Water Security: Big Data-Driven Risk Identification, Assessment and Control of Emerging Contaminants

Bin Liang, Shu-Hong Gao, Hongcheng Wang, Bin Liang, Shu-Hong Gao, Hongcheng Wang

• Publisher: Elsevier
• Year: 2024
• Print ISBN:
  9780443141706
• eBook ISBN:
  9780443141713
• Topic: Biological Sciences
• Subtopic: Environmental Science
• Index: Biological Sciences

Water Security: Big Data-Driven Risk Identification, Assessment and Control of Emerging Contaminants contains the latest information on big data-driven risk detection and analysis, risk assessment and environmental health effect, intelligent risk control technologies, and global control strategy of emerging contaminants. First, this book highlights advances and challenges throughout the detection of emerging chemical contaminants (e.g., antimicrobials, microplastics) by sensors or mass spectrometry, as well as emerging biological contaminant (e.g., ARGs, pathogens) by a combination of next- and third-generation sequencing technologies in aquatic environment. Second, it discusses in depth the ecological risk assessment and environmental health effects of emerging contaminants. Lastly, it presents the most up-to-date intelligent risk management technologies.This book shares instrumental global strategy and policy analysis on how to control emerging contaminants. Offering interdisciplinary and global perspectives from experts in environmental sciences and engineering, environmental microbiology and microbiome, environmental informatics and bioinformatics, intelligent systems, and knowledge engineering, this book provides an accessible and flexible resource for researchers and upper level students working in these fields. - Covers the detection, high-throughput analyses, and environmental behavior of the typical emerging chemical and biological contaminants - Focuses on chemical and biological big data driven aquatic ecological risk assessment models and techniques - Highlights the intelligent management and control technologies and policies for emerging contaminants in water environments

Table of contents

• Water Security: Big Data-Driven Risk Identification, Assessment and Control of Emerging Contaminants
• Cover
• Title Page
• Copyright Page
• Table of Contents
• List of contributors
• About the editors
• Foreword
• Acknowledgments
• Chapter 1 Pollution distribution characteristics and ecological risks of typical emerging chemical contaminants in aquatic environments
• Chapter 2 Micro(nano)plastic-mediated water ecological risks and control technologies
• Chapter 3 Environmental DNA and toxicogenomics in ecological health risk assessment
• Chapter 4 Dissemination mechanism of antibiotic resistance genes in water environment
• Chapter 5 Environmental behavior and risk of antibiotic resistance genes in water environments
• Chapter 6 Pathogens in engineered water systems
• Chapter 7 Environmental ecology and health risk assessment of pathogens in the environment
• Chapter 8 Ecological health assessment of natural water bodies by plankton
• Chapter 9 Analytical approaches, occurrence, migration, and transformation mechanisms of emerging contaminants in multiple media
• Chapter 10 Biosensors and biodegradation for emerging contaminants based on synthetic biology
• Chapter 11 Advanced detection technologies for emerging contaminants based on sensors
• Chapter 12 Optical real-time online sensing technologies and challenges for emerging contaminants
• Chapter 13 Suspect and nontarget screening technologies for emerging contaminants
• Chapter 14 Detection methods for emerging microplastics
• Chapter 15 High-throughput sequencing-based bioinformatics identification technologies for emerging biological risk factors
• Chapter 16 Mining technologies for functional gene markers of emerging contaminants
• Chapter 17 Statistical analyses and visualization of biological sequencing big data
• Chapter 18 Association of antimicrobial biodegradation with the evolution of antimicrobial resistance in ecosystems
• Chapter 19 Microbial transformation of per- and polyfluoroalkyl substances
• Chapter 20 Microbial dehalogenation mechanisms and prospects of bioremediation of persistent halogenated organic contaminants
• Chapter 21 Bacterial and genetic resources for typical emerging pharmaceuticals and personal care products degradation
• Chapter 22 Plastic contaminants in water and recent advances in bioremediation
• Chapter 23 Fate of emerging chemical contaminants in wastewater treatment system
• Chapter 24 Fate and risk management of antibiotic resistance genes in anaerobic digestion
• Chapter 25 Electron transfer regulation-based biotechnology for emerging contaminants treatment
• Chapter 26 Physicochemical control technologies for emerging contaminants in sewage treatment plants
• Chapter 27 Nature-based solutions for emerging contaminants removal
• Chapter 28 Leveraging weak electrical stimulation and artificial intelligence for sustainable microbial dehalogenation in groundwater remediation
• Chapter 29 Using isotope tracers to elucidate the fate of organic micropollutants in the environment
• Chapter 30 Modeling processes and sensitivity analysis of machine learning methods for environmental data
• Chapter 31 Advances in pollution source identification in the integrated drainage system
• Chapter 32 Data-driven management strategies for carbon emissions and emerging contaminants control in wastewater treatment plants
• Chapter 33 A Julia-based activated sludge modeling program for emerging contaminants management
• Chapter 34 Modeling removal of emerging contaminants during wastewater treatment processes
• Chapter 35 Current developments in machine learning models with boosting algorithms for the prediction of water quality
• Chapter 36 New situation of water resources management and water pollution control
• Chapter 37 The value of water resources and the emerging contaminants management
• Index
• Index - Continued
• Index - Continued
• Index - Continued