Earth Systems Protection and Sustainability: Volume 2

Foreword
Preface
Introduction
Contents
Contributors
Part I: Indonesia - Local People and Reasons to Conserve
Chapter 1: Competitive Bioaccumulation by Ceratophyllum demersum L.
1.1 Introduction
1.2 Climatic Conditions of the Competitive Bioaccumulation Experimental Site
1.3 Maintenance of Stock Cultures of Ceratophyllum demersum L.
1.4 Experimental Setup and Heavy Metal Analysis
1.5 Biomass Production Measurements
1.6 Quantification of Metals Removed from Nutrient Solutions by Plants Active Uptake
1.7 Statistical Analysis
1.8 Cd and Ni Removal from Water
1.9 Heavy Metal Effect on Plant Biomass Production
1.10 Conclusion
References
Chapter 2: Climate Change, Sustainability and Resilience in Egypt and Africa
2.1 Introduction
2.2 The Relationship Between Climate Change and Sustainable Development Goals
2.3 Effects of Climate Change on Different Sectors
2.3.1 Water Resources
2.3.2 Agriculture
2.3.3 Human Health
2.3.4 Energy
2.3.5 Tourism
2.4 Summary of Climate Change Impacts in Egypt
2.5 Economic Impacts of Climate Change in Egypt
2.6 Prediction of Nile Flow Changes Resulting from Climate Change
2.7 Climate Resilience
2.7.1 Water Resources
2.7.2 Agriculture
2.7.3 Human Health
2.7.4 Energy
2.7.5 Tourism
2.8 Mitigation Measures
2.8.1 Mitigation Measures in Egypt
2.8.2 Mitigation Measures in Africa
2.9 Policies and Collaborations Overcoming Climate Change in Egypt and Africa
2.9.1 Egyptian Policies, Success and Opportunities
2.9.2 Policies and Cooperation in Africa
2.10 Summary and Conclusions
References
Chapter 3: Mathematical Models Ensuring Freshwater of Coastal Zones in Arid and Semiarid Regions
3.1 Introduction
3.2 Climate Change and Water Resources
3.2.1 Groundwater and Climate Change
3.2.2 Impact of Climate Change on Sea Level Rise (SLR)
3.2.3 Impact of Climate Change on Precipitation
3.2.4 Impact of Climate Change on Hydrology and Water Resources
3.3 Groundwater Reservoirs
3.3.1 Aquifers
3.3.2 Aquitards
3.3.3 Aquicludes/Aquifuges
3.4 Groundwater Contamination
3.4.1 Saltwater Intrusion
3.4.2 Population and Overexploitation
3.5 Groundwater Models
3.5.1 Classification of Groundwater Models
3.5.2 Types of Mathematical Models
3.5.3 Solution Methods for Differential Equations
3.5.3.1 Analytical Solution
3.5.3.2 Numerical Solution
3.5.4 Numerical Model Codes
3.5.5 Water Modelling Packages
3.6 Case Study: The Nile Delta Aquifer (NDA), Egypt
3.6.1 Simulations of Saltwater Intrusion (SWI) in the Northern Delta Aquifer
3.6.1.1 Impact of Sea Level Rise
3.6.1.2 Impact on the Surface Water Hydrograph
3.6.1.3 Impact of Abstraction Rates
3.6.2 Management of Saltwater Intrusion (SWI) in Coastal Aquifers
3.6.2.1 Optimisation and Allocation of Abstraction Rates (OA)
3.6.2.2 Treatment and Recharge (TR)
3.6.2.3 Abstraction, Desalination, and Recharge (ADR)
3.6.2.4 Treatment, Recharge, Abstraction, and Desalination (TRAD)
3.7 Conclusions
References
Chapter 4: Multicriteria Decision-Making for Risks of Natural Disaster in Social Project Assessments
4.1 Introduction
4.2 The Solution Approach Used to Solve Risk Assessment Factors
4.3 Construction Scheme for IRDA (Hazard Disaster Risk Index)
4.4 Hazards, Vulnerability, and Resilience Models and Their Combination
4.4.1 Mass Removal (Flows)
4.4.2 Tsunami
4.4.3 Volcano
4.4.4 Fire
4.4.5 Vulnerability Model
4.4.6 Resilience Model
4.5 Model Consolidation Process (Hazard, Vulnerability, and Resilience)
4.6 Case Study: Risk Disaster of the Hospital in the Locality of Tomé, South of Chile
4.6.1 Conceptual Framework
4.6.2 Application of the Complementary Methodology of Risk Management
4.6.3 Functional Unit (FU)
4.6.4 Forest Fire Hazard
4.6.5 Hazards Due To Mass Movements, Removal and Flows
4.7 Conclusions
References
Part II: Indonesia - Visitors Learning to Conserve and Appreciate Pearls of the Forest
Chapter 5: Mathematical Modelling and Simulation of Chemical and Biological Reaction in Peat Solidification Work for Environme...
