigneswaran, S., Tyagi, R. D., Leong Ong, S., & Kao, C. M. (2012). Membrane technology and environmental applications. Membrane Technology and Environmental Applications, 1
742. Zhang, Z., Ji, D., He, H., & Ramakrishna, S. (2021). Electrospun ultrafine fibers for advanced face masks. Materials Science and Engineering: R: Reports, 143, 100594. Zhu, M., Hua, D., Pan, H., Wang, F., Manshian, B., Soenen, S. J., Xiong, R., & Huang, C. (2018). Green electrospun and crosslinked poly(vinyl alcohol)/poly(acrylic acid) composite membranes for antibacterial effective air filtration. Journal of Colloid and Interface Science, 511, 411
423.

CHAPTER 9

Antifouling membranes for polluted solvents treatment ´l Bahamonde Soria1,2 and Patricia Luis2 Rau 1

Renewable Energy Laboratory, Faculty of Chemical Sciences, Central University of Ecuador, Quito, Ecuador, 2Materials & Process Engineering (iMMC-IMAP), UCLouvain, Louvain-la-Neuve, Belgium

9.1 Introduction Membrane processes are among the most fascinating and fastest growing fields in separation technology. Even though membrane processes are a relatively new type of separation technology, several membrane processes, particularly pressure-driven membrane processes including reverse osmosis (RO), nanofiltration (NF), ultrafiltration (UF), and microfiltration (MF), are already applied on an industrial scale in food, pharmaceuticals, water cleaning, bioproduct processing, and solvent treatment (Huang et al., 2018). Membrane separation processes can be used for a wide range of applications because they can offer significant advantages over conventional separation methods such as distillation and adsorption; compared to these processes, most membrane processes do not involve any chemical, biological, or thermal change of the component. The vast majority of contemporary membrane applications involve aqueous media (seawater desalination, oily wastewater treatment, micropollutant removal from water and drinking water production) and gaseous media (air separation, natural gas sweetening, hydrogen production, and CO2 capture), while organic media remain largely unexplored, so the design of membranes that can operate in organic media is an urgent demand among academic and industrial communities (Huang et al., 2018). This chapter discusses membrane technologies used in the treatment of aqueous and organic streams. Section 9.2 focuses on the surface interactions and fouling mechanisms of membranes used in the treatment of aqueous media. Section 9.3 provides a review of the most common methods for the fabrication of membranes for the treatment of organic solvents, and Section 9.4 gives a brief description of techniques for characterizing and understanding membrane fouling mechanisms.

Current Trends and Future Developments on (Bio-) Membranes. DOI: https://doi.org/10.1016/B978-0-12-824103-5.00006-1 © 2023 Elsevier Inc. All rights reserved.

295

296 Chapter 9

9.2 Membrane technology for aqueous streams Membrane technology has become an indispensable technology platform for water purification, including seawater and brackish water desalination, as well as municipal or industrial wastewater treatment (Alzahrani & Mohammad, 2014). Water purification and desalination include established MF, UF, NF, and RO processes, as well as the emerging forward osmosis (FO) process and membrane distillation (MD). Due to their different pore sizes, the different membrane processes respond to different applications and forms of fouling in water treatment (Werber et al., 2016). Table 9.1 provides an introduction to these processes. As can be seen in Table 9.1, membrane technology is normally affected by membrane fouling. Any material that causes fouling is called a foulant. Fouling results in loss of productivity and a reduction in quality, which is the main impediment to the use of membrane-based processes.

9.2.1 Membrane fouling Membrane fouling can be described as the accumulation of materials (foulants) on the membrane surface or in the membrane pores, resulting in decreased membrane permeate flux. Typically, fouling can be external (contaminants on the external surface of the membrane) or internal (deposition or adsorption of particles or macromolecules on the internal structure of the membrane pores) (Saleh & Gupta, 2016). Membrane fouling is an important and inevitable challenge in all membrane processes. Reduced membrane fouling leads to higher water productivity, reduced cleaning, longer membrane life, and reduced operating and capital costs (Le & Nunes, 2016). The important factors contributing to membrane fouling can be classified into three main categories: operating conditions, membrane characteristics, and contaminant characteristics (Bagheri et al., 2019), as shown in Fig. 9.1. No matter the factor, the fouling effect can be described by Darcy’s law as follows: J5

dV Δp 5 Adt ηRt

(9.1)

Rt 5 Rm 1 Rc

(9.2)

Rm 5 Rmc 1 Rb

(9.3)

Rc 5 R^ c 1 hc

(9.4)

where J is permeate flux, p is transmembrane pressure, is viscosity of solution, Rt is the total membrane resistance, Rm is the flow resistance through the membrane, Rc is the cake

Table 9.1: Characteristics, main materials, and challenges of membrane technology. Membrane Pore size process (nm)

Applications

Species retained

Main materialsa

Ceramics and Polymeric Antifouling and membranes (PES, PVDF, PE, antibiofouling membranes. PAN, PTFE)

-

Surface waters Fresh groundwater Sterile filtration Food and beverage processing Surface waters Fresh groundwater Hemodialysis Sterile filtration Food and beverage processing Surface waters Fresh groundwater Food and beverage processing

Bacteria, turbidity, particles

,1

-

Seawater desalination Brackish (saline) groundwater Surface waters Fresh groundwater

Monovalent ions, low molecular weight

1000
6000

-

MF

100
1000

UF

2
100

NF

1
2

RO

Virus, colloids, macrosolute, algal toxins

Natural organic matter, sugars, divalent ions, removal oil from water

FO

MD

a

Seawater desalination Water desalination Water purification Removal/concentration of ammonium - Resource concentration

Challenges

Salts, ammonium

Membranes with tailored selectivity, able to distinguish solutes of similar size. New Materials such as polyetherketone, crosslinked polyimide and polyazoles to new applications other than water purification. Cost, scale up, chlorineCellulose esters TFC membranes constituted by a resistant membranes, highboron rejection, rejection porous polysulfone of regulated and emerging substrate and a thin trace contaminants and polyamide layer antifouling membranes. Modified membranes and biomembranes. Improve pore wettability (coating with a highly hydrophilic polymer like polydopamine) and improve flux, and fouling resistance. PVDF, PTFE and PP New materials to enhance the mechanical strength and long-term stability of the membrane. Fouling of membrane. NIPS. It is an integrated porous asymmetric membrane with a selective layer on the top or a nonselective porous structure (PES, PVDF and PAN)

PAN, polyacrylonitrile; PE, polyethylene; PES, poly(ether sulfone); PP, polypropylene; PTFE, polytetrafluorethylene; PVDF, poly(vinylidene fluoride).

298 Chapter 9

Parameters related to membrane fouling

xMaterial x Configuraon xHydrophobicity Membrane xSurface porosity characteriscs xPore Size xPore size distribuon xMolecular weight cut-off xElectric field x Configuraon x Cross-flow velocity (CFV) x Hydraulic retenon me x Permeate flux Operang x Filtraon me condions x Transmembrane pressure x Temperature x others

Type of foulants

x Biofouling x Colloids xInorganic precipitates x Organic precipitates xParculates

Figure 9.1 The most important contributing factors to membrane fouling.

layer resistance, Rmc is the clean membrane resistance, Rb is the resistances caused by pore blockage, R^ C is the specific resistance, and hc is the cake height. The pressure drop is the pressure difference between the inlet and the outlet due to the resistance caused by the device. It is often due to the various additional resistances during the filtration process as a result of the polarization with subsequent fouling and a cake resistance. Polarization is the accumulation of retained species adjacent to the membrane and is known as concentration polarization (solutes) or particle polarization (particles). By definition, polarization is a reversible phenomenon and once it becomes irreversible it is called fouling (Fane et al., 2006). After this, the concentration at the membrane surface (Cw) will be greater than in the bulk feed (CB). A well-known film model can provide a useful relationship for Cw in crossflow operation, Cw 5 CB exp ðJv =kÞ

(9.5)

where Jv is permeate flux and k is the boundary layer mass transfer coefficient, which increases with crossflow and decreases with molecular weight, normally the diffusivity (D) over the boundary layer thickness (δ) is replaced by the mass transfer coefficient since the diffusion is a predominant mass transfer mechanism (Dδ  k) (Zhang et al., 2020). This equation is important as it shows that the surface concentration, Cw that can determine fouling, is very dependent on the Jv/k ratio.

Antifouling membranes for polluted solvents treatment 299 Recently, Artificial Intelligence (AI) and machine learning have been proposed as new tools to predict, model, and optimize the operating parameters related to membrane fouling, as well as to classify the fouling-causing microorganisms and recognize the membrane fouling pattern and mechanism (Bagheri et al., 2019). This opens an interesting avenue of exploration for future research.

9.2.2 Fouling classification Membrane fouling can be classified according to the type of fouling and can be divided into five different types: biofouling, colloids, inorganic precipitates, organic precipitates, and particulates (Zhang et al., 2020). Table 9.2 provides their definition and most common foulants: Table 9.2 summarizes the types of foulants that can be incorporated into membranes. It is not easy to reach a general conclusion about which type of fouling in membranes is more dangerous for the membrane lifetime, since there may be different interactions and fouling mechanisms for each fouling agent.

9.2.3 Fouling mechanisms and interpretation Since the mechanisms of fouling are not well-known, they can be studied by classifying them into four general types: Table 9.2: Types of foulants with examples of each type. Parameters related to membrane fouling

Category

Definition

Fouling characteristics

Biofouling Colloids

Biofilm forms on the membrane. Accumulation of particles on the membrane surface and inside the membrane pores, forming a cake layer. Precipitation deposits result in bulk and membrane crystallization.

Inorganic precipitates or scaling Organic precipitates

Example foulants

Bacteria, viruses, and fungi Metal hydroxides, colloidal silica oxyhydroxide and Clays and accumulated particles Oxides, hydroxides and calcium and inorganic salts (CaSO4, CaCO3, SiO2, and BaSO4) Biological substances and Adsorption of natural organic compounds on membrane, causing gel macromolecules (oil, macromolecules, proteins, formation. antifoaming agents, fulvic acid, polysaccharides, and polyacrylic polymers)

300 Chapter 9 Pore plugging/blocking: caused by a complete blockage of the pore, which reduces the active membrane area, it is due to colloids or aggregates that block the entrance or the internal way through the pores, depending on the feed rate. Pore restriction: caused by a reduction in pore diameter due to adsorption/deposition of particles that reach the surface and partially block it or adhere in the inactive region. This leads to a reduction of the active membrane area. Cake formation/surface: similar to the previous ones, it is caused by individual particles, aggregates, and precipitates, but the difference is that these particles neither enter the pores nor seal them; rather, they form a cake on the membrane surface. It is due to the raised concentration on the membrane surface, which becomes the resistance of the cake, in addition to the resistance of the membrane itself. Biofouling: caused by microorganisms, the most common type is a surface deposition due to bacterial adhesion and biofilm growth, resulting in a cake composed of bacterial colonies and expressed biopolymer. The occurrence of membrane fouling during produced water treatment is high owing to the presence of potential foulants in produced water. Moreover, the biofouling mechanism is more prevalent in the processing of water with high nutrient availability as wastewater. During operation, a membrane may go through several fouling stages. Fig. 9.2 depicts the flow stages of a membrane operated under constant pressure conditions. Fig. 9.2 depicts four possible phases during membrane fouling. Phase I is a possible change during water flux testing of the new membrane, as a result of compaction fouling. Phase II is the initial drop in flux when the process is put into operation, this small drop is normally due to concentration polarization, pore clogging, and adsorption interactions (P). Phase III is the long-term operation during which the flux usually continues to decrease, due to fouling deposition, fouling adsorption (AD), and cake consolidation, and finally phase IV is the recovery phase during membrane cleaning (Fane et al., 2006). In turn, the ideal performance of a fouling-free membrane is also shown in discontinuous lines. These results suggest the need for antifouling membranes capable of extending membrane lifetime and resembling ideal behavior or not suffering a sudden decrease in flux ratio (Jv/Jo), where Jo is the initial flux at the beginning of the filtration process.

9.2.4 Membrane cleaning strategies Cleaning can be defined as “a process where material is relieved of a substance, which is not an integral part of the material” (Al-Amoudi & Lovitt, 2007). It is important to know the type of process and qualitative and quantitative information about the feed stream and

I. Initial solvent 2. Initial flux III. Long term flux flux decline drop decline Jv1 FLUX

CF

I. Cleaning

FD AD CC

P

Jv2

Ideal Flux

Water flux before use

J v3 Water flux after clean

2

3

0 10 10 10

1

10

2

10

3

10

4

10

TIME (s) Figure 9.2 Typical flux history during membrane fouling (Fane et al., 2006). Modified from Fane, A. G., Xi, W., & Rong, W. (2006). Membrane filtration processes and fouling. In Interface science in drinking water treatment (pp. 109
132). https://doi.org/10.1016/S1573-4285(06)80076-1. Elsevier Ltd.

302 Chapter 9 retained components in the membrane, which gives an indication of the type of fouling (AlAmoudi & Lovitt, 2007). Based on these observations, a membrane cleaning or membrane modification method can be formulated. The membrane cleaning methods can be classified into five main categories; chemical, mechanical, gas cleaning, electrical (nonconventional) methods, and biofilm removal/ control. 9.2.4.1 Chemical cleaning methods and agents Chemical cleaning is considered as the most effective approach to recover membrane permeability and remove irreversible fouling (Aghapour Aktij et al., 2020), the most common used chemicals are (1) acids (e.g., citric, sulfuric, formic, oxalic and nitric acid), normally used for removing scales and metal dioxides; (2) bases (e.g., NaOH), used to clean (hydrolyze or solubilize) membranes fouled by organic and microbial foulants; (3) chelating agents (e.g., EDTA), used to removal of divalent cations, such as calcium and barium; (4) oxidants and disinfectants (e.g., H2 O2, NaOCl, and peroxyacetic acid), they oxidize typical functional groups found in organic macromolecules to carboxyl, ketonic, and aldehyde groups, which increase their hydrophilicity and facilitate their degradation and detachment from the membrane surface; and (5) surfactants (e.g., detergents), used to emulsify, disperse, and condition the surface. They can help clean membranes, forming micelles with fats, oils, and proteins in water. In addition, they can alter the functions of bacterial cell walls, contributing to biofouling cleanup (Porcelli & Judd, 2010; Saleh & Gupta, 2016; Zondervan & Roffel, 2007). In chemical cleaning, the cleaning agent must reach the fouling agent at concentrations high enough to reduce the interaction forces of the contaminant on the membrane and thus allow its physical removal (Fig. 9.3). Thus the most suitable cleaning agent must be chosen carefully, since it will depend on the nature of the foulant, i.e., organic/inorganic, acid/base, and the state of charge (Zondervan & Roffel, 2007). 9.2.4.2 Mechanical and physical methods These methods include, for example, vibration (moving and rotating the membrane), hydrodynamic forward or backward flushing, permeate back pressure, air spurge, and automatic sponge ball cleaning. These methods depend on mechanical treatment to dislodge and remove foulants from the membrane surface. The backpulsing method is most commonly used for ceramic membranes (Mulder, 1996). Which can be carried out by forcing the permeate (nitrogen or other gas can be used as backpulsing) back through the membrane by reverse transmembrane pressure (Fig. 9.4). Nevertheless, the application of these methods usually results in more complex control and design of the equipment.

Antifouling membranes for polluted solvents treatment 303 1 Fouled membrane and Bulk Reaction

Permeate Membrane

Foulant materials Retentate

2 Bulk transport to and into the fouling layer

Permeate Membrane

Foulant materials

3 Reaction with foulants

Foulant Permeate Membrane materials Retentate

4 Transfer of modified contaminatns to solution and then to bulk solution.

Foulant materials Permeate Membrane

Retentate

Figure 9.3 Conceptual electrostatic equilibrium model for membrane cleaning (Porcelli & Judd, 2010). Modified from Porcelli, N., & Judd, S. (2010). Chemical cleaning of potable water membranes: A review. Separation and Purification Technology, 71(2), 137
143. https://doi.org/10.1016/j. seppur.2009.12.007.

304 Chapter 9

Figure 9.4 Overview of membrane before and after backpulsing in MF and UF processes. CB, CS, and CP are the solute concentration in the bulk, near the membrane surface, and in the permeate, respectively (Gao et al., 2019). Modified from Gao, Y., Qin, J., Wang, Z., & Østerhus, S. W. (2019). Backpulsing technology applied in MF and UF processes for membrane fouling mitigation: A review. Journal of Membrane Science, 587(February). https://doi.org/10.1016/j.memsci.2019.05.060.

9.2.4.3 Cleaning with gas Typically, these methods use air, air/water flow, CO2, and others. The air flushing or air sparging method is used to remove external fouling and to reduce the cake layer deposited on the membrane surface (Alpatova et al., 2020). 9.2.4.4 Electrical or nonconventional methods Within these methods there are techniques such as osmotic backwashing with hypersaline solution, or methods such as ultrasonic, electric, and magnetic fields or electrochemical. Ultrasound is predominantly caused by cavitation. During the rarefaction phase, the medium (normally liquid) is subject to a negative net pressure and ultrasonic cavitation is triggered (Fig. 9.5) (Alventosa-Delara et al., 2014). Cavitation bubbles collapse in the compression phase, leading to the formation of hotspots (specifically in aqueous solutions) with increased local temperatures (5000K) and pressures (1000 atm) (Ashokkumar & Grieser, 2005). The high released energy from the collapse of the cavities overcomes the foulant
membrane interactions, thus removing portions of the fouling layer from the membrane surface and/or preventing fouling accumulation (Maskooki et al., 2010). Electric field is based on a phenomenon called electrokinetics, which applies a direct electric field during membrane filtration to prevent charged foulants from adhering to the membrane surface. One of the main advantages is that the electric field can be applied continuously or intermittently during the work cycle (Fig. 9.5) (Li et al., 2018).

Figure 9.5 (A) Ultrasonic removal of fouling layer from the surface of the membrane (Aghapour Aktij et al., 2020). (B) Diagram of membrane cleaning process using an electric field to mitigate membrane fouling in a crossflow filtration cell (Li et al., 2018). Modified from Aghapour Aktij, S., Taghipour, A., Rahimpour, A., Mollahosseini, A., & Tiraferri, A. (2020). A critical review on ultrasonic-assisted fouling control and cleaning of fouled membranes. Ultrasonics, 108(July), 106228. https://doi.org/10.1016/j. ultras.2020.106228.

306 Chapter 9 9.2.4.5 Biofilm removal and control Biofouling can be reduced by (1) controlling biological fouling during the service and offline modes, using a continuous or periodic introduction of a chemical biocide; and (2) using other agents such as ozone and biofilm prevention with ultraviolet light disinfection (Saleh & Gupta, 2016). The main disadvantage of conventional membrane cleaning strategies is that they may require sophisticated equipment or a large number of reagents. Therefore, prevention or reduction of unwanted interactions between contaminants and the membrane surface may be an essential way to control contaminant adhesion and this could be achieved by modification of the membrane used.

