Sensing Technologies for Real Time Monitoring of Water Quality

A comprehensive guide to the development and application of smart sensing technologies for water quality monitoring

With contributions from a panel of experts on the topic, Sensing Technologies for Real Time Monitoring of Water Quality offers an authoritative resource that explores a complete set of sensing technologies designed to monitor, in real-time, water quality including agriculture. The contributing authors explore the fundamentals of sensing technologies and review the most recent advances of various materials and sensors for water quality??monitoring.

This comprehensive resource includes information on a range of designs of smart electronics, communication systems, packaging, and innovative implementation approaches used for remote monitoring of water quality in various atmospheres. The book explores a variety of techniques for online water quality monitoring including internet of Things (IoT), communication systems, and advanced sensor deployment methods. This important book:

• Puts the spotlight on the potential capabilities and the limitations of various sensing technologies and wireless systems
• Offers an evaluation of a variety of sensing materials, substrates, and designs of sensors
• Describes sensor implementation in agriculture and extreme environments
• Includes information on the common characteristics, ideas, and approaches of water quality and quantity management

Written for students and practitioners/researchers in water quality management, Sensing Technologies for Real Time Monitoring of Water Quality offers, in one volume, a guide to the real time sensing techniques that can improve water quality and its management.

LIBU MANJAKKAL, PhD, is Research Associate at Electronics and Nanoengineering and Engineering in the School of Engineering at University of Glasgow.

LEANDRO LORENZELLI, PhD, is Head of the Microsystems Research Unit at FBK-Center for Materials and Microsystems (Trento, Italy).

MAGNUS WILLANDER, PhD, is Former Chair Professor in Gothenburg University and Linköping University and Visiting Professor and Scientist in various countries.

About the Editors xiii

List of Contributors xv

Preface xix

Section I Materials and Sensors Development Including Case Study 1

1 Smart Sensors for Monitoring pH, Dissolved Oxygen, Electrical Conductivity, and Temperature in Water 3
Kiranmai Uppuluri

1.1 Introduction 3

1.2 Water Quality Parameters and Their Importance 4

1.2.1 Impact of pH on Water Quality 4

1.2.2 Impact of Dissolved Oxygen on Water Quality 5

1.2.3 Impact of Electrical Conductivity on Water Quality 5

1.2.4 Impact of Temperature on Water Quality 5

1.3 Water Quality Sensors 6

1.3.1 pH 7

1.3.1.1 pH Sensors: Principles, Materials, and Designs 7

1.3.1.2 Glass Electrode 7

1.3.1.3 Solid- State Ion- Selective Electrodes 8

1.3.1.4 Metal Oxide pH Sensors 8

1.3.2 Dissolved Oxygen 10

1.3.2.1 DO Sensors: Principles, Materials, and Designs 10

1.3.2.2 Chemical Sensors 10

1.3.2.3 Electrochemical Sensors 11

1.3.2.4 Optical or Photochemical Sensors 12

1.3.3 Electrical Conductivity 13

1.3.3.1 Conductivity Sensors: Principles, Materials, and Designs 13

1.3.4 Temperature 15

1.3.4.1 Temperature Sensors: Principles, Materials, and Designs 16

1.3.4.2 Thermocouples 17

1.3.4.3 Resistance Temperature Detector 17

1.3.4.4 Thermistor 17

1.3.4.5 Integrated Circuit 18

1.4 Smart Sensors 18

1.5 Conclusion 18

Acknowledgment 19

References 19

2 Dissolved Heavy Metal Ions Monitoring Sensors for Water Quality Analysis 25
Tarun Narayan, Pierre Lovera, and Alan O’Riordan

2.1 Introduction 25

2.2 Sources and Effects of Heavy Metals 26

2.3 Detection Techniques 26

2.3.1 Analytical Detection: Conventional Detection Techniques of Heavy Metals 26

2.3.2 Electrochemical Detection Techniques of Heavy Metals 26

2.3.2.1 Nanomaterial- Modified Electrodes 29

2.3.2.2 Metal Nanoparticle- Based Modification 29

2.3.2.3 Metal Oxide Nanoparticle- Based Modification 33

2.3.2.4 Carbon Nanomaterials- Based Modification 34

2.3.3 Biomolecules Modification for Heavy Metal Detection 35

2.3.3.1 Antibody- Based Detection 35

2.3.3.2 Nucleic Acid- Based Detection 37

2.3.3.3 Cell- Based Sensor 38

2.4 Future Direction 40

2.5 Conclusions 40

Acknowledgment 41

References 42

3 Ammonia, Nitrate, and Urea Sensors in Aquatic Environments 51
Fabiane Fantinelli Franco

3.1 Introduction 51

3.2 Detection Techniques for Ammonia, Nitrate, and Urea in Water 53

3.2.1 Spectrophotometry 53

3.2.2 Fluorometry 54

3.2.3 Electrochemical Sensors 54

3.3 Ammonia 59

3.3.1 Ammonia in Aquatic Environments 59

3.3.2 Ammonia Detection Techniques 62

3.4 Nitrate 65

3.4.1 Nitrate in Aquatic Environments 65

3.4.2 Nitrate Detection Techniques 65

3.5 Urea 67

3.5.1 Urea in Aquatic Environment 67

3.5.2 Urea Detection Techniques 69

3.6 Conclusion and Future Perspectives 71

Acknowledgment 71

References 71

4 Monitoring of Pesticides Presence in Aqueous Environment 77
Yuqing Yang, Pierre Lovera, and Alan O’Riordan

4.1 Introduction: Background on Pesticides 77

4.1.1 Types and Properties 77

4.1.2 Risks 78

4.1.3 Regulation and Legislation 79

4.1.4 Occurrence of Pesticide Exceedance 80

4.2 Current Pesticides Detection Methods 80

4.2.1 Detection of Pesticides Based on Electrochemical Methods 82

4.2.1.1 Brief Overview of Electrochemical Methods 82

4.2.1.2 Detection of Pesticides by Electrochemistry 82

4.2.2 Detection of Pesticides Based on Optical Methods 83

4.2.2.1 Detection of Pesticides Based on Fluorescence 87

4.2.3 Detection of Pesticides Based on Raman Spectroscopy 89

4.2.3.1 Introduction to SERS 89

4.2.3.2 Fabrication of SERS Substrates 91

4.2.3.3 Detection of Pesticide by SERS 92

4.2.3.4 Challenges and Future Perspectives 95

4.3 Conclusion 96

Acknowledgment 96

References 96

5 Waterborne Bacteria Detection Based on Electrochemical Transducer 107
Nasrin Razmi, Magnus Willander, and Omer Nur

5.1 Introduction 107

5.2 Typical Waterborne Pathogens 108

5.3 Traditional Diagnostic Tools 108

5.4 Biosensors for Bacteria Detection in Water 110

5.4.1 Common Bioreceptors for Electrochemical Sensing of Foodborne and Waterborne Pathogenic Bacteria 110

5.4.1.1 Antibodies 111

5.4.1.2 Enzymes 111

5.4.1.3 DNA and Aptamers 111

5.4.1.4 Phages 112

5.4.1.5 Cell and Molecularly Imprinted Polymers 112

5.4.2 Nanomaterials for Electrochemical Sensing of Waterborne Pathogenic Bacteria 112

5.4.2.1 Metal and Metal Oxide Nanoparticles 113

5.4.2.2 Conducting Polymeric Nanoparticles 114

5.4.2.3 Carbon Nanomaterials 114

5.4.2.4 Silica Nanoparticles 114

5.5 Various Electrochemical Biosensors Available for Pathogenic Bacteria Detection in Water 115

5.5.1 Amperometric Detection 115

5.5.2 Impedimetric Detection 121

5.5.3 Conductometric Detection 123

5.5.4 Potentiometric Detection 124

5.6 Conclusion and Future Prospective 126

Acknowledgment 127

References 127

6 Zinc Oxide- Based Miniature Sensor Networks for Continuous Monitoring of Aqueous pH in Smart Agriculture 139
Akshaya Kumar Aliyana, Aiswarya Baburaj, Naveen Kumar S. K., and Renny Edwin Fernandez

6.1 Introduction 139

6.2 Metal Oxide- Based Sensors and Detection Methods 140

6.3 pH Sensor Fabrication 141

6.3.1 Detection of pH: Materials and Method 141

6.3.2 Detection of pH: Surface Morphology of the Nanostructured ZnO and IDEs 144

6.3.3 Detection of pH: Electrochemical Sensing Performance 145

6.3.4 Detection of Real- Time pH Level in Smart Agriculture: Wireless Sensor Networks and Embedded System 149

6.4 Conclusion 151

Acknowledgment 152

References 152

Section II Readout Electronic and Packaging 161

7 Integration and Packaging for Water Monitoring Systems 163
Muhammad Hassan Malik and Ali Roshanghias

7.1 Introduction 163

7.2 Advanced Water Quality Monitoring Systems 167

7.2.1 Multi- sensing on a Single Chip 167

7.2.2 Heterogeneous Integration 169

7.2.3 Case Study: MoboSens 169

7.3 Basics of Packaging 171

7.4 Hybrid Flexible Packaging 173

7.4.1 Interconnects 174

7.4.2 Thin Die Embedding 176

7.4.3 Encapsulation and Hermeticity 178

7.4.4 Roll to Roll Assembly 180

7.5 Conclusion 181

References 181

8 A Survey on Transmit and Receive Circuits in Underwater Communication for Sensor Nodes 185
Noushin Ghaderi and Leandro Lorenzelli

8.1 Introduction 185

8.2 Sensor Networks in an Underwater Environment 186

8.2.1 Acoustic Sensor Network 186

8.2.1.1 Energy Sink- Hole Problem 187

8.2.1.2 Acoustic Sensor Design Problems 188

8.2.1.3 The Underwater Transducer 189

8.2.1.4 Amplifier Design 190

8.2.1.5 Analog- to- Digital Converter 194

8.2.2 Electromagnetic (EM) Waves Underwater Sensors 197

8.2.2.1 Antenna Design 198

8.2.2.2 Multipath Propagation 198

8.3 Conclusion 199

Acknowledgment 199

References 200

Section III Sensing Data Assessment and Deployment Including Extreme Environment and Advanced Pollutants 203