5.1 Introduction
5.2 Peat and Its Engineering Challenges
5.3 Peat Solidification Theory
5.3.1 Techniques in Peat Solidification
5.3.2 Stabilisation of Peat by Cement
5.3.3 Effect of Pozzolan as a Secondary Additive in Peat Stabilisation
5.4 Gaps in Peat Improvement Studies
5.5 Biological Reaction in Peat Solidification
5.5.1 Microbes in Peat
5.5.2 Microbes in Solidified Soil
5.5.3 Microbes in Cement Study
5.6 Chemical Reactions in Peat Solidification
5.6.1 Chemical Bonding/Sketching for Raw Peat
5.6.2 Fourier Transform Infrared (FTIR), Nuclear Magnetic Resonance (NMR) and X-Ray Diffraction (XRD) Analysis Explain Chemica...
5.6.3 Chemical Reaction Models of Peat Processes
5.6.4 Chemical Reactions Behind Soil Improvements
5.7 Case Study in Pontian, Johor, Malaysia
5.8 Conclusion
References
Chapter 6: Green Energy Conversion Systems
6.1 Introduction
6.2 Microbial Use for Dual Purposes
6.2.1 Soil Microbial Fuel Cell (SMFC) Design
6.2.2 Design of Boost Converter
6.2.3 Experimental Test of the Soil Microbial Fuel Cell
6.3 Results and Discussion of Soil Microbial Fuel Systems: Potential for Membership in Renewable Energy Mixes
6.4 Conclusion
References
Chapter 7: Flood Risk Estimation and Mapping: Present Status and Future Challenges
7.1 Introduction
7.2 Flood Risk Management: A Risk-Based Approach to Managing Floods
7.2.1 Flood Risk Analysis
7.2.2 Flood Risk Assessment
7.2.3 Flood Risk Reduction
7.2.4 Flood Inundation and Hazard Mapping
7.2.4.1 Quantification of Flood Hazard
7.2.4.2 Geomorphic Approaches
7.2.5 Flood Vulnerability Mapping
7.2.5.1 Various Approaches to Flood Vulnerability Assessment
7.2.6 Flood Risk Mapping
7.2.7 Flood Risk Reduction
7.2.7.1 Structural Measures
7.2.7.2 Nonstructural Measures
7.3 Case Study of the Mahanadi River Basin in India
7.3.1 Jagatsinghpur District: The Focal Point Witnessing Severe Flood Impacts in Odisha, India
7.3.2 Proposed Framework of Flood Risk Mapping
7.3.2.1 Estimation of Regionalized Design Rainfall ()
7.3.2.2 Quantification of Flood Hazard () Through Hydrodynamic Modeling
7.3.2.3 Analysis of Socioeconomic Vulnerability Analysis ()
7.3.2.4 Determination of Flood Risk Through Risk Classifier
7.3.3 Results and Discussion
7.4 Conclusion
References
Chapter 8: Trend Analysis of Rainfall: A Case Study of Surat City in Gujarat, Western India
8.1 Introduction
8.2 Study Area and Data Collection
8.2.1 Study Area
8.2.2 Data Collection
8.3 Methodology
8.3.1 Identifying Trends Using the Mann-Kendall Test in Seasonal Rainfall Data
8.3.2 Using Sen´s Slope Estimator to Provide a Measurement of Trends
8.4 Results and Discussion
8.4.1 Annual and Seasonal Rainfall of Surat
8.4.2 Magnitude of Trend of Rainfall in Surat
8.5 Conclusion
References
Part III: Desertification Risks and Contrasts from Southern Europe and the Philippines
Chapter 9: Risk Assessment Applications: Exposure, Safety, and Security
9.1 Introduction
9.2 Risk Assessment Process
9.2.1 Hazards Identification (Step One)
9.2.2 Exposure Assessment (Step Two)
9.2.2.1 Occupational Exposure
9.2.2.2 Environmental Exposure
9.2.2.3 Risk Related to Exposure to Polluted Air
9.2.2.4 Particulate Matter (PM) and Gaseous Phase
9.2.2.5 Carbon Monoxide (CO)
9.2.2.6 Nitrogen Oxides (NOx)
9.2.2.7 Sulphur Oxides (SOx)
9.2.2.8 Ozone (O3)
9.2.2.9 Lead (Pb)
9.2.2.10 Risk Related to Exposure to Polluted Water
9.2.2.11 Microbial Exposure Through Contaminated Water