9.2.5 Antifouling membranes As we have seen in this chapter, membrane fouling is an important and inevitable challenge in all membrane processes. Lower membrane fouling allows higher water productivity, less cleaning, and longer membrane lifetime, as well as reduced capital and operating costs (Le & Nunes, 2016). Therefore, innovation concerning the use of new materials in the membrane technology sector is a challenge, considering cost and large-scale production. However, the main improvement required for membrane processes is still the resistance to fouling (biological, organic, and fouling) and to chlorine as a cleaning agent. Decades of investigation have been dedicated to this topic (Nunes et al., 2020). However, in order to develop new membranes, it is necessary to know the process of membrane fouling. This process can be studied from two approaches: (a) the minimization of Gibbs free energy of the system (thermodynamic point of view); or (b) the complicated foulant
membrane and foulant
foulant interactions (physicochemical point of view). In turn, the fouling interactions on each foulant can be simplified in three approach
adsorption
accumulation stages (Fig. 9.6). (1) The foulants (or their precursors) approach or contact on a membrane surface driven by transmembrane hydraulic pressure. (2) These foulants adsorb or attach onto the membrane surface via electrostatic, hydrophobic, van der Waals, hydrogen-bonding, or other interactions. (3) Foulants accumulate or aggregate together with each other and then form cake, gel, oil, biofilm, or scaling layers on the membrane surface (Brady & Singer, 2000). Thus antifouling surfaces can be achieved by the following mechanisms: (1) fouling resistant mechanism, resists foulants via inhibiting direct contacting and interaction based on hydration layer effect; (2) fouling release mechanism, drives away foulants via minimizing interaction intensity based on low-surface-energy effect; and (3) fouling attacking mechanism, decomposes foulant

Antifouling membranes for polluted solvents treatment 307

Figure 9.6 Schematics of the three-stage membrane fouling behaviors and proposed antifouling mechanisms (Zhao et al., 2018). Modified from Zhao, X., Zhang, R., Liu, Y., He, M., Su, Y., Gao, C., & Jiang, Z. (2018). Antifouling membrane surface construction: Chemistry plays a critical role. Journal of Membrane Science, 551(92), 145
171. https://doi.org/10.1016/j.memsci.2018.01.039.

accumulation via cell inactivation and foulant oxidization based on active interaction/ reaction effect (Schneider et al., 2014; Zhao et al., 2018). Strategies for the development and design of antifouling membranes generally consider changing membrane characteristics or properties such as chemical structure (functional groups, charge, and hydrophilicity) and morphology (pore size, surface roughness, or surface pattern) to obtain characteristics such as high hydrophilicity, negative surface charge, and low surface roughness, which are desirable characteristics for a low fouling propensity (Le & Nunes, 2016). Moreover, the rational combination of defense mechanisms also plays crucial roles in elevating the overall antifouling properties of membranes. In addition, the modification of commercial membranes could also help to produce a potentially sustainable solution to prevent fouling. In order to have a better understanding of strategies to minimize membrane fouling, these can be divided into two groups: membrane design and manufacturing and surface modification of membranes. 9.2.5.1 Membrane design and manufacturing methods Established water purification processes such as MF, UF, NF, and RO, as well as the emerging reverse osmosis (FO) process use a wide range of membrane materials such as polymeric and inorganic membranes to produce stable membranes. However, membrane fouling can affect

308 Chapter 9 both inorganic and polymeric membranes. Finding new materials able to overcome the trade-off between antifouling capacity and permeability has become an urgent necessity. It is well-known that polymeric membranes are by far the most widespread, due to their high processability and low cost. Recent advances in methods for controlling the structure and chemical functionality in polymer films can potentially lead to new classes of membranes for water purification. Polymeric membranes and their corresponding fabrication methods are discussed in this section. There are two main manufacturing methods (phase inversion membranes and thinfilm composite polyamide membranes) which will be discussed in this section, as well as the design of high-selectivity membranes. 9.2.5.1.1 Phase inversion membranes

This process involves the controlled precipitation of a dissolved polymer in a thin film to produce a porous membrane structure (Baker, 2012; Nunes et al., 2020; Werber et al., 2016). The main phase inversion technique is nonsolvent-induced phase separation (NIPS), in which a film of polymer dissolved in solvent (nonpolar phase) is immersed in a water bath (polar phase). These two phases form the solid membrane matrix (from the polymerrich phase) and pores (from the polymer-poor phase). Other phase inversion techniques include controlled solvent evaporation, in which a volatile solvent is allowed to evaporate from a liquid film that includes polymer and nonsolvent, and phase separation is thermally induced. 9.2.5.1.2 Thin-film composite polyamide membranes

These membranes comprise a nonporous, highly crosslinked polyamide selective layer and an underlying porous support layer, typically made of polysulfone. TFC polyamide membranes can achieve water permeability and salt rejection far exceeding the asymmetric cellulose
acetate-based membranes. The polyamide selective layer is formed through interfacial polymerization of a diamine, commonly, m-phenylenediamine (MPD) for RO, FO, and NF, and piperazine (PIP) for NF with a triacyl chloride, particularly trimesoyl chloride (Lau et al., 2015; Werber et al., 2016). In membrane manufacturing high fouling (accumulation of substances on the membrane surface or within the membrane pores) propensity is a major obstacle for efficient membrane technology. The use of synthetic polymers in the manufacture of membranes, such as polyvinylidene fluoride (PVDF), polysulfone, polyethersulfone (PES), and polyacrylonitrile (PAN) (Cheryan, 1998) have many advantages. However, they are also fairly hydrophobic, which can exacerbate organic and biological fouling through increased adsorption of foulants to the membrane surface and interior pores (Zhu et al., 2016).

Antifouling membranes for polluted solvents treatment 309 On the other hand, TFC polyamide membranes used in RO, FO, and NF are highly susceptible to all three types of fouling, largely owing to a combination of surface morphology, hydrophobicity, and charge. But MPD-based TFC membranes are also fairly hydrophobic, thereby increasing rates of organic and biological fouling (Herzberg & Elimelech, 2007). One of the most important challenges is to reduce the high surface roughness of MPD-based TFC membranes in order to decrease the fouling. One of the most promising measures of membrane manufacturing is designing highly selective membranes (Werber et al., 2016). Both phase inversion and TFC membranes are prone to organic and biological fouling due to their inherent chemical and physical surface properties. Therefore, clever design of highly selective membranes or appropriate tailoring of membrane surface chemical properties can substantially improve their resistance to fouling. 9.2.5.1.3 Designing highly selective membranes

The design of the water channels can help to produce a change in the movement of water through the membrane. These subnanoporous water channels, if well designed, could offer a significant improvement in desalination performance. An important method for producing selective membranes is the use of subnanoporous materials, including aquaporin membrane protein, single-wall carbon nanotubes, selfassembled channel-forming macrocycles, and single-molecule synthetic water channels (Fig. 9.7). In addition, selective coating can be used, including inverse hexagonal channels, twisted channels formed in bicontinuous cubic phase using polymerizable surfactants, and graphite-based structures with graphite oxide or reduced graphite oxide (Goh et al., 2013; Tang et al., 2013; Werber et al., 2016). Finally, controlled formation of the near-isoporous UF membrane using block copolymers can also be used (Peinemann et al., 2007). 9.2.5.2 Surface modification of membrane Surface engineering is indispensable for antifouling membrane design. Normally, antifouling membranes of MF and UF can be obtained by postmodification of commercial membranes (surface modification) or in situ modification of the phase inversion process (3D modification). In the case of antifouling NF and RO membranes, they can be obtained via not only the postmodification method (surface modification), but also the construction of a new or alternative antifouling-functionalized separating barrier on porous substrates (barrier layer modification), which has a high solute rejection (Zhao et al., 2018). Therefore, research interest in the construction of antifouling membrane surfaces has grown in recent years. In order better to understand the latest efforts in exploring membrane fouling mechanisms, this section will be divided into two groups: (1) advanced antifouling strategies (passive

310 Chapter 9

Figure 9.7 (A) Selective membranes formed with: carbon nanotubes, graphene based frameworks, aquaporin, synthetically designed nanochannel and polymerizable surfactants (Tang et al., 2013). (B) Controlled formation of the near-isoporous ultrafiltration (pore size 5
50 nm). Modified from Galiano, F., Figoli, A., Deowan, S. A., Johnson, D., Altinkaya, S. A., Veltri, L., De Luca, G., Mancuso, R., Hilal, N., Gabriele, B., & Hoinkis, J. (2015). A step forward to a more efficient wastewater treatment by membrane surface modification via polymerizable bicontinuous microemulsion. Journal of Membrane Science, 482, 103
114. https://doi.org/10.1016/j.memsci.2015.02.019.

Antifouling membranes for polluted solvents treatment 311 fouling resistance and fouling release and active antifouling on and off the surface) and (2) advanced methods for the fabrication of antifouling membrane surfaces such as surface bioadhesion (bioinspired). 9.2.5.3 Advanced antifouling strategies Since the fouling mechanism varies from foulant to foulant, fabrication of antifouling membrane surfaces can be based on two strategies: passive (prevents the initial adsorption of foulants on the membrane surface without affecting the intrinsic features of the foulants), and active (eliminates proliferative fouling by destruction of the chemical structure and inactivation of the cells). 9.2.5.3.1 Passive antifouling membranes

The passive antifouling membranes rely on manipulating the physicochemical and/or topological structures of the membrane surface to weaken the foulant
membrane surface interactions and thus prevent foulants from adsorption or settlement. So, passive antifouling membranes can prevent the foulants from arriving at the membrane surface (fouling resistance) or drive the attached foulants away from the membrane surface (fouling release) (Choudhury et al., 2018). 9.2.5.3.1.1 Fouling resistance strategies To have antifouling characteristics, a membrane must possess certain conditions such as being hydrophilic, electrically neutral, hydrogen bond accepting, and not hydrogen bond donating (Ostuni et al., 2001; Wei et al., 2014). Particularly in the case of hydrophilic surfaces, they can suppress nonspecific interactions and prevent contaminants from adhering to the membrane surface, which is known as “fouling resistance.” Typically, membrane hydrophilicity is often inspired by the hydrophilicity of cell membranes and numerous hydrophilic materials, such as poly (ethylene glycol) (PEG)-based polymers, zwitterionics, glycomimetics, and peptidomimetics, which are often used for this purpose (Choudhury et al., 2018; Misdan et al., 2016). This fouling resistance strategy can be explained by two main mechanisms (Fig. 9.8): the steric repulsion effect and formation of a hydration layer. The steric repulsion effect is governed by entropic instability and formation of a hydration layer prevents effectively the nonspecific adsorption of foulants by the free energy variation arising from dehydration entropic effects (Zhang et al., 2016). With these modifications the adsorption of foulants (for example proteins) leads to compression of the extended polymer brushes and the free mobility of the polymer chains is restrained. This will create unfavorable entropy loss, making this protein adsorption entropically unfavorable. On the other hand, the hydrophilic polymer brushes can build a compact hydration layer on the surface through hydrogen bonding or ionic solvation,

312 Chapter 9

Figure 9.8 (A) Hydrophilic membranes with fouling resistance properties. (B) Heterogeneous membranes with the coexistence of hydrophilic and nonpolar low surface energy segments exhibit both fouling resistance and fouling release properties (Zhao et al., 2014). Modified from Zhao, X., Su, Y., Li, Y., Zhang, R., Zhao, J., & Jiang, Z. (2014). Engineering amphiphilic membrane surfaces based on PEO and PDMS segments for improved antifouling performances. Journal of Membrane Science, 450, 111
123. https://doi.org/10.1016/j.memsci.2013.08.044.

effectively preventing the nonspecific adsorption of foulants (Krishnan et al., 2008; Zhang et al., 2016). In addition, some nanomaterials can also impart fouling resistance to membrane surfaces. Particularly, inorganic NPs, like metals (e.g., Ag, Cu, Zn) metal oxides (e.g., SiO2, TiO2, ZnO, Fe3O4, Al2O3, and ZrO2) (Zhang et al., 2013), zeolite and boehmite and carbon-based

Antifouling membranes for polluted solvents treatment 313 nanomaterials (CBNs), like carbon nanotubes (CNTs) and graphene oxide (GO) (Schneider et al., 2014; Zhao et al., 2018) have attracted considerable attention because of their superior functionalities for ameliorating the fouling resistance property of the membrane surface (Zhang et al., 2016). Most of these nanomaterials are intrinsically hydrophilic, which can increase the number of hydrogen bonding sites at the membrane surface, thereby allowing the formation of an interfacial layer of tightly bonded water molecules that are highly oriented and have slow dynamics. 9.2.5.3.1.2 Fouling release strategies Hydrophilic membranes usually show a high recovery of the permeate flux, however, a significant decrease of the flux during the filtration process is also common (Zhang et al., 2016). Thus fouling cannot be alleviated simply by membrane hydrophilization, due to hydrophilic membrane surfaces successfully resisting fouling caused by nonmigratory foulants such as biomacromolecules and natural organic matter, but often failing to substantially resist fouling caused by spreadable foulants, especially oils (Chen et al., 2011). A membrane self-cleaning surface inspired by natural lotus wax has directed the construction of surfaces with low surface energy. This strategy aims to weaken the interfacial bonds so that attached foulants are more readily removed from the depositing surfaces at low hydrodynamic shear forces, which is known as “fouling release” (Choudhury et al., 2018; Zhao et al., 2014). Creating nanoscale chemical heterogeneities that enhance thermodynamically unfavorable interactions between the surface and the fouling agents is one antifouling strategy that can be employed. To this end, modifiers containing silicon- or fluorine-based segments with low nonpolar surface energy and a low Young’s modulus could be suitable candidates to facilitate fouling release (Zhang et al., 2016). Nowadays, a variety of amphiphilic copolymers containing hydrophilic segments (e.g., PEG) and nonpolar, low surface energy segments (e.g., fluoroalkyl and semifluorinated side chains and perfluoropolyether segments) are explored as amphiphilic antifouling coatings (Dimitriou et al., 2011; Sundaram et al., 2011; Zhang et al., 2016). In turn, polymers with silicone or alkyl segments can also be used to release scale and develop environmentfriendly antifouling coatings (Fig. 9.8B). Finally, it is possible to create heterogeneous antifouling surfaces with the union of various block-like copolymers containing hydrophilic poly(ethylene oxide) or zwitterionic segments with low surface energy fluorine-based or silicone-based segments (Fig. 9.8B). It is also possible to construct heterogeneous hybrid membranes with stable coexistence of amphiphilic copolymers and inorganic NPs on the membrane surface 9.2.5.3.1.3 Active antifouling strategies The passive antifouling strategies can show limitations, owing to their inability to suppress the colonization of bacteria. An alternative strategy is to

314 Chapter 9 construct antibiofouling membrane surfaces that can actively inhibit microbial colonization and prevent biofilm formation. Active strategies rely on the presence of antimicrobial agents, which can kill bacteria by interfering with biochemical pathways. These strategies can be classified into off-surface and on-surface active antifouling strategies. The off-surface active antifouling strategies are based on releasable antimicrobial agents. These strategies allow the leaching of antibacterial compounds from the membrane surface into the biological milieu, or through generating reactive oxygen species (ROS) via catalytic reactions facilitated by nanocatalysts on the membrane surface. Normally, for the antibacterial release biocidal metal-based nanomaterials such as silverbased and copper-based are commonly applied as releasable antimicrobial agents for fabrication of antibiofouling membranes (Kim & Van Der Bruggen, 2010; Soleymani Lashkenari et al., 2019; Zhang et al., 2016; Zhu et al., 2016), because they have antimicrobial properties against a broad spectrum of microorganisms, from Gram-positive to Gram-negative bacteria and microalgae (Choudhury et al., 2018). The off-surface active antifouling properties are usually attributed to the free ions released, such as Cu1, Ag1, Zn1, and others from metal-based nanomaterials. The antibacterial properties of some ions such as Ag1, Cu1, and Zn1 are well-known; the antibacterial mechanism is complicated but this mainly includes the disruption of ATP production and DNA replication (mutation) (Fig. 9.9). The main inconvenience of this strategy is the depletion of antimicrobial agents, because the agents are exposed off-surface. The on-surface active antifouling strategies are based on unreleasable antimicrobial agents. On-surface strategies use unreleasable antibacterial agents that kill microbes on contact. In this strategy, the antibacterial agents are directly introduced onto the membrane surface to target attached cells through different physical or chemical mechanisms. Cationic polymeric materials are used for this purpose which have cationic antimicrobial groups as quaternary ammonium (QA), phosphonium, guanidinium and other. Of these, the most commonly used are QA-based polycations such as quaternized polyethylenimine and chitosan N-alkylated poly(4-vinyl-pyridine) (P4VP) and quaternary derivatives of poly (ester-carbonate), acrylic acid, and cellulose (Choudhury et al., 2018; Kolesnyk et al., 2020; Nunes et al., 2020; Susanto et al., 2020; Zhang et al., 2016). Furthermore, a range of CBNs have cytotoxic bacteria activity. Particularly, CNTs and graphene-based nanomaterials (GBNs) exhibit excellent bacterial cytotoxicity due to their unique physicochemical properties (Manawi et al., 2016; Shabani et al., 2020).

Antifouling membranes for polluted solvents treatment 315

Figure 9.9 Mechanisms of toxicity of nanoparticles (NPs) and their ions to produce free radicals, resulting in induction of oxidative stress (i.e., reactive oxygen species ROS), resulting in bacterial death (Hajipour et al., 2012). Modified from Hajipour, M. J., Fromm, K. M., Akbar Ashkarran, A., Jimenez de Aberasturi, D., Larramendi, I. R. de, Rojo, T., Serpooshan, V., Parak, W. J., & Mahmoudi, M. (2012). Antibacterial properties of nanoparticles. Trends in Biotechnology, 30(10), 499
511. https://doi.org/ 10.1016/j.tibtech.2012.06.004.

For CNTs various cytotoxic mechanisms have been hypothesized, such as physical membrane rupture, oxidative stress and disruption of intracellular metabolic pathways. In the case of GBNs they include graphene, GO, and reduced GO (rGO) (Fig. 9.10). The bacterial cell membrane is usually the membrane damaged by two main mechanisms: (1) puncturing and penetration through the lipid bilayer by atomically sharp edges of graphene, sheet adhesion on the cell membrane surface and lipid extraction by the graphene sheet; and (2) peroxidation by oxidative stress (Nel et al., 2006; Smith & Rodrigues, 2015; Zhang et al., 2016). In addition, nanocomposite agents that integrate both types of releasable and nonreleasable antimicrobial agents have been recently designed and synthesized. This kind of nanocomposite agent will open a new avenue for developing water treatment membranes with excellent active antifouling features.

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Figure 9.10 GO sheets antimicrobial activity on a membrane. Modified from Khanzada, N. K., Rehman, S., Leu, S. Y., & An, A. K. (2020). Evaluation of antibacterial adhesion performance of polydopamine cross-linked graphene oxide RO membrane via in situ optical coherence tomography. Desalination, 479(October 2019), 114339. https://doi.org/10.1016/j.desal.2020.114339.

The revised surface modification techniques can be 1D techniques, i.e., they only produce thin films on the surface of the membrane but two other recently developed modification approaches exist: 2D modification (formation of nanotubes, nanowires, or nanocables), and 3D modification (more complex structures, such as brushes), which further improve the antifouling properties and water flow (Fig. 9.11). These techniques can be performed by different methods of surface adhesion, among which bioadhesion has attracted attention in recent research.

9.2.6 Bioadhesion (bioinspired adhesion chemistry) The concept of bioinspired adhesion is due to the use of mussel adhesive proteins (MAPs). |Catecholic-, amino acid-, and 3,4-dihydroxyphenylalanine (DOPA)-rich MAPs allow mussels to adhere to a variety of materials with high hydrogen-bonding strength in wet conditions (Tang et al., 2013). Dopamine (Fig. 9.12), containing both amine and catechol groups, exhibits a similar molecular structure to DOPA and has moved into the spotlight as an effective novel broad-range artificial adhesive coating adhesive (Liebscher et al., 2013). The multifunctional polydopamine (PDA) coatings can be generated by in situ spontaneous oxidative self-polymerization of dopamine on a wide range of substrates in an alkaline solution under mild conditions (Ye et al., 2011; Zhao et al., 2018).