9 An Introduction to Microplastics, and Its Sampling Processes and Assessment Techniques 205
Bappa Mitra, Andrea Adami, Ravinder Dahiya, and Leandro Lorenzelli

9.1 Introduction 205

9.1.1 Properties of Microplastics 208

9.1.2 Microplastics in Food Chain 209

9.1.3 Human Consumption of Microplastics and Possible Health Effects 209

9.1.4 Overview 210

9.2 Microplastic Sampling Tools 212

9.2.1 Non- Discrete Sampling Devices 212

9.2.1.1 Nets 212

9.2.1.2 Pump Tools 213

9.2.2 Discrete Sampling Devices 215

9.2.3 Surface Microlayer Sampling Devices 215

9.3 Microplastics Separation 215

9.3.1 Separating Microplastics from Liquid Samples 215

9.3.1.1 Filtration 215

9.3.1.2 Sieving 216

9.3.2 Separating Microplastics from Sediments 218

9.3.2.1 Density Separation 218

9.3.2.2 Elutriation 218

9.3.2.3 Froth Floatation 219

9.4 Microplastic Sample Digestion Process 220

9.4.1 Acidic Digestion 221

9.4.2 Alkaline Digestion 221

9.4.3 Oxidizing Digestion 221

9.4.4 Enzymatic Degradation 222

9.5 Microplastic Identification and Classification 222

9.5.1 Visual Counting 222

9.5.2 Fluorescence 223

9.5.3 Destructive Analysis 223

9.5.3.1 Thermoanalytical Methods 224

9.5.3.2 High- Performance Liquid Chromatography 225

9.5.4 Nondestructive Analysis 225

9.5.4.1 Fourier Transform Infrared Spectroscopy 225

9.5.4.2 Raman Spectroscopy 226

9.6 Conclusions 228

Acknowledgment 229

References 229

10 Advancements in Drone Applications for Water Quality Monitoring and the Need for Multispectral and Multi- Sensor Approaches 235
Joao L. E. Simon, Robert J. W. Brewin, Peter E. Land, and Jamie D. Shutler

10.1 Introduction 235

10.2 Airborne Drones for Environmental Remote Sensing 237

10.3 Drone Multispectral Remote Sensing 239

10.4 Integrating Multiple Complementary Sensor Strategies with a Single Drone 241

10.5 Conclusion 242

Acknowledgment 243

References 243

11 Sensors for Water Quality Assessment in Extreme Environmental Conditions 253
Priyanka Ganguly

11.1 Introduction 253

11.2 Physical Parameters 255

11.2.1 Electrical Conductivity 255

11.2.2 Temperature 258

11.2.3 Pressure 260

11.3 Chemical Parameters 262

11.3.1 pH 262

11.3.2 Dissolved Oxygen and Chemical Oxygen Demand 265

11.3.3 Inorganic Content 268

11.4 Biological Parameters 271

11.5 Sensing in Extreme Water Environments 273

11.6 Discussion and Outlook 276

11.7 Conclusion 278

References 278

Section IV Sensing Data Analysis and Internet of Things with a Case Study 283

12 Toward Real- Time Water Quality Monitoring Using Wireless Sensor Networks 285
Sohail Sarang, Goran M. Stojanović, and Stevan Stankovski

12.1 Introduction 285

12.2 Water Quality Monitoring Systems 286

12.2.1 Laboratory- Based WQM (LB- WQM) 286

12.2.2 Wireless Sensor Networks- Based WQM (WSNs- WQM) 287

12.2.2.1 Solar- Powered Water Quality Monitoring 289

12.2.2.2 Battery- Powered Water Quality Monitoring 291

12.3 The Use of Industry 4.0 Technologies for Real- Time WQM 296

12.4 Conclusion 297

References 298

13 An Internet of Things- Enabled System for Monitoring Multiple Water Quality Parameters 305
Fowzia Akhter, H. R. Siddiquei, Md. E. E. Alahi, and S. C. Mukhopadhyay

13.1 Introduction 305

13.2 Water Quality Parameters and Related Sensors 306

13.3 Design and Fabrication of the Proposed Sensor 310

13.3.1 Sensor’s Working Principle 312

13.4 Experimental Process 312

13.5 Autonomous System Development 313

13.5.1 Algorithm for Data Classification 315

13.6 Experimental Results 318

13.6.1 Sensor Characterization for Temperature, pH, Nitrate, Phosphate, Calcium, and Magnesium Measurement 319

13.6.2 Repeatability 323

13.6.3 Reproducibility 325

13.6.4 Real Sample Measurement and Validation 327

13.6.5 Data Collection 330

13.6.6 Power Consumption 330

13.7 Conclusion 333

Acknowledgment 333

References 333

Index 339

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