9.2.2.12 Chemical Exposure Through Contaminated Water
9.2.2.13 Industrial Source and Human Dwelling
9.2.2.14 Agricultural Activities
9.2.2.15 Water Treatment or Material in Drinking Water
9.2.2.16 Pesticides Used for Public Health (Other Than Agriculture)
9.2.2.17 Naturally Occurring Risks
9.2.2.18 Risk Related to Exposure to Polluted Land
9.2.3 Risk Characterisation (Step 3)
9.2.4 Dose-Response Assessment (Step 4)
9.2.5 Risk Management (Step 5)
9.3 Case Studies Related to the Risk of Environmental Exposure
9.3.1 Yellowknife Gold Mine, Canada
9.3.2 Bhopal Gas Disaster, India
9.3.3 Lanzhou Region, Yellow River, China
9.4 Conclusion
References
Chapter 10: Application and Control of Quadrotors
10.1 Introduction
10.2 Applications of Quadrotors
10.2.1 Journalism, Filming, and Aerial Photography
10.2.2 Shipping/Delivery
10.2.3 Disaster Management, Search, and Rescue/Healthcare
10.2.4 Geographic Mapping
10.2.5 Structural Safety Inspections
10.2.6 Precision Agriculture
10.2.7 Wildlife Monitoring/Poaching
10.2.8 Law-Enforcement and Border Patrol
10.2.9 Construction Sites
10.2.10 Entertainment
10.2.11 Military and Law Enforcement
10.3 Modeling of Quadrotors
10.4 Control of Quadrotors
10.5 Case Studies
10.5.1 Precise Positioning for Delivery Quadrotor
10.5.2 Adaptive Positioning of Quadrotor
10.6 Conclusion and Future Applications
References
Chapter 11: Sustainable Wind Turbine Systems Based on On-line Fault Estimation and Fault Tolerant Control
11.1 Introduction
11.2 Wind Turbine Projects: Current Situation and Challenges
11.3 Wind Turbine Model, Operation, and Control
11.4 Wind Turbine Nominal Control: FTC
11.5 Sliding Mode Controller (SMC) Design
11.5.1 The Effect of System Fault ψp(xp,βr)
11.5.2 The Effect of the Generator Speed Sensor ωgf = ωg + fg (Where ωgf Is the Faulty Measurement and fs Is the Additive Sens...
11.6 PPIO-Based Generator Speed Sensor Fault Estimation
11.7 Simulation Results
11.7.1 The Performance of ISMC as a Passive FTC Against Pitch Actuator System Fault
11.7.2 The Performance of Integrated ISMC and PPIO Against Simultaneous System and Generator Speed Sensor Faults
11.7.3 The Performance of Integrated ISMC and PPIO Against Simultaneous System and Pitch Angle Sensor Fault
11.8 Conclusions
References
Chapter 12: Deep Learning and Its Environmental Applications
12.1 Introduction
12.1.1 Artificial Intelligence
12.1.2 Machine Learning
12.1.3 Deep Learning
12.1.4 Differences Between Machine Learning and Deep Learning
12.2 Deep Learning Processes
12.3 Theories of Deep Learning Algorithms
12.3.1 Deep Neural Network
12.3.2 Multilayer Artificial Neural Networks
12.4 Convolutional Neural Networks
12.4.1 Convolution Layer
12.4.2 Pooling Layer
12.4.3 Fully Connected Layer
12.4.4 Network Hyperparameters
12.5 Recurrent Neural Networks
12.6 Long Short-Term Memory
12.7 A Comparison Between Deep Learning Algorithms
12.8 Advantages and Challenges of Deep Learning
12.8.1 Advantages of DL
12.8.2 Challenges of DL
12.9 Utilization of DL in Environmental Systems Applications
12.9.1 Application of DL in Earthquake Prediction
12.9.2 Using RNN Deep Learning for Earthquake Prediction
12.9.3 Using CNN Deep Learning for Earthquake Prediction
12.9.4 Applications of DL in Climate and Weather Forecasting
12.9.4.1 Rainfall Prediction Using DL
12.9.5 Applications of DL in Environmental Protection and Sustainability
12.10 Conclusion
References
Index