Antifouling membranes for polluted solvents treatment 317

Figure 9.11 Schematics of water transport through (A) nanocrystals embedded rGO laminates, (B) stacked rGO sheets, and (C) nanoporous crystal. Modified from Guan, K., Zhao, D., Zhang, M., Shen, J., Zhou, G., Liu, G., & Jin, W. (2017). 3D nanoporous crystals enabled 2D channels in graphene membrane with enhanced water purification performance. Journal of Membrane Science, 542(August), 41
51. https:// doi.org/10.1016/j.memsci.2017.07.055.

PDA can tightly adhere to virtually all solid surfaces through multiple interactions, such as covalent bonding, coordination, hydrogen bonding, and π
π stacking (Liebscher et al., 2013; Zangmeister et al., 2013). Besides, the residual catechol, quinone, and amine groups of PDA could enable further reactions with functional molecules (Ye et al., 2011). The quinone groups could react with nucleophilic amine and thiol groups via the Michael addition or Schiff base reactions (Bahamonde et al., 2020; Hajipour et al., 2012; Zhang et al., 2016; Zhang et al., 2013). Dopamine and its derivatives can be used as antifouling modifiers for membranes individually, due to the hydrophilicity induced by the zwitterionic groups (Misdan et al., 2016). Fouling resistance of PDA can be attributed to the hydrophilicity and electrostatic repulsion of the protonated amine groups of PDA (Barclay et al., 2017; Xiang et al., 2015). Nevertheless, the antifouling performance of the PDA-modified membrane is usually limited, because of the existence of relatively hydrophobic aromatic rings as well as the lack of antifouling functional groups in PDA molecules (Zhang et al., 2016). Therefore, the catechol moiety could strongly chelate with other metal ions, facilitating the mineralization of inorganic particles or nanoparticles on PDA surfaces through coprecipitation or redox reactions, in order to improve the hydrophilic and antifouling properties of the modified membranes. For this, the bioinspired membranes can be modified by means of adhesion and reaction of the PDA. 9.2.6.1 Adhesion functionality A one-step modification method can be used for in situ codeposition of functional materials (e.g., hydrophilic poly-sulfobetaine methacrylate and polyethylenimine) (Wang et al., 2015), and it can be incorporated in the in situ deposition of PDA on PP MF membranes. This modification can show significant improvement in the hydrophilicity of the membrane

318 Chapter 9

(A)

Cl

HO

NH3

OH

OH

HO OH OH

HO

NH2

Water, RT pH = 8.8

n HN

(B) O

HO

O N

O H

N H

O

N

HO

N H

O

4

3

O

HO

N H

HO

2

1

O

NH 2

O

HO

NH 2

HO 7

6

5

H HO

O N

HO

NH

O N H

O

O H

B

C

E

G H

n

HO HO

A

NH

O

HN

O

D

H H

O

F

N H

O O

O

n

H

N H

H 8

9

10

Figure 9.12 (A) Dopamine and synthesis of poly(dopamine) and (B) proposed structures of PDA.

surface and excellent separation performance for protein solution or oil/water elusion, as well as enhanced fouling resistance. 9.2.6.2 Reaction functionality of polydopamine Bioadhesion-assisted grafting is considered a promising approach for the antifouling modification of membranes. The kinds of antifouling modifiers, including inorganic particles (e.g., Au, Cu, Si, and Ag NPs or TiO2, ZnO, SiO2, Al2O3, ZnO, ZrO2, etc) (Khorshidi et al., 2018) (Fig. 9.13),

Antifouling membranes for polluted solvents treatment 319

Figure 9.13 Possible configurations of PDA adsorbed on TiO2: (A) possible mechanism of mPEG-DOPA binding to TiO2 surfaces; (B) possible configurations: (I) monodentate binding with a hydrogen bridge to a neighboring surface hydroxide and (II) bidentate binding (Bahamonde et al., 2020); (C) possible deposition mechanism of polydopamine on the membrane surface and (D) possible mechanism of binding TiO2 nanoparticles on the membrane surface (Zhang et al., 2013). Modified from Zhang, R. X., Braeken, L., Luis, P., Wang, X. L., & Van der Bruggen, B. (2013). Novel binding procedure of TiO2 nanoparticles to thin film composite membranes via self-polymerized polydopamine. Journal of Membrane Science, 437, 179
188. https://doi.org/10.1016/j.memsci.2013.02.059.

320 Chapter 9 biomacromolecules (e.g., heparin) (Jiang et al., 2010), polymers (e.g., PEG, PVA, polyvinyl pyrrolidone (PVP), zwitterionic polymers) (McCloskey et al., 2012), and small organic molecules, can be easily grafted to membrane surfaces by covalently/noncovalently bonding with the PDA layer, endowing the membranes with good antifouling properties against foulants (e.g., oil, proteins, platelets, and microorganisms) (Yan et al., 2020). Due to the versatility of surface modification with PDA the materials that can modify the membranes have been arranged in two groups: polymers and incorporation of nanoparticles (metal and metal oxide nanoparticles, carbon nanotechnology, metal
organic frameworks, etc.) (Jun et al., 2020). For this method, dopamine can react, for example, with the surface of metal oxide nanoparticles via surface complexation by any of these routes: (1) via catechol as a bidentate bonding; (2) bridged bidentate bonding; and (3) a complex mechanism as monodentate-bidentate bonding or hydrogen bonding (Fig. 9.13). These photocatalysts deposited on the surface could help to degrade contaminants such as drugs, dyes, biofoulings, and others (Tang et al., 2013) if the modified membranes are irradiated with UV light (Khorshidi et al., 2018; Nasrollahi et al., 2021). Although surface modification based on bioadhesion is universally applicable for various membrane surfaces and different materials, the long-time deposition of PDA usually causes severe pore blockage, leading to flux decline. Moreover, the high cost of dopamine and the characteristically dark color of the PDA coating may be impediments for industrialization (Zhang et al., 2016).

9.2.7 Other methods 9.2.7.1 New materials Polyamide membranes dominate the membrane industry; yet in their use they have a fundamental challenge to break through the upper bound due to an uncontrollable, excessive degree of crosslinking. A novel trend is the development of microporous polymeric membranes with rigidly intrinsic pores for rapid and precise molecular separation. MOPs have swiftly evolved as a promising alternative to conventional materials due to their intriguing inherent attributes, including robust organic backbone, persistent porosity, and high surface area. Advanced microporous organic polymers (MOPs), divided into crystalline (e.g., COFs) and amorphous (e.g., PIMs, PAFs, CMPs, POCs, HCPs, etc.) catalogs, have proven promising in the development of molecular-sieving membranes. Unlike traditional polymers with dynamic microporosity, MOPs have robust and well-defined pore architectures (Zhu et al., 2020).

Antifouling membranes for polluted solvents treatment 321 9.2.7.1.1 New manufacturing and modification methods

The commercialization of sustainable 3D printing technology has changed the face of manufacturing of antifouling membranes. In research related to manufacturing membranes 3D printing technology has been adopted successfully, due to its sustainable, low-risk, precise, uniform, and relatively low-cost fabrication methods (Yanar et al., 2020), therefore, this method shows great potential for exploration. 9.2.7.1.2 Hybrid membranes

It is important to note that it is possible to make modifications to membranes by combining several of the methods mentioned. Modifications using two or more of the methods described above are known as hybrid membranes.

9.3 Membrane technology for organic solvent Membrane technology is also an important process in the separation of organic solvents, as it can reduce the energy, carbon, and space intensity of traditional processes and avoid the phase change of the fluids to be separated. Membrane separation technology is being used more and more in the recovery and separation of organic solvents due to its separation efficiency. The most commonly used materials for membrane preparation are those with strong organic solvent resistance. Kinds of novel polymers, metal/covalent
organic framework, carbon materials, polymers of intrinsic microporosity, and conjugated microporous polymers provide possibilities and solutions to prepare organic solvent-resistant membranes. These materials can be used to manufacture membranes for pervaporation, organic solvent UF, organic solvent NF, organic solvent RO, and organic solvent FO, which are the most demanding and high-throughput separations in industry, due to the fact that they separate different molecules with very similar kinetic diameters (Fig. 9.14) (Lively & Sholl, 2017). Pervaporation is an efficient way to separate organic solvent mixtures which can be used for the separation of binary or multicomponent liquid mixtures. The separation in this process occurs through a nonporous polymeric or microporous ceramic membrane (Gaa´lova´ et al., 2019; Kujawa et al., 2015). PV is a molecular-level liquid separation technology that combines membrane permeability and evaporation. The driving force of pervaporation is the difference in chemical potentials generated by the difference in partial pressures on the feed and permeate sides (Ne´el et al., 1985). Typically, pervaporation can be used in three areas: (1) removal of organic solvents from aqueous solutions, (2) dehydration of solvents, and (3) separation of organic solvent mixtures (Knozowska et al., 2020). The main challenge for the development of pervaporation is related to the preparation of membranes that are more stable under adverse conditions and with higher separation efficiency.

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Figure 9.14 Molecular size range for OSRO, PV, and OSN and representative molecules in each range for each technique (Liu et al., 2020). Modified from Liu, C., Dong, G., Tsuru, T., & Matsuyama, H. (2020). Organic solvent reverse osmosis membranes for organic liquid mixture separation: A review. Journal of Membrane Science, August, 118882. https://doi.org/10.1016/j.memsci.2020.118882.

Ultrafiltration of organic solvents is a pressure-driven membrane separation technology. Small molecules of solute and solvent pass through the membranes and large molecules of solute are rejected. The main problem with UF membranes is their strong swelling in many organic solvents, which limits their applications. Many studies have shown that polyimide, polybenzimidazole, and polyurea have good separation performance in organic solvents (Polotskaya et al., 2009; Yeo et al., 2020). These membranes can also suffer cake fouling with different colloids. The effects of cake fouling for organic solvents on the cake fouling are different from aqueous ones, an extended Derjaguin-Landau-Verwey-Overbeek (XDLVO) model can correlate well this kind of fouling and predict the interaction energy between colloidal particles and rough membrane surfaces, but more studies are needed to provide more insights on this (Yin et al., 2020; Yuan et al., 2018).

Antifouling membranes for polluted solvents treatment 323 Organic solvent nanofiltration (OSN). Unlike traditional aqueous NF membranes, which usually separate charged ions and other compounds from water, OSN membranes typically separate uncharged organic molecules from other organic molecules (Lively & Sholl, 2017). These membranes have been commercialized for use in pharmaceutical applications and have been demonstrated in refining applications, but improvements in membrane materials, module fabrication, and process engineering are needed to enable these membranes to perform even more demanding separations (Hermans et al., 2015). Organic solvent reverse osmosis (OSRO). Similar to the aqueous RO process, the OSRO process primarily follows the solution
diffusion mechanism, in which the molecule dissolves in the membrane matrix and then diffuses through it as a permeate (Jang et al., 2019; Liu et al., 2021). The organic liquids are separated mainly due to their differences in sorption or diffusion behaviors in the membranes. Unlike OSN membranes, which largely differentiate solutes from solvents based on hydrodynamic radio, organic solvent RO membranes separate organic molecules based primarily on small differences in kinetic diameter (Lively & Sholl, 2017). In recent years, OSRO has been used in the separation and purification of organic solvents (Liu et al., 2021). Organic solvent forward osmosis (OSFO), or perstraction, has the potential to enable bulk chemical separations not accessible by OSRO, such as separations in which the osmotic pressure is simply too high for practical operation. In OSFO processes, molecules with a large kinetic diameter, such as mesitylene or branched paraffins, which have low vapor pressure, are used as the draw solution to osmotically extract the more permeable component from a feed mixture and the loaded draw solution can then be regenerated using OSN, OSRO, or flash techniques (Lively & Sholl, 2017). On the other hand, OSFO can also be used to break down distillation azeotropes. The common membranes are polymeric membranes and supported-liquid membranes.

9.3.1 Membrane materials Membrane materials developed for the filtration of organic solvents can be classified into three categories: inorganic membranes, polymeric, and novel membrane materials with intrinsic structure (Ren et al., 2020), as simplified in Table 9.3.

9.3.2 Principal problems At present, the main challenge of membrane technology for organic solvents is the difficulty of implementing large-scale industrial operation due to the lack of industrial-scale preparation of various membrane materials. In addition, flux, selectivity, organic solvent resistance, thermal stability, and lifetime need to be further improved and finally, the costly equipment required can also directly affect its application.

Table 9.3: The preparation methods, applications, advantanges, and disadvantanges of membranes used in organic solvent filtration. Membranes

Manufacturing methodsa,b

Inorganic: ceramics materials as: Al2O3, TiO2, SiO2, ZrO2, SiC

OSU OSN Suspended particle sol
gel anodic oxidation chemical vapor deposition (CVD), phase division, hydrothermal synthesis

Polymeric

ISA (PAN, PDMS, PEI, PEEK, PBI, ECTFE, PVA, PA)

PV OSN OSRO OSFO

TFC (porous support layer) such as (PAN), (PAA), (PVDF), (PVP), (PI), (PBI), chitosan, etc. SC (active polymerization) of (PS-bPAA)

OSN PV OSRO OSFO

A lot of monomers to explore.

OSN

Good organic solvent resistance.

LbLS (mix of polyelectrolytes and GO-CaCO3, PDA, COFs, PI, GO, MOFs as ZIF-8, etc.) Microporous membranes, conjugated microporous polymers (CMPs), polymers of intrinsic microporosity (PIMs)

OSN PV

Excellent separation performance. Low-cost environmental friendliness

OSN PV

High specific surface area. Strong resistance of organic solvent. CMPs: flexible and diverse design systems and numerous preparation methods. PIMs: high specific surface area, manageable pore structure, physical and chemical stability, thermal stability, resistance to organic solvent, easy process molding, and excellent mechanical properties. GO: extremely high specific surface area. DLC: manageable thickness, ultra-thin deposition and large-area preparation, strong resistance to organic solvents. CMS: unique pore

Novel membrane materials with intrinsic structure

Carbon-based materials graphene oxide (GO), diamond-like carbon (DLC), carbon molecular sieve (CMS), carbon nanotubes (CNTs), and metal
graphene nanohybrids.

Applicationsb

OSN PV

Advantages

Disadvantages

Chemical stability; Strong resistance to acid, alkali and organic solvents. Great mechanical strength against high pressure. Capability of backflush. Antimicrobial ability. High-temperature resistance (400 C and 800 C). Narrow pore size distribution. Great organic solvent resistance.

Fragile, cracks, low selective separation.

Thick separation layer (0.1 mm) leads to large hindrance and low flux. Improve development of membrane materials. Limitations of membrane materials Microstructure Homogenization of pore size. Improve development of membrane materials. CMPs: difficulty of application and secondary processing due to the fact that most amorphous CMPs are insoluble powder. PIMs: improve compatibility and solvent resistance for improved interface.

GO: imprecise control of layer spacing and structural stability. Graphene is prone to agglomeration. DLC: improve membrane separation performance. CMS: increase

Highly rigid crystalline materials Covalent organic frameworks (COFs), Metal organic frameworks (MOFs), Cyclodextrin (CD).

a

OSN OSRO

structure, high chemical, temperature and organic solvent resistance. CNTs: hydrophobicity, atomic smooth inner surface, high mechanical strength, excellent electrical properties, thermal stability and adsorption properties. Metal
graphene nanohybrids: good mechanical properties of metals and flexibility of graphene. COFs: remarkable permeation of both polar and nonpolar organic solvent. MOFs: strong coordinate bonds to form three-dimensional microporous structure, high specific surface area and porosity, various function, adjustable size and diverse types of MOFs. CD: microporous structure with organic solvent resistance.

permeability. CNT: improve permeability of low-viscosity organic solvents, preparation technologies cannot yet meet industrial production scale requirements, the combination of CNTs and membranes is not strong enough. Metal-graphene nanohybrids: by component agglomeration, a new preparation technology is essential. COFs: poor solubility and processability of COFs. MOFs: Limited application of nanoparticles due to aggregation and compatibility with media. CD: improve lifetime and separation stability.

ISA, Integrally skinned asymmetric. ECTFE, ethylene chlorotrifluoroethylene; COFs, Covalent-organic frameworks; GO, graphene oxide; LbL, The layer-by-layer; LbLS, self-assembly membranes; MOFs, metalorganic frameworks; PA, polyaniline; PAA, polyacrylic acid; PAN, polyacrylonitrile; PBI, polybenzimidazole; PDMS, polydimethylsiloxane; PEEK, polyether ether ketone; PEI, poly (ether imide); PI, polyimide; PS-b-PAA, polystyrene-block polyacrylic acid; PVA, Polyvinyl alcohol; PVDF, polyvinylidene chloride; PVP, polyvinyl pyrrolidone; SC, segmented copolymers; TFC, thin film composite membranes. b

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9.3.3 Fouling in membrane technology for organic solvents The membrane fouling phenomena during organic solvent filtration have been poorly explored (Yin et al., 2020). Since it is a young technology, studies of antifouling membranes for the treatment of organic solvents are limited at the present time. The following aspects should be considered for possible improvement. Firstly, scalable preparation of inorganic separation membrane and new materials available. Secondly, polymeric membranes can be modified by chemical crosslinking and inorganic/organic hybridization (improving performance, selectivity, permeability, and membrane strength, as well as reducing the degree of swelling). Third, membranes can be optimized by the addition of new materials such as graphene, CNTs, various zeolitic imidazolate frameworks MOFs, and COFs to produce new two-dimensional and three-dimensional membrane materials with large pore structure (Ren et al., 2020). These researches and applications will greatly promote the progress of chemical technology (Van Der Bruggen & Luis, 2014).

9.4 Brief description of techniques for characterizing and understanding mechanisms membrane fouling Characterization techniques play a key role in characterizing and understanding membrane fouling and fouling mechanisms. The following is a brief summary of the most common techniques (Scanning electron microscopy (SEM), Transmission electron microscopy (TEM), Atomic Force Microscopy (AFM), X-Ray Diffraction (XRD), Fourier transform infrared spectroscopy (FT-IR), X-ray photoelectron spectroscopy (XPS), Energy-dispersive X-ray (EDX), contact angle, zeta potential) (Jhaveri & Murthy, 2016) used for the characterization of nanocomposite membranes. SEM. This technique is used to compare the surface morphology of different membranes (pristine vs modified membranes or clean vs fouled). This technique can evaluate both the membrane surface and the membrane cross-section. EDX and XPS. These techniques provide an elemental analysis of the surface or crosssection of the membrane. AFM is used to know and compare the surface topology (roughness) of pristine, modified, and fouled membranes. A poor roughness is responsible for imparting the antifouling ability as the foulants from water are less prone to adsorb on the smoother surfaces. TEM normally is used to determine the size of NPs (0.1 nm).

Antifouling membranes for polluted solvents treatment 327 Contact angle is used to determine the wetting of the membrane surface by the contact angle between the water droplet and the membrane surface. A high contact angle is hydrophobic, whereas a low contact angle is hydrophilic. If the membrane is hydrophilic, it can produce an antifouling effect for aqueous streams. Zeta potential is a new technology used to measure the surface charge of the membrane. XRD is used to know the presence and crystallinity of nanoparticles on nanocomposite membranes. FT-IR is generally used to analyze the stretching and bending vibrations of chemical bonds of compounds present on the surfaces of crosslinked or self-assembled nanocomposite membranes.

9.5 Conclusions and outlook The success of membrane technology is critically dependent on how fouling is dealt with. This chapter presents the types of contaminants, fouling mechanisms, and the cleaning and control of membrane fouling. In addition, membrane surface modification, both active and passive, and its influence on membrane fouling were discussed. Furthermore, the latest advances in membrane modification for organic solvents are shown. Finally, a brief description of the techniques used to understand and characterize membrane fouling was presented. With the widespread use of membrane technology, materials used as membranes and the research on their properties should be given attention. The development of antifouling membranes has received a high level of attention from both academia and industry, due to the large number of methods and materials used in new research on this subject. However, the membrane preparation methods and materials used still remain an important pillar for the development of antifouling membranes. The main challenge is to find membranes that can simultaneously provide adequate flux and less fouling. The combination of nanomaterials, such as CBNs (GO and CNT), MOFs, COFs, metal oxides, zeolites, and nano-sized polymeric particles, with new membrane fabrication methods, such as 3D printing, could improve the performance of membranes used for aqueous and organic fluxes. Although the history of the organic solvent membranes technology is relatively short in comparison to aqueous applications membranes technology, the growing interest in organic solvent membrane development has been obvious over the past decade. Therefore, the application of membrane technology to organic solvent separation will surely attract more and more attention. This is why future research should focus on the design and development of functional and efficient membrane materials.

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Acknowledgments The authors acknowledge the support provided by I´Acadmie de Recherche et d’Enseignemetn Supe´rieur (ARES) and Central University of Ecuador for financially supporting this work (RFCQ-CQ-SO13
186
2017).

List of acronyms AD AFM AI CBN CC CF CMP CMPs CNT COFs COs CPM CVD DOPA ECTFE EDX FD FO FT-IR GO HCP ISA LbL LbLS MAPs MD MF ML MOFs MOPs MPD NF NIPS NOM NPs OSN OSRO OSU P PA PAA PAF

fouling adsorption atomic force microscopy Artificial intelligence carbon-based nanomaterials cake consolidation compaction fouling conjugated microporous polymers microporous polymers carbon nanotubes covalent-organic frameworks covalent organic structures cationic polymeric materials chemical vapor deposition 3,4-dihydroxyphenylalanine ethylene chlorotrifluoroethylene energy-dispersive X-ray fouling deposition forward osmosis Fourier transform infrared spectroscopy graphene oxide hypercrosslinked polymers integrally skinned asymmetric the layer-by-layer self-assembly membranes mussel adhesive proteins membrane distillation microfiltration machine learning metal-organic frameworks microporous organic polymers m-phenylenediamine nanofiltration non-solvent induced phase separation natural organic matter nanoparticles organic solvent nanofiltration organic solvent reverse osmosis ultrafiltration of organic solvents adsorption interactions polyaniline polyacrylic acid porous aromatic structures

Antifouling membranes for polluted solvents treatment 329 PAN PBI PDA PDMS PE PEEK PEI PEO PES PI PIMs POC PP PS-b-PAA PSBMA PTFE PV PVA PVDF PVDF PVP PVP RO ROS SC SEM TEM TFC UF XPS XRD

polyacrylonitrile polybenzimidazole polydopamine polydimethylsiloxane polyethylene polyether ether ketone poly(ether imide) poly(ethylene oxide) poly (ether sulfone) polyimide polymers of intrinsic microporosity porous organic cages polypropylene polystyrene-block polyacrylic acid polysulfobetaine methacrylate polytetrafluorethylene pervaporation polyvinyl alcohol poly (vinylidene fluoride) polyvinylidene chloride polyvinyl pyrrolidone pyrrolidone reverse osmosis reactive oxygen species segmented copolymers scanning electron microscopy transmission electron microscopy thin-film composite ultrafiltration X-ray photoelectron spectroscopy X-ray diffraction

List of symbols CBis Cw hc D J Jo Jv k Rb Rc Rm Rmc Rt R^ C

concentration of species in the bulk feed concentration of species at the membrane surface cake height diffusivity permeate flux initial flux flux in determine time boundary layer mass transfer coefficient resistance due to pore blockage resistance offered by the cake layer resistance to flow through the membrane resistance of the new or clean membrane total membrane resistance specific resistance

330 Chapter 9 η ΔP δ

viscosity transmembrane pressure membrane boundary layer thickness

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CHAPTER 10

Membrane sensors for pollution problems S. Mondal1, M. Malankowska2,3, A.H. Avci4, U.T. Syed1, L. Upadhyaya5 and S. Santoro4 1

LAQV/Requimte, Department of Chemistry, Faculty of Science and Technology, NOVA University of Lisbon, Caparica, Portugal, 2Institute of Nanoscience and Materials of Aragon (INMA), CSICUniversity of Zaragoza, Zaragoza, Spain, 3Chemical and Environmental Engineering Department, University of Zaragoza, Zaragoza, Spain, 4Department of Environmental Engineering, University of Calabria, Rende, Italy, 5King Abdullah University of Science and Technology (KAUST), Biological and Environmental Science and Engineering Division (BESE), Advanced Membranes and Porous Materials Center (AMPM), Thuwal, Saudi Arabia

10.1 Introduction Pollution is a side-effect of the current “take
make
waste” industrial model with devastating consequences on the environment. The linear economy has jeopardized biodiversity, ecosystems, and human health worldwide. Consequently, the current alarming scenario calls for a dramatic change in anthropic activities toward sustainability and economic circularity. Membrane technology plays a decisive role in this paradigm shift by opening unprecedented horizons to the process intensification of eco-friendly and energy-efficient industrial activities. Moreover, membrane processes have become popular in environmental remediation (especially in water purification) and they have gained more attention in pollution prevention, including recycling, posttreatment, and disposal or release practices (Dasgupta et al., 2015; Ji et al., 2010; Figoli et al., 2020). Alternatively, national and international institutions have imposed detailed regulations to limit water and air pollution. Undoubtedly, the environment quality management is underpinned on the in situ and real-time detection of pollutants in gaseous exhausts and industrial waste streams, whereas the incessant in-field monitoring with portable and inexpensive sensors is a powerful strategy to understand the pollution exposure of communities against ticked health indicators (Winton et al., 2020; Baiardi, 2020). Due to the environmental concerns from pollution faced by modern society, the sensing approach is a crucial field of research and a dynamic market. Moreover, the COVID-19 pandemic outbreak demonstrated the importance of the development of cheap, disposable, simple, and reliable sensors for pathogens (Zhao et al., 2020). Current Trends and Future Developments on (Bio-) Membranes. DOI: https://doi.org/10.1016/B978-0-12-824103-5.00004-8 © 2023 Elsevier Inc. All rights reserved.

335

336 Chapter 10 A specific sensor is engineered from a highly selective membrane responsible for molecular recognition and/or selective capture of the target analyte(s). The membrane is tendentially coupled/integrated with an electrochemical transducer that converts the interactions of target molecules-sensitive material into a quantifiable signal (Antun˜a-Jime´nez et al., 2012). Membrane-based sensors are made of materials with strong chemical affinity toward the target analytes (Santoro et al., 2016a,b; Ma et al., 2021). Their morphologies are designed to present molecular cavities of tailored shape, chemical, and electronic environment for molecular recognition of the target from complex mixtures (Ding et al., 2010). Overall, membrane technology consists of a solid background for the development of advanced sensors to detect pollutants. In this chapter, we detail the implementation of membranes in sensors to detect gaseous pollutants and elucidate the mechanism of detection. Also, the key features of membranes for the detection of nano/microplastics and pathogens, two of the trending emerging questions, are highlighted.

10.2 Air pollution 10.2.1 Membrane-based gas sensors In the technologically driven era of modern civilization, air pollution monitoring has become imperative for protecting “Mother Nature.” Prompt detection of pollution and identification of its sources reduces the danger or harm to humankind and the environment. Membranes are becoming a competent technology for the quick detection of polluting gases. Since their porosity and functionality can be tailor-tuned, they can be designed to selectively pass the target analyte. This gives a twofold advantage: firstly, it reduces the volume of analyte that will be detected by the sensors; and secondly, it protects the sensors from deterioration on exposure to corrosive gases, thereby extending their service life. Gas sensor technology plays a pivotal role in effectively detecting air pollutants such as greenhouse gases, carbon monoxide, nitrous oxide, sulfur oxide, etc., with precision and reliability. The rapid advancement in electronic and computing technology over the last few decades has called on the substantial progress in instrumentation, computerization, and automation of chemical processes incorporating membranes. The underlying fundamental principle in sensing technology is the diffusion of gases through membranes (i.e., membrane-based gas sensors), which aids in meeting the growing demand for the commercialization of process monitoring in industrial and environmental pollution quantification.

10.2.2 Working principle of membrane-based gas sensor A typical membrane-based gas sensor comprises three components: gas-selective membrane, recognition unit, and transducer (Fig. 10.1). Specific gas molecules permeate through the membrane and undergo a chemical or biochemical reaction in the recognition

Membrane sensors for pollution problems 337 Gas inlet

` Membrane Recognion unit Transducer Signal transmission

Figure 10.1 Schematic representation of a typical membrane-based gas sensor.

unit, generating a signal that is detected and transmitted by the transducer (Pinto et al., 1999). The membranes used for gas sensors act as a selective barrier between two phases leading to the passage of one or more desired gas molecules while retaining the rest. The choice of membrane material for gas sensor applications is based on specific physicochemical properties, as these materials can be tailor-made to be used for specific gas mixtures (Figoli et al., 2015). The permeability and selectivity of the membrane are the key parameters that dictate the membrane performance. Permeability of a species i (Pi) is the rate at which they permeate across the membrane. This depends on a kinetic parameter (diffusion) and a thermodynamic parameter (partition coefficient). The molar flux of i (Ji) is expressed as the product of permeance (Pi0 ) and the trans-membrane pressure (Fp). Permeance is defined as the permeability per unit thickness (δ) of the membrane. Therefore,
 Pi 0 (10.1) 3 Fp : Ji 5 Pi 3 Fp 5 δ For transport of species i and j simultaneously crossing a membrane, its ideal selectivity (αij) is expressed as the ratio of permeability of i (Pi) with respect to that of j (Pj): αij 5

Pi : Pj

(10.2)

The fundamental law that guides the transport of gases across the membrane can be derived from Fick’s first law, which relates the flux to the concentration gradient (ΔCi). Considering an ideal situation (no boundary layer resistances), we can express Ji as: Ji 5 Di 3 ΔCi ;

(10.3)

338 Chapter 10 where Di is the diffusion coefficient. The mass transfer coefficient (Mi) of component i, can be expressed as ðt ðt 0  Di : A  (10.4) Ci ;f 2 Ci ;p dt; Mi 5 Ji : Adt 5 0 0 δ where A is the cross-sectional area of the membrane, Di0 is the effective diffusivity, and Ci,f and Ci,p are the concentrations of i on the feed and permeate side of the membrane, respectively. With the incorporation of various transducers, the detection signal (Ii) is usually proportional to Mi: I ~ Mi :

(10.5)

It is desirable for membrane-based sensing devices to have a fast response time and high sensitivity. Hence membranes with high permeability and selectivity are chosen for a given application. This opens up the possibility of designing tailor-made membranes for each application (Freeman, 1999). To better understand the transport of gas analytes through the membrane, it is imperative to be acquainted with its mechanism. We know from the kinetic theory of gases that the transport of a gas is guided by collisions among molecules and with the walls of the chamber. The average distance traveled by gas molecules between two such successive collisions is defined as the mean-free path. Different transport mechanisms have been proposed based on the mean-free path of permeating species and membrane pore size. Table 10.1 details these transport mechanisms.

10.2.3 Categories of membrane-based gas sensors Conventional direct gas sensing methods often lack a competitive advantage due to low selectivity or sensitivity. For example, in ammonia detection, solid-state sensors lack sensitivity to measure low concentrations of NH3 and the same happens for higher concentrations for other gases (Timmer et al., 2005). Membrane-based gas sensors are competent replacements in such scenarios as they amalgamate the merits of sensors and the Table 10.1: Mechanisms of gas transport (Pandey & Chauhan, 2001). Transport model

Mechanism

Lattice diffusion/ convective flow Knudsen diffusion Surface diffusion

Membrane pore size . mean-free path of i

Diffusion solubility

Membrane pore size , mean-free path of i The membrane pore size in-between size of the different permeating gas molecules The gas molecule dissolves in membrane material and thereafter transfer by diffusion mechanism

Membrane sensors for pollution problems 339 selectivity of the membranes. The selective membrane allows gas molecules of interest to pass through the membrane and enter the recognition unit matrix (Ohira et al., 2002). This means a twofold advantage to the sensor; firstly, it improves the overall selectivity of the sensor by enhancing the quality and quantity of chemical and biochemical reactions in the recognition unit, and secondly, it selectively reduces the large volume of analyte feed to detectable species which are formed and detected by the transducers (Boring et al., 2002). However, the drawback of such devices might be membrane fouling, which will inhibit the sensors’ accuracy (de Jong et al., 2006). Based on the type of reaction inside the recognition unit, the membrane-based gas sensors can be classified into chemical sensors and biosensors. The recognition unit undergoes chemical or biochemical reactions accordingly with the permeated gas molecules, resulting in a measurable signal detected and transmitted by the transducers. We can classify the gas sensors based on transducer type into electrochemical (potentiometric, amperometric, and conductometric) and optical sensors. The membrane-based gas sensors gained industrial attention due to their user-friendly usage, higher sensitivity, precision, and comprehensive affordability (Fig. 10.2). In all electrochemical sensors, the gas molecules permeate through the membrane and enter the recognition unit. This unit’s matrix comprises a reference solution (electrolytic solvent or gels), a cathode, and an anode. The incoming gas molecule undergoes a chemical reaction with the solution in the electrodes’ presence. This leads to a generation of a voltage difference (potentiometric), a current difference (amperometric), or a conductivity difference (conductometric). In optical sensors, the molecule of interest interacts with the chromophore agent leading to emission/absorption of light detected by optical transducers. Although optical sensors exhibit high sensitivity, their usage is limited due to the relatively

Membrane-based Gas Sensors

Poten ometric

Chemical Sensor

Biosensor

Electrochemical

Op cal

Amperometric

Conductometric

Figure 10.2 Classification of the membrane-based gas sensor.

340 Chapter 10 high cost. In biosensors, permeated gas molecules undergo a biochemical reaction in the recognition unit, generating an electrical/optical signal detected by the transducers. This process is comparatively more sensitive as it involves highly selective biological reactions. These biosensors can be available in two different configurations of transducers: optical and electrochemical. Compactness, high selectivity, and sensitivity in self-sufficient structures with direct transduction from analytes to signals make them appropriate for on-field environmental monitoring.

10.2.4 Recent breakthrough in membranes for air pollution sensing The primary role of the mixed matrix membrane is to act as a passive support for the homogeneous dispersion of the sensitive nanofiller. Membrane-based sensors are usually highly porous to facilitate the interactions with the analytes, resulting in greater accessibility to sensing sites. Moreover, the embodiment of the functional nanomaterials into polymeric networks provides effective and continuous protection to its functionality by limiting the interference arising from competitors. Polymeric materials like Nafion, polyaniline (PANI), polyvinyl chloride (PVC), polyvinyl alcohol (PVA), polyesters, and polytetrafluoroethylene (PTFE) are widely used materials for the fabrication of sensitive membranes. In recent years, there has been significant interest in the development of novel nanomaterials like metal
organic frameworks (MOFs), graphene oxides (GO), molybdenum disulfide (MoS2), and tungsten disulfide (WS2) as potential candidates for the detection of toxic gases in the environment in the form of composite membranes. Metal
organic frameworks, also called coordination compounds, are extensively applied for gas separation and catalysis due to their tunable pore size, sorption capacities, and thermal stabilities. In fact, MOFs offer well-defined pore shapes and sizes and recordsetting surface areas and pore volumes, which will promote an easy, rapid access to internal sites that bind analytes. One of the Zeolitic imidazole framework (ZIFs), a kind of essential MOF, has been employed to explore gas sensing due to its hydrophobicity and humidity resistance characteristics. GO has two-dimensional atomic layers of sp2-bonded carbon atoms and is a widely used material for various separation applications due to the higher thermal/mechanical stability, larger surface area, excellent electrical conductivity owing to high density of electrons, and lower cost compared to MOFs. Garg et al. (2020) developed the ZIF-67 and reduced GO composite membranes to detect ammonia with a sensor detection limit of 74 ppb. This ammonia sensor was engineered by synergically exploiting the key features of the different materials: (1) ZIF-67 to facilitate the ammonia recognition; and (2) GO to enhance the conductivity and the surface-to-volume ratio of the nanocomposite. The thin selective nanocomposites of ZIF-67/rGO with a high surface-to-volume ratio (1080 m2/g) deposited over the interdigitated gold electrodes ensured the detection of NH3 (20
50 ppm).

Membrane sensors for pollution problems 341 Abu-Hani et al. (2017) incorporated the tungsten oxide (WO3) nanoparticles in PVA membrane, which significantly increased the membrane conductivity compared to PVA without nanofiller. The polymer membrane served as host for WO3 and its conductivity was further enhanced by incorporating ionic liquid in hybrid membranes to detect H2S with a detection limit of 10 ppm. The sensors have shown excellent temperature resistance and reproducibility along with a cheaper and facile route of fabrication. Liu et al. (2019) deposited ZIF-8 crystals on indium oxide (In2O3) nanofiber where In2O3/zinc oxide (ZnO) nanofibers were used as the support and source of Zn21for the formation of ZIF-8 using a self-template strategy. The coated ZIF-8 comprised an effective gas enrichment medium characterized by selectivity for the target gas repealing the diffusion of water molecules. In fact, the hydrophobic nature of ZIF allows the sensors to be used in humid conditions without affecting its performance. The composite showed an excellent detection limit as low as 1 ppb for NO2. ZnO-based one-dimensional hollow nanowire itself is a promising material for sensor application due to its higher surface area and semiconductor properties Lee et al. (2017). developed the hollow nanowire-based sensors with ZnO deposited on sacrificial cyclopore polycarbonate membranes via atomic layer deposition techniques. The sensors exhibited a surface area of 10.17 m2/g with 0.1
10 ppm detection limit for NO2. The major drawback of ZnO-based material is the selectivity to gas components in a mixture. Blending the ZnO with p-type materials such as graphene will introduce p-n type heterojunction and modulate the output signal. Kim et al. (2017) developed the ZnO semiconductor graphene nanocomposite using the microwave irradiation method, which showed superior selectivity and sensitivity toward NO2 gas. Lee et al. (2019) developed a blend of reduced GO and ZnO membrane, capable of detecting NO2 with a 5
100 ppm detection limit. The use of ZnO and reduced GO in the blend reduced the response time and recovery time due to the supply of reactive electrons from ZnO’s oxygen vacancy and the formation of the C-O-Zn bond. Traditionally, self-assembly, layer deposition techniques, phase separation, and template synthesis procedures were used to prepare porous hollow nanofibers (Ding et al., 2010). Due to the increase in demand for cost-effective technology, the electrospinning strategy gained significant attention (Ding et al., 2010; Santoro et al., 2017). In a typical electrospinning process, liquid jets are produced on the capillary tip by varying the electrical impedance, which changes the surface tension of releasing droplets and accelerates the collector plate (Santoro et al., 2019). As the evaporation of solvent continues, and the stretching process continues over the length, ultrathin porous polymeric fibers are formed, which are the most promising templates for the fabrication of sensor materials (Ding et al., 2010; Santoro et al., 2017). Mahmoud and coworkers (Ali et al., 2020) integrated PVA with tungsten(VI) oxide and produced organic
inorganic hybrid electrospun fibers that could operate at room temperature. The nanoparticles were incorporated with ionic liquid and deposited on PVA fiber, which was used to estimate H2S.

