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Elsevier

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

  • 1st Edition - June 12, 2024
  • Latest edition
  • Editors: Bin Liang, Shu-Hong Gao, Hongcheng Wang
  • Language: English

Water Security: Big Data-Driven Risk Identification, Assessment and Control of Emerging Contaminants contains the latest information on big data-driven risk detection and an… Read more

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Description

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.

Key features

  • 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

Readership

Researchers and students in the following fields: Environmental Science and Engineering, Intelligent Systems and Knowledge Engineering, Environmental Microbiology and Microbiome, Environmental Informatics and Bioinformatics, Environmental Health, Environmental Management, Environmental Epidemiology, Ecotoxicology, Environmental Chemistry, Environmental Ecology, Environmental Geochemistry, etc. Their main responsibilities are to guide undergraduate and postgraduate students to engage in related research, assist policy agencies to formulate relevant management standards, regulations, and laws, and to manage related businesses and administrative departments. Environmental management and protection, public health and other administrative and educational departments, scientific research institutions, and environment-related water companies, etc. Moreover, environmental policy decision makers, hydrologists, as well as managers and R&D personnel in environmental protection and water companies

Table of contents

1. Pollution distribution characteristics and ecological risks of typical emerging chemical contaminants in aquatic environments

2. Microplastics-mediated water ecological risks and control technologies

3. Environmental DNA (eDNA) and toxicogenomics in ecological health risk assessment

4. