Sensing Technologies for Real Time Monitoring of Water Quality

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