342 Chapter 10 Interestingly, some polymers such as PANI present intrinsically gas-sensitive (i.e., NH3, CO, and SO2) and conductive properties. Bhadra et al. (2019) fabricated the graphene
PANI nanocomposite-coated polystyrene (PS) nanofiber mats using the electrospinning procedure. Interestingly, the peculiar morphology of the nanocomposite, consisting of a coating of 10 nm of PANI nanofibers and graphene around 3 μm of PS fibers, ensured CO2 sensing with a 20
100 ppm detection limit. Table 10.2 details examples of state-of-the-art gas sensors’ for the detection of different gas pollutants and their modes of operation.

10.3 Water pollution 10.3.1 Plastics Plastic litter in the marine environment is more than just an unpleasant visual problem. It is shocking to see plastic waste washed up on beaches, floating islands of plastic in the middle of the ocean, and sea creatures tangled up and suffocating in plastic waste. Yet, these terrible scenes only show the immediate impact of this global issue. Microplastics, too small to be seen by the naked eye, are arguably a much greater and longer lasting ecological disaster. Membrane technology is a promising approach in the removal and detection of low-molecular-weight contaminants, such as microplastics or even nanoplastics. Plastics were created as a solution for scarce and expensive raw components, such as animal bones, tortoiseshell, and ivory. Their exceptional properties dramatically changed our world and resulted in their massive manufacture in the last decades rising to an annual worldwide production in 2018 of 359 Mt (Andrady, 2011; Wright et al., 2013). However, nowadays only about 32.5% of plastic waste is recycled (Wright et al., 2013) and it is unacceptable that this waste ends up in rivers, lakes, or the oceans. Microplastics present different challenges compared to their macrocounterparts, mainly due to the ability of bioaccumulation of toxic compounds (such as persistent organic pollutants) on the microplastics’ surface thanks to their high surface to volume ratio (Malankowska et al., 2021; Wagner et al., 2014). Such accumulation results in a dramatic risk to the marine biota, as well as to humans via for example sea salt or fish ingestion (Malankowska et al., 2021; Karbalaei et al., 2018). Particles in the dimensions between 0.1 and 100 μm are considered microplastics according to IUPAC (International Union for Pure and Applied Chemistry) (Vert et al., 2012). Nevertheless, recently microplastics were defined as plastic fragments whose longest dimension is below 5 mm (Bujnicki et al., 2019). Moreover, a new concept of nanoplastics as products of the degradation of microplastics was introduced in 2011 (Andrady, 2011), with the upper size limit being 100 nm (Jambeck et al., 2015).

Table 10.2: Membrane-based sensors for air pollution detection. Type of gas

Type of sensors Membrane materials

Sensing material

Detection limit

Reference

NH3

Optical

Polyaniline
polymethyl methacrylate (PMMA) composite film Tributylphosphate-coated polyolefin fiber

Polyaniline films as sensor; Nulling optical-transmittance bridge with a laser source as recorder LED and photodiode

10
4000 ppm

Gore-Tex Teflon membrane

LED and silicon phototransistor

0.05 μM

Stainless steel electrodes; NaOH/EDTA solution with deionized water; Micronal B330 conductivity meter




Nicho et al. (2001) Schmitt et al. (2012) Willason and Johnson (1986) Pasquini and de Faria (1987) Chabukswar et al. (2001) Khan et al. (2011)

Conductometric Polytetrafluoroethylene

Acrylic acid doped with polyaniline films

Amperometric Potentiometric

Quartz crystal micro balance

DC electrical resistance meter; FTIR spectra and X-ray diffractograms (XRD) Polyurethane
clay nanohybrid Polyurethane film & nanohybrids used a direct electrode; Pd wire as reference electrode; phosphate buffer solution as reference; ammonium hydroxide solutions as detecting solution; sensing performance measured by electrometer using I-V technique ZIF-67 and reduced GO composite membranes ZIF-67/rGO film deposited over interdigitated gold electrodes (IDEs); source and measurement unit (B2901A, Agilent, USA) Polyaniline (PAN) and isopolymolybdic acid (PMA) Ultrathin PAN/MO3 films as sensor; ohmmeter as composite detector Cellulose triacetate Nonactin membrane mounted on ISE-561 Phillips electrode (working electrode) and Ag/AgCl wire (reference electrode) Commercial PTFE membrane Orion 90
0029 double-junction electrode containing a 0.01 mol l-1Tris
HCl solution (pH 5 7.5) in the outer compartment was used as reference electrode; Stainless steel tube as grounding electrode; A Crison 20002 digital decivoltmeter coupled with a Kipp & Zonen BD 111 recorder Poly(acrylic acid) (PAA) and PVA electrospun Continuous films coated quartz crystal microbalance membranes (100
400 nm fiber diameter) (QCM) sensor; resonance frequency counter Electrospun fibrous PAA membrane (1
7 μm in Fibrous membrane coated QCM sensor; resonance diameter) frequency counter PAA and PVA electrospun membranes (100
400 Fibrous membrane coated QCM sensor; resonance nm fiber diameter) frequency counter

10
1000 ppm

1
600 ppm 0.0175 6 0.001 μM

74 ppb

Garg et al. (2020)

100 ppm

Li et al. (2000) Krawczy´ nski vel Krawczyk et al. (1994) Lima et al. (1999)

10 μmol/L 5 3 10
4 mol/L

50 ppm 130 ppb 50 ppb

Ding et al. (2004) Ding et al. (2005) Ding et al. (2005)

(Continued)

Table 10.2: (Continued) Type of gas

Type of sensors Membrane materials

Sensing material

Detection limit

Reference

CO2

Optical

Sodium dihydrogen phosphate and phenol red as indicator; Spectrophotometer absorbance at 554 nm a detector Membrane mounted on Ostec electrode bodies acts as sensor; Double beam spectrophotometer absorbance at 550 nm as detector Membrane as sensor material; spectrophotometer to record absorbance; digital camera determined the hue component of pictures

2.50 3 102 μl/L

Satienperakul et al. (2004)

200 ppm

Xie et al. (2012)




Perez de VargasSansalvador et al. (2017) Luoh and Hahn (2006)

Polytetrafluoroethylene

Poly(vinyl chloride), o-nitrophenyl octyl ether, chromoionophore IV (ETH 2412) blend

CO

2-Hydroxyethyl cellulose, meta-cresol purple sodium salt, glycerin, sodium hydrogen carbonate and the ionic liquid 1-ethyl-3-methyl-imidazolium chloride blend Electrospun PAN fibers incorporated with iron oxide, antimony tin oxide and zinc oxide nanoparticles (50
200 nm fiber diameter) Graphene
PANI nanocomposite-coated polystyrene (PS) nanofiber Conductometric n-type tin (IV) oxide (SnO2)/MWCNT nanofibers

NOx

Optical

Membrane fiber mats as sensor; Fourier transform infrared spectroscopy (FTIR) as detector

700 ppm

Nanocomposite-coated PS membranes as sensor; Keithley source meter used to measure resistivity Polyethylene terephthalate with aluminum electrodes

20
100 ppm

0.5 mg/L

Tetramethyl orthosilicate based sol-gel films

Optical fibers and bifurcated fibers for absorbance and reflectance measurements Encapsulated cytochrome c

1
25 ppm

Polyaniline
polystyrene sulfonic acid composite

Gold interdigitated electrodes

20 ppm

Porous polypropylene

Polymethyl methacrylate optical fibers

5.5 ppbv

ZnO nanowires on cyclopore polycarbonate membranes Multiwall carbon nanotube
ZnO composite membrane Conductometric Acrylic acid doped with polyaniline films

Titanium and platinum coated interdigitated electrodes

0.1
10 ppm

Gold interdigitated electrodes

2
20 ppm

Acrylic acid doped with polyaniline films




Amperometric

Polished silicon wafers, quartz slides and alumina plates with printed Ag electrodes Platinum electrode




Blend of 10% PVC, 3% tetrabutylammonium hexafluorophosphate (TBAHFP), and 87% of 2-nitrophenyloctyl ether (NPOE) Polydimethylsiloxane (PDMS) (20 μm thickness)

Platinum electrode

80 ppb

Platinum disk electrode

20 nM
50 μM

rGO-ZnO composite membrane

Gold electrode

5
100 ppm

ZIF-8 Indium oxide (In2O3) nanocomposite

Gold electrode

1 ppb

Carbonized polytetrafluoroethylene

PAN and PMA composite Nafion 117 (Dupont de Nemours)

50 ppm

0
100 ppm

Bhadra et al. (2019) Yang et al. (2007) Frenzel et al. (2004) Aylott et al. (1997) Xie et al. (2002) Tian et al. (2017) Lee et al. (2017) Vyas et al. (2012) Chabukswar et al. (2001) Li et al. (2000) Ho and Hung (2001) ´ Hrnˇc´ıˇrova et al. (2000) Mizutani et al. (2001) Lee et al. (2019) Liu et al. (2019)

SOx

H2S

Potentiometric

Polytetrafluoroethylene

Orion 90
00
02 double-junction electrode

Amperometric

Nafion

Au-Nafion solid polymer electrolyte (SPE) electrodes

Polytetrafluoroethylene (50 μm thick)

Polytetrafluoroethylene (50 μm thick)

Optical

Teflon (SM 11807, Sartorius, pore diameter 0.2 μm)

Fluorescence detector F 1050 equipped with a 12-μL quartz cell

´jo et al. Arau (1998) 0.6 μg/L Hodgson et al. (1999) ´jo et al. 0.03 mg/L Arau (2005) 40 nm
0.1 mM Mana and Spohn (2001)

Amperometric

SPE (Solid polymer electrolyte)
Ag electrode

45ppb

Copper and Stainless steel electrodes

10 ppm

Silver electrode

10
5 mol/L

Orion sulfide-selective electrode Copper sheet and a stainless-steel grid

50 mg/L 100 ppb

Optical

NAFION 417 Cation perfluorinated (0.425 nm thick) Polyvinyl alcohol
ionic liquid
tungsten oxide composite membrane Microporous polypropylene membranes (0.1 pm pore size, 75% porosity, 80 pm thickness) Polytetrafluoroethylene (0.05 mm thick) Tungsten(VI) oxide-PVA (WO3-PVA)Electrospun fibers (110
150 nm fiber diameter) Molybdenum sulfide/citric acid composite

LPFG (long period fiber grating)

0.5 ppm

Quartz crystal micro balance Potentiometric

PAA and PVA electrospun membranes (100
400 nm fiber diameter) Polytetrafluoroethylene (0.1 mm thickness)

Quartz crystal microbalance

50 ppb

Galvanic hydrogen cyanide sensor; electrometer (model 612, Keithley Instruments) as detector Metallic silver-wire electrode in presence of silver ion complexing agent as sensor; differential amplifier for potential difference measurements Sensor made of ninhydrin in alkaline medium (controlled conditions); spectrophotometer (at 510 nm) as detector Gold electrodes and membrane microfibricated on Kapton substrate act as sensor; Keithley sourcemeter 2612 A records the electrical resistance

0.1 mg/dm3

Potentiometric

Cyanide

Microporous polypropylene membranes (porosity 75% pore size 0.2 pm, thickness 80 pm Optical Trimethylamine Electro chemical

Polytetrafuluoroethylene (Tecator) Titanium oxide (TiO2) nanotube membrane

3.2
180 mg/L


2.5 μg/L 40
400 ppm

Schiavon et al. (1995) Abu-Hani et al. (2017) Frenzel (1990) Brunt (1984) Hittini et al. (2020) Qin et al. (2018) Ding et al. (2006) Hachiya et al. (1999) Frenzel, Liu et al. (1990) Themelis et al. (2009) Perillo and Rodrı´guez (2016)

346 Chapter 10 This restriction is significant, since particles below such limit, in contrast to microplastics, may be capable of disrupting the cell membrane (Andrady, 2011). Furthermore, the Norwegian Environmental Agency focused on the effect of microplastics entering the natural environment via industrial or domestic wastewater and raised a concern about worrying plastic pollution in drinking water as well as plastic debris in seas and oceans (Bujnicki et al., 2019). This happens mainly due to the direct addition of primary microplastics to our environment. In general, plastics could be fabricated as microplastics in origin (primary microplastics), or they could experience physicochemical degradation of bigger plastic debris (secondary microplastics) (Cole et al., 2011). Primary microplastics are usually added to facial cleansers or scrubbers, cosmetics, and air-blasting media as indicated in Table 10.3 (Bintein, 2017). Secondary microplastics are a result of different polymeric degradation processes (Andrady, 1994), such as: 1. 2. 3. 4.

Photodegradation (action of light—usually sunlight; one of the fastest degradation processes) Biodegradation (action of living organisms such as microbes) Thermooxidative degradation (slow oxidative breakdown at moderate temperature) Hydrolysis (reaction with water) (Andrady, 2011, 1994).

Among these degradation processes, the UV solar radiation is the most efficient and the fastest, breaking down the plastic litter lying on the beach or exposed to air (Andrady, 2011). On the other hand, in the case of biodegradation, the microbial species that are able to metabolize polymers are rare in nature, hence common plastics do not biodegrade fast enough. Nonetheless, there are some examples of biopolymers that can undergo Table 10.3: Main markets where primary microplastics are added in Europe, estimation of mass production in tons/year in 2017 and main polymer types fabricated per market (Bintein, 2017). Product Cosmetics/ personal care Paints and coatings Detergents Oil and gas industry Agriculture

Tons/year (2017) 714 220 142 2

Difficult to estimate Industrial Difficult to abrasives estimate Minor industries 1.6

Main polymer types Polyurethane (about 50% of all microplastics in cosmetics), polyethylene, cellulose acetate, polylactic acid, Nylon-11 Acrylic polymers, fibers of polyamide, polyacrylonitrile Polyurethane, polyester, polyamide, acrylic, PMMA, PET glitters, rheology modifiers, polyethylene Additives, cross-linking agents, wax inhibitors Used as coatings to form pills and control the release of fertilizers, polysulfone, polyacrylonitrile, cellulose acetate PMMA particles, rubbers, polyethylene


Membrane sensors for pollution problems 347 biodegradation: chitins (Poulicek & Jeuniaux, 1991), chitosan (Andrady & Pegram, 1992), and a few synthetic polymers such as aliphatic polyesters do biodegrade rapidly in the sea (Mayer et al., 1996). Taking all this information into account, it is essential to understand that microplastics are very difficult to degrade floating in a cold ocean or sea. Hence, it is essential to search for alternative detection and remediation techniques.

10.3.2 Microplastics removal from wastewater One of the important contributors of microplastics to the oceans and seas is the wastewater. This is because of the lack of proper removal technology in standard screening methods available today (Carr et al., 2016; Talvitie et al., 2017). The common particle removal methods in wastewater treatment plants (WWTPs) are based on three types of treatments: (1) pretreatments, (2) primary treatments, and (3) secondary treatments. These procedures remove approximately 75% of microplastics from wastewater (Hu et al., 2019). There is a clear need of an improvement in the separation procedures of WWTPs, and membranes are a promising approach for this purpose. Recently an additional treatment stage based on membrane separation was introduced to the WWTPs (tertiary treatment) and an increase in the microplastics removal up to 98% was observed. The 2% of nonrejected microparticles corresponded to either microplastics with sizes below 20 μm or to nanoplastics (Poerio et al., 2019; Silva et al., 2018). Coagulation steps combined with, for example, ultrafiltration (UF) membranes (pore sizes between 1 and 100 nm) result in a rejection of organic matter as well as microplastics. However, the final effluent still may consist of some fraction of plastic particles (Talvitie et al., 2017; Mason et al., 2016), which might be due to the degradation of plastics in a water environment that can affect the molecular weight of the plastic litter, resulting in an increased possibility to pass through the membrane (Mason et al., 2016). Membrane bioreactors that were claimed to reject 99.9% of microplastics with sizes above 20 μm from wastewater are another example where membrane technology is efficiently used in the removal of micropollutants (Talvitie et al., 2017). Moreover, the dynamic membrane (DM) technology was investigated for microplastic rejection as well. A highly permeable membrane with big pores was used to allow the formation of a cake-layer with large, suspended solids to obtain a selective barrier. Such a system requires lower pressures than UF and microfiltration (MF) membranes and no extra chemicals are needed (as it is commonly used in the coagulation steps in the WWTPs) (Ma et al., 2013a,b). Nevertheless, even though the rejection of microplastics was in the range of 90%, only the particles in the range of 90 μm or larger were filtrated (Li et al., 2018). Summing up, different membranes were used to study the influence on the removal of microplastics as part of the tertiary treatment of a WWTP. It was concluded that MF, UF, and reverse osmosis (RO) membranes and their derivatives (such as membrane bioreactors or DMs systems) and a combination of RO and UF membranes, will give rise to an almost total removal of microplastics and nanoplastics (Ziajahromi et al., 2017).

348 Chapter 10

10.3.3 Drinking water Purification of drinking water pollution is currently one of the biggest and most severe problems. Microplastics were found in inland water bodies such as lakes and rivers in different countries worldwide suggesting that open-air waterbodies are sensitive to mismanaged plastic wastes that can break down into smaller pieces creating micro- or even nanoplastics (Zhao et al., 2014; Lima et al., 2014). In addition, the presence of microplastics (0.5
10 μm in size) at a concentration of ca. 650 μg/L in drinking water from the plastic bottles is highly possible (Zuccarello et al., 2019). One of the conventional methods to remove microplastics from drinking water is by agglomeration and precipitation using Fe- and Al-based salts (Ma et al., 2019). However, it was demonstrated that UF membranes and a coagulation
precipitation method could be complementary in the removal of microliter, defined as pollutants in the micrometer range. Nevertheless, the membrane fouling effect should be carefully monitored (Ma et al., 2019) since it limits the effectiveness of the separation in the long term (Zhang & Chen, 2020). Fouling phenomena can be reversible or irreversible and are usually related to the hydrophilicity or hydrophobicity of the membrane surface. In general, hydrophobic surfaces favor the interaction with the organic species responsible for fouling, thus hydrophilic properties of the membrane are anticipated. To enhance the hydrophilic character of the membrane the skin layer composition should be controlled by incorporating hydrophilic fillers such as GO (Ma et al., 2020), zeolites (Dong et al., 2015), or certain MOFs (Echaide-Go´rriz et al., 2017). NF thin films, on the other hand, might be very effective in the removal of even the smallest microplastics due to their intermediate character between UF and RO membranes. In this specific case some part of the membrane is porous and the other is dense. In theory, the transport model that describes the transfer through the NF membrane is a mixture between the solution
diffusion model (typical for RO membranes) and a pore
flow model (typical for UF membranes). The result of such small differences is a slightly higher solvent permeation through NF than RO but a higher molecular weight cut-off in the latter than in the first (Vandezande et al., 2008).

10.3.4 Potential membranes for microplastic removal Even though the membranes for microplastics or nanoplastics removal are still under research and are not commercially available yet, there are some promising highly permeable thin films, effective in the removal of salts or light organic molecules that, in principle, should be smaller than the majority of micro- and nanoplastics. Such NF membranes, either in the form of thin-film composite or thin-film nanocomposite, are very attractive due to: (1) low clean water production costs, (2) high filtered water production, and (3) high retention. Moreover, some commercially available NF membranes fabricated by either large manufacturers (i.e., Filmtec, Nitto Group, and Koch Membranes) or smaller

Membrane sensors for pollution problems 349 ones (i.e., Polymem Membrane Manufacturer, Lanxess, and Synder Nanofiltration) show outstanding performances that are interesting even for nanoplastics removal (https:// synderfiltration.com/nanofiltration/membranes/, access June 2021; https://lanxess.com/en/ Products-and-Solutions/Brands/Lewabrane, access June 2021; https://www.polymem.fr/en/ products/, access June 2021; https://www.lenntech.com/products/membrane/romembranes. htm, access June 2021).

10.3.5 Microplastic detection Membrane technology could be also successfully used as a sensor and could help in the detection of microplastics, which is a difficult and time-consuming process. The main challenges in microplastic detection in water consist of (1) capturing of microplastics from water or sediment, (2) plastic type identification (due to discoloration, abrasion, fragmentation), and (3) separation of different types of plastics in one sample (high-density, low-density) (Eerkes-Medrano et al., 2015). In general, microplastics characterization could be divided into chemical and physical type of analysis. Chemical characterization is related to the chemical composition of the plastic litter while physical analysis involves the characterization of the shape, size, and color (Sun et al., 2019). Considering the treatment of the wastewater, the sample is collected in a big container, separated by pumping, filtrated, and collected with an autosampler (Sun et al., 2019). Taking into account that collected water has to be filtered, the mesh/pore size of the filtrating membranes is of crucial importance. There are three main sample detection and processing techniques: (1) density separation, (2) membrane filtration and sieving, and (3) visual sorting. Density separation technique, based on the difference in densities of plastics and sediments, is a promising approach for the quantification and detection of microplastics, however, the volume of the sample analyzed by this method is limited (Hidalgo-Ruz et al., 2012; Corcoran et al., 2009). Hence, membranes are a promising candidate for a detection of microplastics via size exclusion. Micro- and macroparticles are separated by passing them through a filter with pore sizes in the range of 1
2 μm, usually with the help of vacuum (Noren, 2007). This technique enables different size categories to be distinguished and could be combined with a type of chemical analysis such as Raman spectroscopy, infrared spectroscopy, Fourier-transform infrared spectrophotometry, scanning electron microscopy, or differential scanning calorimetry, etc. (Malankowska et al., 2021) (Fig. 10.3).

10.4 Pathogens Nowadays, especially in developing countries, waterborne diseases cause serious mortality due to low water quality. In order to treat and prevent health problems, detection of

350 Chapter 10

Figure 10.3 Schematic representation of the membranes used in sensing procedures as a function of the part of the ocean. Adapted from Malankowska, M., Echaide-Gorriz, C., Coronas, J. (2021). Microplastics in marine environment: a review on sources, classification, and potential remediation by membrane technology. Environmental Science: Water Researchearch and Technology. https://doi.org/10.1039/D0EW00802H.

pathogens is of vital importance. Salmonella, Escherichia coli, Campylobacter, Legionella, and Listeria are extensively studied pathogenic bacteria in order to address health and safety issues in the food industry, water and environmental quality control, and clinical diagnosis (Lazcka et al., 2007). On the other hand, among hundreds of viral infections, lately SARS-CoV-2, HIV, hepatitis, Zika, and Ebola have been a threat to human health (Bukasov et al., 2021). The latest pandemic, SARS-CoV-2, evinced the necessity of accurate, appropriate, and fast detection. Established detection methods, namely, polymerase chain reaction, culture and colony counting methods, and immunology-based methods are considered as time-consuming and complex. Therefore, recently, biosensors have gained an increasing attention in pathogen detection owing to their reliable results in a relatively shorter time (Lazcka et al., 2007). Biosensors consist of two main components; a biorecognition element and a transducer. The latter can be classified depending on its working principle as electrochemical, optical, thermometric, piezoelectric, magnetic, and micromechanical.

Membrane sensors for pollution problems 351 Membranes can contribute to the biosensor mechanism by taking different roles, that is, a mechanical support, a component helping transduction, a filter diluting or concentrating pathogens, and an immobilizing agent for active proteins (van den Hurk & Evoy, 2015). In the following section, various examples of membrane-based biosensors utilized for pathogen detection in water sources will be covered. The main purpose of the biosensors is to transform the interaction between biomolecule and probe molecule into an observable signal output. Electrochemical and optical methods are the most popular transduction signal forms used in biosensors.

10.4.1 Electrochemical methods In electrochemical sensors, the response to a constant or an alternating excitation can be quantitatively monitored by amperometric, potentiometric, or impedance-based methods (Lojou & Bianco, 2006). For detection of O157:H7, a very pathogenic variant of E. coli, in water samples, Theegala et al. (2008) designed an oxygen electrode-based amperometric biosensor in which an outer cellulosic membrane and an inner Teflon membrane were utilized. In the design, a nitrocellulose membrane guaranteed the immobilization of O157:H7
horseradish peroxidase (HRP) conjugate, while the Teflon membrane separated the electrode and electrolyte fluid, thus allowing transport of oxygen molecules. After the pathogens’ immobilization on the outer membrane, a decrease in enzyme activity alters the oxygen concentration in the electrolyte. Applying 0.7 V potential difference allows oxygen reduction to hydroxide ion that is proportional to concentration. Therefore, it is possible to correlate E. coli O157:H7 concentration with the dissolved oxygen concentration (Theegala et al., 2008). In a resistance-based biosensor device, polypyrrole-coated polypropylene microfiber membranes were utilized for E. coli O157:H7 detection (McGraw et al., 2012). Glutaraldehyde was used in order to bond the antibodies of pathogen to the membrane. The immobilization of the bacteria on the membrane surface increased the resistance of membrane. The increase was used to quantify the bacteria concentration immobilized on membrane surface for a 0
9 CFU/mL range (McGraw et al., 2012).

10.4.2 Optical methods Another common pathogen detection technique is by optical biosensors that allow direct, real-time, and label-free detection of various biocomponents. Being sensitive, specific, small, and cost-effective are the most salient features of optical techniques (Damborsky´ et al., 2016). In optical biosensors, the interaction between the biocomponent and the

352 Chapter 10 transducer can be characterized by colorimetry, luminescence techniques, absorbance, or radioactivity (van den Hurk & Evoy, 2015). In order to quantitatively detect E. coli O157:H7, Park et al. (2008) developed an enzyme-linked immune-strip biosensor utilizing four different types of membranes: a glass fiber membrane, a glass membrane, a nitrocellulose membrane, and a cellulose membrane were arranged from bottom to top as the sample application pad, conjugate release pad, signal generation pad, and absorption pad, respectively (Fig. 10.4). Briefly, the sample solution containing E. coli O157:H7 had an immune-reaction with HRP forming an E. coli O157:H7/HRP complex which has a secondary immune-reaction with immobilized monoclonal antibody later on the signal generation pad. After immobilization of the complex, an enzyme substrate fed from the substrate application pad has a reaction with HRP resulting in an observable signal. Later, the mark of the reaction is transformed into colorimetric signals for capture with a digital camera for a quantitative characterization (Park et al., 2008).

Figure 10.4 Schematic representation of membrane based immuno-strip biosensors for Escherichia coli O157: H7 detection based on: (A) immuno-reaction in vertical direction and (B) enzymatic reaction in horizontal direction. Reprinted from Park, S., Kim, H., Paek, S.H., Hong, J.W., & Kim, Y.K. (2008). Enzymelinked immuno-strip biosensor to detect Escherichia coli O157:H7, Ultramicroscopy, 108, 1348
1351. https://doi. org/10.1016/j.ultramic.2008.04.063. Copyrights 2008 with permission from Elsevier.

Membrane sensors for pollution problems 353 Another waterborne disease that threatens the public health is typhoid, caused by Salmonella typhi bacteria present in poor-quality water sources. Conventional microbiological methods consist of several time-consuming steps, such as isolation, enrichment, and identification of bacteria, that can take 24
72 h (June et al., 1996). Jain et al. (2012) developed a simple, fast, and cost-effective technique that can quantitatively detect S. typhi up to 2000 cells/mL. The biosensor consists of a surface aminated black isoporous polycarbonate membrane that immobilized the bacteria by using a glutaraldehyde linker. Next, the amount of linked bacteria was calculated by a colorimetrical method (Jain et al., 2012). An interesting study was carried out for detection of E. coli considering the requirements of a space station (Glazier and Weetall, 1994), where the sensor design, limited space, lack of scientific personal to operate the analysis, and limited usage of disposable materials were the main criteria. In this regard, an E. coli biosensor was devised by utilizing the autofluorescence properties of the bacterium. A silver metal membrane filter with 0.45 μm pores was chosen to collect the E. coli and to avoid the overlapping fluorescence signals. Following this, the number of bacteria was quantified by a microscope and a counter. However, the authors pointed out that, despite the advantages, the technique might fail due to low selectivity in the presence of other organics (Glazier and Weetall, 1994).

10.5 Conclusion and future trends The competitive advantage of membranes over their peers in environmental pollution sensors are due to: (1) ability to guarantee high sensitivity by capturing the analytes from complex gaseous or aqueous mixture; (2) ensuring reliability by rejecting competitors; and (3) extending the shelf life by protecting the recognition unit and the transducer from aggressive media and fouling. The permeability and selectivity of the membranes employed in the detection of gaseous pollutants is governed by the solution
diffusion model. Tendentially, the embodiment of nanotechnologies, such as MOFs into the polymeric membranes, favors the selective permeation of the analytes, whereas the employment of conductive materials aims to facilitate the transmission of electrochemical signals. Nevertheless, PANI has gained more attention because of its intrinsic gas-sensitive and conductive properties. Pollution with micro- or nanoplastics constitutes a global concern due to their prevalence as stable pollutants in water and in soil. Membrane technology (especially MF, UF, and NF) is a promising approach that is suitable for the removal of secondary microplastics from WWTPs effluents. Moreover, membranes show successful performance in the detection of microplastics by size exclusion that can be tuned by designing membranes with different pore sizes. Undoubtedly, the COVID-19 outbreak has stressed upon the dire need for the development of advanced biosensors to detect the presence of pathogens. Furthermore, in this case,

354 Chapter 10 membrane technology is a key component acting as a passive mechanical support and an active filter for receptors responsible for the detection. Overall, the achievements in membrane technology are fundamental to designing specific sensors characterized by high reliability, sensitivity, and long shelf life. However, the complexity of natural samples and the growing wide variety of pressing environmental issues continuously require the development of novel tailor-made advanced membranes with improved chemical and steric recognition.

List of acronyms CFU DC EDTA FTIR GO HIV HRP IDE ISE IUPAC LED LPFG MF MOF MWCNT NF NPOE PAA PAN PANI PDMS PET PMA PMMA PS PTFE PVA PVC QCM RO SARS-COV-2 SPE TBA HFP UF WWTP XRD ZIF

colony forming unit direct current ethylenediaminetetraacetic acid fourier transform infrared spectroscopy graphene oxide human immunodeficiency virus horseradish peroxide interdigited gold electrode ion-selective electrode international union for pure and applied chemistry light-emitting diode long-period fiber grating microfiltration metal
organic framework multiwall carbon nanotube nanofiltration 2-nitrophenyl octyl ether polyacrylic acid polyacrylonitrile polyaniline polydimethylsiloxane polyethylene terephthalate polymethyl acrylate polymethyl methacrylate polystyrene polytetrafluoroethylene polyvinyl alcohol polyvinyl chloride quartz crystal microbalance reverse osmosis severe acute respiratory syndrome coronavirus 2 solid polymer electrode tetrabutyl ammonium hexafluorophosphate ultrafiltration wastewater treatment plants X-ray diffraction zeolitic imidazolate framework

Membrane sensors for pollution problems 355

List of symbols A Ci,f Ci,p Di Di’ Fp Ji Mi Pi Pi’ t αi, j ΔCi δ

cross-sectional area concentration of species i on feed side concentration of species i on permeate side diffusion co-efficient of species i effective diffusivity of species i trans-membrane pressure molar flux of species i mass transfer coefficient of species i permeability of species i permeance of species i time selectivity of species i with respect to j concentration gradient of species i thickness

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Index Note: Page numbers followed by “f” and “t” refer to figures and tables, respectively.

A Absorbed Pb, 152 153 Acceptable daily intake (ADI), 198 200 Acetone, 263 264, 266 267, 277, 279 Acid deposition, 7, 22, 34, 39 Acid rain, 79 Active antifouling strategies, 313 314 Acute cadmium exposures, 86 87 AD. See Adsorption (AD) ADD. See Average daily dose (ADD) Additives materials, 268 269 ADI. See Acceptable daily intake (ADI) Adsorption (AD), 139, 167, 189 191, 255 256, 300 Advanced antifouling strategies, 311 316 Advanced materials, 268 269 Advanced oxidation processes (AOPs), 196 197, 208 209 Aerobic wetlands, 166 AFM. See Atomic Force Microscopy (AFM) AI. See Artificial Intelligence (AI) Air cleaning filters, 268 membranes, 257 260 contaminants in air pollution, 256f materials for, 265 269 polymeric membrane preparation for, 260 264 technology applications in, 270 284

and purification, 258t Air conditioners, 281 284 membrane humidification or evaporative cooling, 282f membrane vacuum drying, 282f Air filtration, 269, 273, 274t Air monitoring system, 60 61 Air pollutants, 2, 4, 8, 24, 39, 42 long range transport of, 26f Air pollution, 1 2, 39, 45, 57, 78 81, 116 122, 255 256, 336 342. See also Water pollution advances in air pollution monitoring, 60 73 high density PM2.5 monitoring network, 71f IoT and information communication technologies for sensors, 64 70 modern air pollution monitoring network, 72f modern monitoring network, 70 73 saturation monitoring, 60 64 anthropogenic air pollutants, 5t atmospheric trace gases and elements, 6t categories of membrane-based gas sensors, 338 340 evolution, 26f limits and cancer classification for some important pollutants, 5t mechanisms of gas transport, 338t

363

membrane-based gas sensors, 336 membrane-based sensors for air pollution detection, 343t most significant, 3t in Po Valley, 3f and polar regions, 27 34 recent breakthrough in membranes for air pollution sensing, 340 342 spatial scales of, 21 25 atmospheric pollution, 21t multisource and multiple adverse effects of, 23f natural and anthropogenic emissions, 24t system, 22 use of radon in air pollution data interpretation, 49 54 index ISA and experimental values of PM10, 55f natural radioactivity in summertime and wintertime, 52f radon measurements with daily concentration of PM10, 53f working principle of membranebased gas sensor, 336 338 Air quality, 45, 49, 54, 67, 69t, 78, 116 122, 255 256 Air transport mechanism in membranes, 270 272 solution-diffusion mechanism in dense polymeric membrane, 270f Air-conditioning systems, 257, 285 Airborne As, 138

364 Index Airborne Hg(0), 143 144 Alkylphenols (APs), 185, 194 195 Alkylphenols and polyethoxylated precursors (APEOs), 194 195, 201 Alkylphenols ethoxylates (APEs), 185 ALS. See Amyotrophic lateral sclerosis (ALS) Aluminum, 9 10, 207, 264 Alzheimer’s diseases, 79, 147 152 AMDEs. See Atmospheric mercury depletion events (AMDEs) Ammonia (NH3), 8 Ammonium nitrate (NH4NO3), 8, 19 Ammonium sulfate ((NH4)2SO4), 6 7 Amyotrophic lateral sclerosis (ALS), 148 152 Analytical requirements, 62 Anthropogenic emissions, 4, 18 19, 24t, 25f, 28, 209 210 Antibacterial release biocidal metal-based nanomaterials, 314 Antibiotic resistance genes (ARGs), 199 200, 202 205 Antibiotic-resistant bacteria (ARB), 199 200 Antifouling membranes, 306 316 membrane design and manufacturing methods, 307 309 for polluted solvents treatment brief description of techniques for characterizing and understanding mechanisms membrane fouling, 326 327 membrane technology for aqueous streams, 296 321 membrane technology for organic solvent, 321 326 surface modification of membrane, 309 311 three-stage membrane fouling, 307f AOPs. See Advanced oxidation processes (AOPs)

APEOs. See Alkylphenols and polyethoxylated precursors (APEOs) APEs. See Alkylphenols ethoxylates (APEs) APs. See Alkylphenols (APs) Aqueous media, 295 Aqueous streams antifouling membranes, 306 316 bioadhesion, 316 320 fouling classification, 299 fouling mechanisms and interpretation, 299 300 membrane cleaning strategies, 300 306 membrane fouling, 296 299 membrane technology for, 296 321 methods, 320 321 new materials, 320 321 ARB. See Antibiotic-resistant bacteria (ARB) ARGs. See Antibiotic resistance genes (ARGs) Arsenic (As), 154 155 As-minerals, 138 exposure, 86 potentially toxic elements, 138 139, 147 148 toxicity of, 146 157 Arsenic-rich pyrite (Fe(S, As)2), 138 Arsenolite (As2O3), 138 Arsenopyrite (FeAsS), 138 Artificial Intelligence (AI), 299 Atmosphere, 48, 102, 138 evolution of pollutants in, 25 27 Atmospheric environment, 116 122 membrane-based atmospheric gas monitoring methods, 122t organic and inorganic compounds in soil, 117t organic and inorganic compounds in water and soil, 118t Atmospheric mercury depletion events (AMDEs), 32 33

Atmospheric pollutants, 39, 73, 183 184, 277 Atmospheric pollution, 21t, 60 Atmospheric stability, 49, 54 60 concentration of NO, NO2 and O3, 57f trend of oxidants, 59f Atomic Force Microscopy (AFM), 326 Atomic oxygen, 14 Auto-ID Lab. See AutomatedIdentification Laboratory (AutoID Lab) Automated-Identification Laboratory (Auto-ID Lab), 64 65 Average daily dose (ADD), 153 Azimut Station, 70

B BAC. See Biologically activated carbon (BAC) Backpulsing method, 302 BAF. See Biologically activated filters (BAF) Barium, 302 Bay region, 202 Benzene, 5t, 8 9, 53 54, 68, 90, 231 232 Benzophenone-3 (BP3), 193 194 Big data, 104 Bioadhesion, 316 320 adhesion functionality, 317 318 poly(dopamine) and proposed structures of PDA, 318f bioadhesion-assisted grafting, 318 reaction functionality of polydopamine, 318 320 Biodegradation, 189, 194 195, 202 205, 346 347 Biofilm removal and control, 306 Biofouling, 300, 306 mechanism, 300 Bioinspired adhesion chemistry, 316 320 Biologically activated carbon (BAC), 161 Biologically activated filters (BAF), 161

Index Biopolymeric materials, 265 268 Biopolymers, 229 230, 265 266, 268, 346 347 Biosensors, 339, 350 351 Bisphenol A (BPA), 185, 194 195, 199t Bisphosphenol-A, 81 82 Black carbon (BC), 4 Blood Pb, 152 153 Blood brain barrier, 150 153 BP3. See Benzophenone-3 (BP3) BPA. See Bisphenol A (BPA) Bromine (Br), 31 33

C CA. See Cellulose acetate (CA) Cadmium (Cd), 86 87, 137, 155 156 potentially toxic elements, 139 141, 148 149 toxicity of, 146 157 Cake formation/surface, 300 Calcium, 150 152, 302 Calibration, 62 Campylobacter, 349 350 Capillary electrophoresis (CE), 111 115 Carbon dioxide (CO2), 6t, 18 19, 27, 68, 88 Carbon monoxide (CO), 5t, 6t, 9 10, 336 Carbon nanotubes (CNTs), 229 230, 310f, 312 313 Carbon tetrachloride, 231 232 Carbon-based nanomaterials (CBNs), 312 314, 327 Carbon-containing PM, 24 25 Carbonate rocks, 140 Carcinogenic risk (CR), 153 Cardiovascular system, 85 86, 147 148 Casting coating methods, 264, 265f Cationic polymeric materials, 314 CBNs. See Carbon-based nanomaterials (CBNs) CCL-3. See Contaminant Candidate List 3 (CCL-3) CD. See Cyclodestrin (CD) CE. See Capillary electrophoresis (CE)

Cellulose acetate (CA), 229 230, 234t, 258t Cellulose nanocrystals (CNCs), 242 243 Central nervous system (CNS), 147, 255 Cesium (137Cs), 87 Chemical cleaning methods and agents, 302 Chloride ion (Cl ), 12 Chloroform, 112t, 263 264 Chromium (Cr), 137, 149 150, 156 potentially toxic elements, 141 142 toxicity of, 146 157 Chronic Cd-poisoning, 148 149 Circumstantial data, 150 152 City background pollution, 39 City increment, 39 Cleaning with gas, 304 Climate change, 27, 39, 183 184 “Cloud quality control” model, 70 71 CNCs. See Cellulose nanocrystals (CNCs) CNS. See Central nervous system (CNS) CNTs. See Carbon nanotubes (CNTs) Coagulation methods, 160 162 Coating methods, 264 Coexistence, 66, 312f, 313 Colorectal cancer, 86 87 Compliance testing, 66 Concentration polarization, 298, 300 Concentration-driven process, 256 Conductivity, 105 106, 162, 265 266, 269, 339 341 “Coning” effect, 48 Connectivity, 66 Connectivity, Continuity, Compliance, Coexistence, Cyber security (5C), 66 Constructed wetlands, 166 167 Contact angle, 240 242, 326 327 Contaminant Candidate List 3 (CCL-3), 186 187

365

Contaminated waters, biological treatment of, 159 160 Continuity, 66 Conventional direct gas sensing methods, 338 339 Coordination compounds. See Metal organic frameworks (MOFs) Coronavirus (COVID-19), 274t, 276, 283 285, 335, 353 354 COVID-19. See Coronavirus (COVID-19) CR. See Carcinogenic risk (CR) Crystallinity, 266 267, 267t, 327 Cyber security, 66 Cyclodestrin (CD), 269 Cytochromes P450, 202

D D isomer-lactic acid, 268 Daily intake (DI), 153 Darcy’s law, 296 298 DEET. See Diethyltoluamide (DEET); N,N-diethyl-mtoluamide (DEET) Delayed demixing, 261 262, 262f Demethylation, 143 144, 150 152 Deposition velocity, 17, 42 43 Detection signal, 337 338 DGT. See Diffusive gradient in thin-film technique (DGT) DI. See Daily intake (DI) Dichloroethane, 231 232 Diet, 80 Diethyltoluamide (DEET), 206 Diffusion solubility, 338t Diffusion-based method, 102 104 Diffusive gradient in thin-film technique (DGT), 102 104, 107 110, 108f, 109f, 115 116 3,4-dihydroxyphenylalanine (DOPA), 316 Dioxin-like PCBs (dl-PCBs), 187 188, 202 Dioxins, 25 26, 79, 86, 90 Dip coating methods, 265f Direct sampling and detection, 104 107

366 Index Dissolved organic carbon (DOC), 158, 161 Dissolved organic matter (DOM), 140, 143 Dissolved oxygen (DO), 139 dl-PCBs. See Dioxin-like PCBs (dl-PCBs) DM. See Dynamic membrane (DM) DO. See Dissolved oxygen (DO) DOC. See Dissolved organic carbon (DOC) DOM. See Dissolved organic matter (DOM) Dopamine, 316 317, 318f, 320 Dose taken (DT), 153 Drinking water, 137, 146 148, 348 contamination, 188f international directives on, 184 188 treatment plants, 202 209 organic contaminants detected in drinking water, 203t Drinking water effect level (DWEL), 198 199, 199t Drinking Water Parameter Cooperation Project, 186 187 Dry adiabat, 44 45 DT. See Dose taken (DT) Dust, 1, 10, 68, 70, 141, 155, 255, 273 DWEL. See Drinking water effect level (DWEL) Dynamic membrane (DM), 347

E Ebola, 349 350 EC. See Elemental carbon (EC); European Commission (EC) ECs. See Emerging contaminants (ECs) EDCs. See Endocrine disrupting compounds (EDCs) EDTA. See Ethylenediaminetetraacetic acid (EDTA) EDX. See Energy-dispersive X-ray technique (EDX)

EIPS. See Evaporation-induced phase separation (EIPS) Electric field, 88, 283 284, 304, 305f Electrical methods, 304 305 Electrochemical methods, 351 Electrochemical transducers, 339 340 Electrocoagulation, 159, 162 Electrokinetics, 304 Electromagnetic pollution, 88 Electrospinning, 262 264, 263f, 273 275 membrane formation via NIPS, 262f parameters affecting electrospinning, 263t Electrospun nanofibers, 283 Electrospun nanofibrous membranes, 273 275 Electrospun polyurethane fibers, 280 Elemental carbon (EC), 13 Elemental removal processes, 159 160 biological treatment of contaminated waters, 159 160 electrocoagulation, 159 membranes, 159 Emerging contaminants (ECs), 183 184 Emissions, 2, 39, 91 of pollutants, 2 Endocrine disrupting compounds (EDCs), 183 184, 186 187, 194, 199t, 201 202, 209 210 Endocrine disruptors, 183 184 Energy-dispersive X-ray technique (EDX), 326 Environmental air pollution. See also Near-source air pollution air pollution and polar regions, 27 34 in Po Valley, 3f anthropogenic air pollutants, 5t atmospheric trace gases and elements, 6t

evolution of pollutants in atmosphere, 25 27 limits and cancer classification for some important pollutants, 5t most significant air pollutants, 3t most significant pollutants, 6 21 NH3, 8 NOx, 7 8 O3 and photochemical pollution, 14 21 SO2, 6 7 volatile organic compounds, 8 14 spatial scales of air pollution, 21 25 Environmental authorities, 101 Environmental monitoring, 102 environmental applications, 110 122 atmospheric environment, 116 122 soil environment, 115 116 water environment, 110 115 membrane-based monitoring methods, 103f, 104 110 Environmental pollutants, 102 104 Environmental pollution, 77, 80, 138, 285, 336, 353 Environmental quality standards (EQSs), 185 186 Environmental risk assessment of antibiotics, 199 200 EQSs. See Environmental quality standards (EQSs) Escherichia coli, 199 200, 240 242, 283, 349 350 O157:H7 detection, 351 352 Ethyl acetate, 263 264 Ethyl mercury (EtHg), 143 144 2-ethyl-hexyl-4trimethoxycinnamate (EHMC), 193 194 Ethylenediaminetetraacetic acid (EDTA), 164 EU Water Framework Directive (WFD), 185

Index European Commission (EC), 186 187 European Drinking Water Directive, 185 Evaporation-induced phase separation (EIPS), 261 Exfoliated molybdenum disulfide (eMoS2), 240 Extended Derjaguin-LandauVerwey-Overbeek (XDLVO), 323

ultrasonic removal of fouling layer, 305f Fourier transform infrared spectroscopy (FT-IR), 326 327 Free radicals, 78, 315f FT-IR. See Fourier transform infrared spectroscopy (FT-IR) Fumes, 1 Fumigation effect, 48

F

GAC. See Granular activated carbon (GAC) Gas permeability, 271 Gas sensors, 62 63, 68, 122, 336 340 Gas-chromatography, 104 105 Gas-diffusion-based methods, 111 115 Gaseous elemental mercury (GEM), 32 33 Gaseous media, 295 GBNs. See Graphene-based nanomaterials (GBNs) GEM. See Gaseous elemental mercury (GEM) Genetics, 80 Glutathione (GSH), 148 152 Glyphosate, 86 87 GO. See Graphene oxide (GO) Granular activated carbon (GAC), 198, 206 208 Graphene oxide (GO), 240, 312 313, 340 Graphene-based nanomaterials (GBNs), 314 315 Greenockite (CdS), 139 140 Groundwaters, 139, 144 146, 153 156, 158, 183 185, 189 192, 194 195, 208 209 GSH. See Glutathione (GSH)

Face masks, 273f, 276 Fanning, 48 Faraday’s Law, 105 Fatty acids, 152 153 Fe electrodes, 159, 161 162 Ferric chloride (FeCl3), 158 160 FIA. See Flow injection analysis (FIA) Fick’s first law, 108, 337 338 Filter life time efficiency, 273 Flow injection analysis (FIA), 111 122 Fluoropolymers, 265 266, 267t Flux, 240, 271 272, 313, 323, 337 338 FO. See Forward osmosis (FO) Forward osmosis (FO), 296, 308 309 Foulants, 296, 302, 306 307, 311, 326 approach, 306 307 with examples, 299t Fouling, 298 classification, 299 mechanisms and interpretation, 299 300 foulants with examples, 299t in membrane technology for organic solvents, 326 release, 313 strategies, 313 toxicity of NPs, 315f resistance, 311 hydrophilic membranes with fouling resistance properties, 312f strategies, 311 313

G

H Hagen Poiseuille equation, 271 Halogens, role of, 31 34 Harmful algal blooms, 83 84 Hazard quotient (HQ), 153 157 Hb. See Hemoglobin (Hb) HDWCs. See Human drinking water concentrations (HDWCs)

367

Health risk assessment approach of potentially toxic elements, 153 157 Healthcare industry, 101 Heavy metals, 33 34, 82, 86, 90, 102, 108 109, 115 116, 157 158, 166 Hemoglobin (Hb), 9 10 Hepatitis, 349 350 Hexavalent Cr, 149 150 High-energy microwaves, 88 Hollow fibers, 257, 265 266 Horseradish peroxidase (HRP), 351 352 HQ. See Hazard quotient (HQ) HRP. See Horseradish peroxidase (HRP) Human drinking water concentrations (HDWCs), 199 200, 200t Human immunodeficiency virus (HIV), 349 350 Hunter-Russell syndrome, 150 152 Hybrid membranes, 321, 341 Hydrogen peroxide, 16, 27 28, 78, 196 197 Hydrolysis, 161 162, 189 191, 346 Hydrophilic membranes, 234 239, 282, 312f, 313 Hydroxide, 143, 158 162, 165, 351 Hydroxyl radicals (OH), 7, 30, 196 197

I IARC. See International Agency for Research on Cancer (IARC) IIoT. See Industrial IoT (IIoT) In situ membrane-based monitoring technology, 115 116 Indium oxide (In2O3), 341 Individual protection devices, 272 276 electrospinning apparatus and process, 275f face masks and nanotechnology, 273f

368 Index Individual protection devices (Continued) membrane-based processes used for, 274t Indoor pollution, 81 Industrial IoT (IIoT), 73 Information communication technologies for sensors, IoT and, 64 70 Inorganic As, 147 148 Inorganic compounds in soil, 117t, 118t in water, 118t Inorganic Hg, 150 152 Inorganic NPs, 312 313 Inorganic species, 140 141 Instantaneous demixing, 261 262 International Agency for Research on Cancer (IARC), 4, 147 148 International Union for Pure and Applied Chemistry (IUPAC), 342 346 Internet of Things (IoT), 63, 65f and information communication technologies for sensors, 64 70 Ion-exchange membranes, 102 Ion-exchange-based sensor, 105 IoT. See Internet of Things (IoT) ITU. See Telecommunication Development Sector (ITU) IUPAC. See International Union for Pure and Applied Chemistry (IUPAC)

K Keratosis, 86 Knudsen diffusion, 271 272, 338t Knudsen equation, 271

L L isomer-lactic acid, 268 Land of Fires, 89 90 Large-scale environmental pollution assessments, 101 Lattice diffusion/convective flow, 338t Lead, 77, 79, 144 146, 152 153, 157 toxicity of, 146 157

Lead (Pb), 6t, 115 116, 137, 144 145, 152 153, 157, 185 Lead anglesite (PbSO4), 144 145 Lead cerussite (PbCO3), 144 145 Lead galena (PbS), 144 145 Lead tetroxide (Pb3O4), 146 Lead(II)oxide (PbO), 146 Legionella, 349 350 L. pneumophila, 91 92 Light pollution, 87 88 Limit of quantification (LOQ), 207 Liquid jets, 262 263, 341 Liquid membranes, 102, 105, 257, 258t Listeria, 349 350 Lofting, 48 Looping, 48 LOQ. See Limit of quantification (LOQ) Low cost sensors, 61 Low energy consumption, 61

M m-phenylenediamine (MPD), 308 309 Machine learning, 299 MACs. See Maximum admissible concentrations (MACs) MAPs. See Mussel adhesive proteins (MAPs) Mass spectrometry, 104 105 Mass transfer coefficient, 298, 337 338 Maximum admissible concentrations (MACs), 153 MD. See Membrane distillation (MD) Mechanical methods of membrane cleaning, 302 303 Mechanisms membrane fouling, brief description of techniques for characterizing and understanding, 326 327 Melanosis, 86 Membrane cleaning, 300 biofilm removal and control, 306 chemical cleaning methods and agents, 302

electrical or nonconventional methods, 304 305 ultrasonic removal of fouling layer, 305f flux history during membrane fouling, 301f with gas, 304 mechanical and physical methods, 302 303 conceptual electrostatic equilibrium model, 303f membrane before and after backpulsing in MF and UF process, 304f methods, 302 strategies, 300 306 Membrane distillation (MD), 229 230, 296 Membrane technologies, 229 230, 256, 295 296 applications in air cleaning, 270 284 air conditioners, 281 284 air transport mechanism in membranes, 270 272 individual protection devices, 272 276 recovery of vapors of organic substances from air, 277 281 for aqueous streams, 296 321 background of membrane technologies used in water remediation, 230 233 graphical depiction of MF, UF, NF, and RO, 232f guideline values of volatile organic compounds for drinking water purposes, 233t membrane-based processes, membrane’s pore sizes, MWCO, 231f environmental applications, 110 122 atmospheric environment, 116 122 soil environment, 115 116 water environment, 110 115

Index main materials, and challenges of, 297t membrane-based monitoring methods, 103f, 104 110 for organic solvents, 321 326 fouling in, 326 Membrane Technologies and Research Inc. (MTR), 281 Membrane-based monitoring methods, 102 111 direct sampling and detection, 104 107 membrane-based detection techniques, 106f passive sampling and detection, 107 110 membrane-based sensors, 109f Membranes, 101, 159, 162 165, 256, 295 for air cleaning, 257 260 membrane-based technologies, 258t PEBAX 1074 and SPEEK hollow fiber membranes, 259t polymer membranes for CO2 and CH4 separation, 258t air transport mechanism in, 270 272 bioreactors, 229 230 contactors, 229 230 crystallization, 229 230 design and manufacturing methods, 307 309 designing highly selective membranes, 309 phase inversion membranes, 308 thin-film composite polyamide membranes, 308 309 evaporative cooling, 282 283, 282f formation via NIPS, 262f fouling, 296 299, 297t, 298f gas separation, 229 230 humidification cooling, 282f materials, 323 additives and advanced materials, 268 269

for air cleaning, 265 269 polymeric and biopolymeric materials, 265 268 membrane-based air dehumidification process, 282 membrane-based amperometric detection, 105 membrane-based atmospheric gas monitoring methods, 122t membrane-based conductimetric sensors, 105 106 membrane-based detection techniques, 106f membrane-based electrochemical sensors, 105, 122 membrane-based gas sensors, 336 categories, 338 340 classification, 339f working principle of, 336 338 membrane-based optical sensors, 106 107 membrane-based techniques, 101 102 pore sizes, 231f sensors for pollution problems, 335 air pollution, 336 342 pathogens, 349 353 water pollution, 342 349 separation processes, 295 surface, 298 surface modification of, 309 311 advanced antifouling strategies, 311 316 fouling release strategies, 313 fouling resistance strategies, 311 313 passive antifouling membranes, 311 316 selective membranes formed with, 310f MEMS. See Microelectromechanical systems (MEMS) Mercury (Hg), 32, 137, 150 152, 156 157

369

potentially toxic elements, 142 144 role of, 31 34 toxicity of, 146 157 Metal dioxides, 302 Metal removal from water, 157 167 enhanced elemental removal processes, 159 160 metal removal in municipal wastewater treatment works, 158 159 Metal-oxide (MOx), 63 Metal organic frameworks (MOFs), 324t, 326 327, 340, 348, 353 Methane (CH4), 9 10, 27 oxidation, 31 Methyl mercury (MeHg), 83 84, 143 144 4-methyl-benzilidine-camphor (4MBC), 193 194 MF. See Microfiltration (MF) MFO. See Mixed-function oxidase (MFO) Microbial foulants, 302 Microelectromechanical systems (MEMS), 62 Microfiltration (MF), 229 230, 295, 347 Microplastics, 342 detection, 349 potential membranes for microplastic removal, 348 349 removal from wastewater, 347 Micropollutants, 188 Microporous organic polymers (MOPs), 320 Microprocessor unit (MPU), 66 67 Minamata disease, 150 152 Mixed matrix, 235t Mixed matrix membranes (MMM), 229 230, 233 234, 260 Mixed-function oxidase (MFO), 202 MMM. See Mixed matrix membranes (MMM)

370 Index Modern monitoring network, 70 73 high density PM2 5 monitoring network, 71f modern air pollution monitoring network, 72f MOFs. See Metal organic frameworks (MOFs) Molar flux, 337 Molecular weight cut-off (MWCO), 164, 231f Molybdenum disulfide (MoS2), 340 Monitoring networks, 63 64 MOPs. See Microporous organic polymers (MOPs) Moringa oleifera, 161 MPD. See m-phenylenediamine (MPD) MPU. See Microprocessor unit (MPU) mTAP project, 284 MTR. See Membrane Technologies and Research Inc. (MTR) Multiwall carbon nanotube (MWCNT), 239, 269 Municipal wastewater treatment works, metal removal in, 158 159 Mussel adhesive proteins (MAPs), 316 MWCNT. See Multiwall carbon nanotube (MWCNT) MWCO. See Molecular weight cut-off (MWCO)

N N,N-diethyl-m-toluamide (DEET), 193 N-methyl-D-glucamine resin, 115 116 Nafion, 340 Nanocomposite membranes, 229 230, 235t, 242 background of membrane technologies used in water remediation, 230 233

for organic compounds and pollutants removal from water, 233 243 GO-TiO2 composite, 241f mixed matrix and nanocomposite membranes, 235t polymeric-based membranes employed in membrane technologies, 234t Nanofiber membranes, 273 Nanofiber-based material, 275 Nanofibrous membranes, 278 Nanofilter, 163 Nanofiltration (NF), 229 231, 295 Nanomaterials, 312 313 Nanoparticle ethoxylates (NPnEOs), 185 Nanoparticles (NPs), 264, 315f Natural emissions, 4, 7 Natural gas, 258 260 Natural organic matter (NOM), 234 239, 242 243 Natural radioactivity, 50 52 Near-source air pollution, 39. See also Environmental air pollution advances in air pollution monitoring, 60 73 atmospheric stability and secondary pollutants, 54 60 different scales of pollution to local pollution, 40f elevated emission sources, 46 49 smoke plumes emitted by elevated sources, 47f near-source chemical and physical parameters, 40 43 thermal structure of troposphere, 43 46 use of radon in air pollution data interpretation, 49 54 New materials, 320 321 hybrid membranes, 321 new manufacturing and modification methods, 321 NF. See Nanofiltration (NF) NIPS. See Nonsolvent induced phase separation (NIPS)

Nitric acid (HNO3), 7 8, 19, 30, 57 58 Nitrogen (N), 8, 147 148 Nitrogen dioxide (NO2), 2, 7, 42, 54 55 Nitrogen oxides (NOx), 7 8, 27 28, 30, 41 42, 56, 63, 79 Nitrous acid (HONO), 27 28, 56 Noise pollution, 84 86 NOM. See Natural organic matter (NOM) Nonconventional methods, 304 305 Nonorganic arsenic, 86 Nonporous membranes, 270 Nonsolvent induced phase separation (NIPS), 234 239, 261 262, 308 membrane formation via, 262f nascent membrane/bath interface, 261f Nonsteroidal antiinflammatory drugs (NSAIDs), 189, 203t Nonylphenol (NP), 185, 199t NP. See Nonylphenol (NP) NPnEOs. See Nanoparticle ethoxylates (NPnEOs) NPs. See Nanoparticles (NPs) NSAIDs. See Nonsteroidal antiinflammatory drugs (NSAIDs)

O OC. See Octocrylene (OC); Organic carbon (OC) Octocrylene (OC), 193 194 Octylphenol (OP), 185 Octylphenol ethoxylates (OPEOs), 194 195 OH. See Hydroxyl radicals (OH) Oil disasters, 83 84 OM. See Organic matter (OM) OMMt. See Organically modified montmorillonite (OMMt) One-step modification method, 317 318 OP. See Octylphenol (OP) OPEOs. See Octylphenol ethoxylates (OPEOs) Optical methods, 351 353

Index Optical transducers, 339 340 Organic carbon (OC), 4 Organic compounds, 260 detection, 104 105 nanocomposite membrane for, 233 243 in of water bodies, 112t in potable water alkylphenols and bisphenol A, 194 195 drinking water treatment plants, 202 209 environmental and ecosystem effects, 198 202 international directives on surface and drinking waters, 184 188 PAHs, PBDEs, PCBs, and PCDD/Fs, 195 197 per-and polyfluoroalkyl substances, 197 198 personal care products, 192 194 pharmaceuticals, 189 192 sources, environmental dynamics, and final fate, 188 198 in soil, 117t, 118t in water, 118t Organic foulants, 302 Organic matter (OM), 9 10, 90, 143, 239 Organic media, 295 Organic micropollutants, 184, 188 Organic pollutants, 188 189 Organic solvent forward osmosis (OSFO), 323 Organic solvent nanofiltration (OSN), 322f, 323 Organic solvent reverse osmosis (OSRO), 322f, 323 Organic solvents, 295 membrane technology for, 321 326 fouling in membrane technology for organic solvents, 326 membrane materials, 323 membranes used in organic solvent filtration, 324t

principal problems, 323 325 membranes used in organic solvent filtration, 324t mixtures, 321 ultrafiltration of, 322 Organic species, 140 141 Organic substances from air, recovery of vapors of, 277 281 Organically modified montmorillonite (OMMt), 239 240 Organization for Economic Cooperation and Development, 78 OSFO. See Organic solvent forward osmosis (OSFO) OSN. See Organic solvent nanofiltration (OSN) OSRO. See Organic solvent reverse osmosis (OSRO) Oxygen (O2), 9 Ozone (O3), 14 21, 56, 58, 63 formation potential, 18 isopleth plot, 17f nitrogen-containing species, 20f transport, 39 in troposphere, 15f

P P4VP. See Poly(4-vinyl-pyridine) (P4VP) PA. See Polyamide (PA) PAC. See Polyaluminum chloride (PAC) PAH. See Poly aromatic hydrocarbons (PAH) PAHs. See Polycyclic aromatic hydrocarbons (PAHs) PAN. See Peroxyacetyl nitrate (PAN); Polyacrylonitrile (PAN) PANI. See Polyaniline (PANI) Parabens (alkyl-phydroxybenzoates), 193 Parkinson’s diseases, 79, 147 149 Particulate matter (PM), 2, 10 14, 255 airborne particulate matter collected in different environments, 13f

371

number, surface, and mass of airborne particulate matter, 11f O3 in troposphere, 15f Pasquill Gifford radiation, 49 Passive antifouling membranes, 311 316 Passive sampling and detection, 107 110 Passive tubes, 68 70 Pathogens, 349 353 electrochemical methods, 351 optical methods, 351 353 PBDEs. See Polybrominated diphenyl ethers (PBDEs) PCBs. See Polychlorinated biphenyls (PCBs) PCDD/Fs. See Polychlorinated dibenzo-p-dioxins and furans (PCDD/Fs) PCPs. See Personal care products (PCPs) PDA. See Personal Digital Assistant (PDA); Polydopamine (PDA) PE. See Polyethylene (PE) PEBAX 1074 hollow fiber membranes, 259t PEG. See Poly(ethylene glycol) (PEG) PEI. See Polyethylenimine (PEI) Per-fluoroalkyl substances (PFASs), 184, 197 198 Perfluorinated carboxylic acid (PFCAs), 197, 207 208 Perfluorinated carboxylic sulfonic acids (PFSAs acids), 197, 207 208 Perfluoroalkyl acids (PFAAs), 185 186, 197 198, 201, 208 Perfluorohexane sulfonic acid (PFHxS), 185 186 Perfluorononanoic acid (PFNA), 185 186 Perfluorooctane sulfonate (PFOS), 185 186, 197, 207 208 Perfluorooctanoic acid (PFOA), 185 186, 198, 207 208 Permeability, 267 of species, 337

372 Index Permeance, 337 Permeate flux, 296 298 Permeating flux, 271 Peroxy radicals (R-O-O-), 9 Peroxyacetyl nitrate (PAN), 19, 30, 234t, 265 266, 268, 308 Persistent organic pollutants (POPs), 33 34, 90, 187 Personal care products (PCPs), 183 184, 186 189, 192, 194 Personal Digital Assistant (PDA), 65 Perstraction, 323 Pervaporation, 229 230, 321 PES. See Polyethersulfone (PES) Pesticides, 86 87 PFAAs. See Perfluoroalkyl acids (PFAAs) PFASs. See Per-fluoroalkyl substances (PFASs); Polyfluoroalkyl substances (PFASs) PFCAs. See Perfluorinated carboxylic acid (PFCAs) PFHxS. See Perfluorohexane sulfonic acid (PFHxS) PFNA. See Perfluorononanoic acid (PFNA) PFOA. See Perfluorooctanoic acid (PFOA) PFOS. See Perfluorooctane sulfonate (PFOS) PFSAs acids. See Perfluorinated carboxylic sulfonic acids (PFSAs acids) Pharmaceuticals, 183 184, 189 192 classes detected in aquatic environment, 190t Pharmaceuticals and personal care products (PPCPs), 183 184, 195 197, 199t Phase inversion, 260 262 EIPS technique, 261 membranes, 308 NIPS technique, 261 262 TIPS technique, 262 VIPS technique, 262 Phosphorus (P), 147 148 Photochemical pollution, 14 21 nitrogen-containing species, 20f

ozone isopleth plot, 17f Photodegradation, 346 Phthalates, 81 82 Physical methods of membrane cleaning, 302 303 PIP. See Piperazine (PIP) Piperazine (PIP), 308 Plasma coated membranes, 264 Plastics, 342 347 Platanus acerifolia, 18 PM. See Particulate matter (PM) PNECs. See Predicted no-effect concentrations (PNECs) Poiseuille flow, 271 Polar atmosphere reactive nitrogen species in polar regions, 29f renitrification of, 28 31 Polar regions, 27 air pollution and, 27 34 renitrification of polar atmosphere, 28 31 role of halogens and mercury, 31 34 Polarization, 298 Pollutants, 2, 79, 115 116, 335 evolution of pollutants in atmosphere, 25 27 air pollution evolution, 26f long range transport of air pollutants, 26f nanocomposite membrane for pollutants removal from water, 233 243 Pollution, 39, 77, 335 form, 87 88 Poly aromatic hydrocarbons (PAH), 13, 23 24, 24t, 187, 202 Poly-fluoroalkyl substances (PFASs), 184, 197 198 Poly(4-vinyl-pyridine) (P4VP), 314 Poly(ethylene glycol) (PEG), 268 269, 311 Polyacrylonitrile (PAN), 234t, 308, 346t Polyaluminum chloride (PAC), 157 158 Polyamide (PA), 234t, 239 membranes, 320

polyamide-6 electrospun nanofibers, 283 Polyaniline (PANI), 340, 342, 353 Polybrominated diphenyl ethers (PBDEs), 195 197 Polychlorinated biphenyls (PCBs), 187 Polychlorinated dibenzo-p-dioxins and furans (PCDD/Fs), 187, 195 197 Polycyclic aromatic hydrocarbons (PAHs), 79, 185, 195 197 Polydopamine (PDA), 316 configurations, 319f reaction functionality of, 318 320 Polydopamine-coated ferroferric oxide (Fe3O4@PDA), 243 Polyesters, 340 Polyethersulfone (PES), 234t, 242 243, 308 Polyethylene (PE), 234t, 259 260 Polyethylenimine (PEI), 314 Polyimide-based membrane, 279 Polymeric coating, 264 Polymeric materials, 265 268, 340 Polymeric membranes, 265 266, 308 employed in membrane technologies, 234t preparation for air cleaning, 260 264 electrospinning technique, 262 264 phase inversion, 260 262 polymeric coating, 264 Polymerization reactions, 264 Polymers, 265 266 membranes, 257 258 for CO2 and CH4 separation, 258t Polypropylene (PP), 234t, 259 260 Polystyrene (PS), 258t, 342 Polysulfone (PSF), 234 239, 234t, 308 Polytetrafluoroethylene (PTFE), 267t, 340, 343t

Index Polyvinyl alcohol (PVA), 162 163, 274t, 340 Polyvinyl chloride (PVC), 234t, 340 Polyvinyl pyrrolidone (PVP), 318 320 Polyvinylamine (PVam), 164 Polyvinylidene fluoride (PVDF), 229 230, 234t, 308 POPs. See Persistent organic pollutants (POPs) Populus alba, 18 Pore plugging/blocking, 300 Pore restriction, 300 Potable waters, 229 230 Potassium (40K), 87 Potentially toxic elements, 137 As, 138 139 case studies, 160 165 coagulation methods, 160 162 membranes, 162 165 Cd, 139 141 Cr, 141 142 effectiveness of current treatment works, 165 167 lead, 144 146 mercury, 142 144 metal removal from water, 157 167 toxicity of As, Cd, Cr, Hg, and Pb, 146 157 arsenic, 147 148, 154 155 cadmium, 148 149, 155 156 chromium, 149 150, 156 guidelines limit and health risk assessment approach of, 153 157 lead, 152 153, 157 mercury, 150 152, 156 157 PP. See Polypropylene (PP) PPCPs. See Pharmaceuticals and personal care products (PPCPs) Predicted no-effect concentrations (PNECs), 198 200, 200t Pressure drop, 298 efficiency, 273 Pressure-driven process, 256 Primary microplastics, 342 346, 346t

Primary pollutants, 40, 54 Primary sulfide minerals, 144 145 Provisional tolerable weekly intake (PTWI), 154, 156 157 PS. See Polystyrene (PS) PSF. See Polysulfone (PSF) PTFE. See Polytetrafluoroethylene (PTFE) PTWI. See Provisional tolerable weekly intake (PTWI) Public health environmental pollution’s influence on air pollution, 78 81 case studies, 88 92 noise pollution, 84 86 other forms of pollution, 87 88 soil pollution, 86 87 water pollution, 81 84 PVA. See Polyvinyl alcohol (PVA) PVam. See Polyvinylamine (PVam) PVC. See Polyvinyl chloride (PVC) PVDF. See Polyvinylidene fluoride (PVDF) PVP. See Polyvinyl pyrrolidone (PVP)

Q QA. See Quaternary ammonium (QA) Quality of data, 62 Quaternary ammonium (QA), 314 Quercus, 18

R Radiation inversion, 44 Radio frequency identification (RFID), 64 65 Radon, 49 54 REACH. See Registration, Evaluation, Authorization, and Restriction of Chemicals (REACH) Reactive nitrogen species in polar regions, 29f Reactive oxygen species (ROS), 78, 314

373

Reduced GO (rGO), 315, 340 Regional pollution, 39 Registration, Evaluation, Authorization, and Restriction of Chemicals (REACH), 185 186 Reverse osmosis (RO), 157 158, 202 205, 229 230, 295, 347 RFID. See Radio frequency identification (RFID) rGO. See Reduced GO (rGO) RO. See Reverse osmosis (RO) ROS. See Reactive oxygen species (ROS)

S Safe Drinking Water Act (SDWA), 186 187 Salmonella, 349 350 S. typhi, 353 SARS-CoV-2, 276, 283 284, 349 350 Saturation monitoring, 60 64 EU Limits and standards with WHO guidelines, 62t Scanning electron microscopy (SEM), 68, 276, 326 Scorodite (FeAsO4. 2H2O), 138 SDWA. See Safe Drinking Water Act (SDWA) Seawaters, 110 111, 142, 146, 257, 296 Secondary microplastics, 346 Secondary organic aerosol (SOA), 12 13 Secondary pollutants, 21 22, 54 60 concentration of NO, NO2 and O3, 57f trend of oxidants, 59f SEM. See Scanning electron microscopy (SEM) Sensors, 63, 106 107, 335 environment monitoring, 69t IoT and information communication technologies for, 64 70 smart sensor building blocks, 67f technology, 63

374 Index Severe acute respiratory syndromes, 276 Short-chain PFAA, 208 Sick Building Syndrome, 91 92 Silver (Ag), 240 242 NPs, 264 Smart Citizen Kit, 70 Smart membranes, 284 Smell, 1 SOA. See Secondary organic aerosol (SOA) Soft coal, 2 Soil environment, 115 116 monitoring technologies, 116 organic and inorganic compounds in, 117t, 118t pollution, 86 87 system, 115 Solar irradiation, 42 Solid membranes, 102 matrix, 308 Spectroscopy techniques, 104 105 SPEEK. See Sulfonated PEEK (SPEEK) SPEEK hollow fiber membranes, 259t Sphalerite (ZnS), 139 140 Spin coating methods, 264, 265f Spray coating methods, 264, 265f Staphylococcus aureus, 283 Street increment, 39 Subnanoporous materials, 309 Sulfonated PEEK (SPEEK), 259, 259t Sulfur compounds, 7, 285 Sulfur dioxide (SO2), 6 7 Sulfur oxides (SOx), 7, 90, 257 Sulfur trioxide (SO3), 6 7 Sulfuric acid (H2SO4), 6 7, 16 Summer pollution, 16 Surface diffusion, 271 272, 338t Surface engineering, 309 Surface modification of membrane, 309 311 Surface waters, 184 international directives on, 184 188 Synthetic polymers, 158 159, 308, 346 347

T TDI. See Tolerable daily intake (TDI) Teflon, 259 260 Telecommunication Development Sector (ITU), 64 65 TEM. See Transmission electron microscopy (TEM) Temperature-induced phase separation (TIPS), 260, 262 Tetrachloroethylene, 231 232 Thermal inversion, 43 44 Thermal pollution, 88 Thermooxidative degradation, 346 Thermoplastic materials, 266 Thin-film composite polyamide membranes, 308 309 Thin-film technique, 102 Thorium (232Th), 87 Three-dimensional networks (3D networks), 262 263 Time-weighted average concentration, 108 TIPS. See Temperature-induced phase separation (TIPS) Tolerable daily intake (TDI), 185, 198 199 Toluene, 231 232 Trace elements, 153, 166, 185 Transmission electron microscopy (TEM), 326 Transport, 2 of air pollutants, 26f Triangle of death, 90 1,1,1-trichloroethane, 231 232 Trichloroethylene, 231 232 Troposphere O3 in, 15f thermal structure of, 43 46, 43f inversion layer by subsidence, 45f planetary boundary layer, 46f Tropospheric ozone (O3), 7, 14 Tungsten disulfide (WS2), 340 Tungsten oxide (WO3), 341 Turbulence process, 41 turbulence-related parameters, 50

Two-dimensional networks (2D networks), 262 263

U UCMR-3. See Unregulated Contaminant Monitoring Rule-3 (UCMR-3) UF. See Ultrafiltration (UF) UFPs. See Ultrafine particles (UFPs) Ultrafiltration (UF), 229 231, 295, 347 of organic solvents, 322 Ultrafine particles (UFPs), 11 Ultrasound, 304 Uniform nanofibers membranes, 262 263 Unregulated Contaminant Monitoring Rule-3 (UCMR-3), 186 187 Uranium (238U), 87 “Urban heat island” effect, 281 US Environmental Protection Agency (US EPA), 50, 147 148, 185 US EPA. See US Environmental Protection Agency (US EPA) US National Toxicology Program, 156

V Vapor-induced phase separation (VIPS), 260, 262 Vascular system, 86 87 Vibrio fisheri, 198 199 VIPS. See Vapor-induced phase separation (VIPS) Vitamins C and E, 80 VOCs. See Volatile organic compounds (VOCs) Volatile organic compounds (VOCs), 8 14, 17 18, 67, 79, 255, 277 CO, 9 10 control techniques, 278f particulate matter, 10 14 recovery, 279f VOC-limited region, 17 18

Index W Wastewater, microplastics removal from, 347 Wastewater treatment plants (WWTPs), 183 184, 189 192, 194 195, 347, 353 Water, 183 184 background of membrane technologies used in water remediation, 230 233 environment, 110 115 organic compounds in all kinds of water bodies, 112t flux, 300 organic and inorganic compounds in, 118t purification process, 307 308 quality monitoring, 110 111 security, 110 111 treatment technologies, 156 Water pollution, 81 84, 342 349 drinking water, 348 microplastic detection, 349 microplastics removal from wastewater, 347 plastics, 342 347 potential membranes for microplastic removal, 348 349

Water quality criterion (WQC), 198 199 Water Safety Plan approach, 192 WFD. See EU Water Framework Directive (WFD) WHO. See World Health Organization (WHO) Winter pollution, 16 Winter smog, 7 Wireless, 62 Wireless local area network (WLAN), 66 WLAN. See Wireless local area network (WLAN) Wood-burning fires, 1 World Health Organization (WHO), 78, 137, 147 148, 186 187, 231 232 Air Quality Guidelines, 16 WQC. See Water quality criterion (WQC) WWTPs. See Wastewater treatment plants (WWTPs)

X X-Ray Diffraction (XRD), 326 X-ray photoelectron spectroscopy (XPS), 326

375

XDLVO. See Extended DerjaguinLandau-Verwey-Overbeek (XDLVO) XPS. See X-ray photoelectron spectroscopy (XPS) XRD. See X-Ray Diffraction (XRD) Xylene, 231 232, 279

Y Young’s modulus, 313

Z Zeolitic imidazole framework (ZIFs), 340 ZIF-8, 341 ZIF-67, 340 Zeta potential, 242 243, 326 327 ZIFs. See Zeolitic imidazole framework (ZIFs) Zika, 349 350 Zinc oxide (ZnO), 341 ZMOD4510IA1R gas sensor module, 63 ZnO. See Zinc oxide (ZnO)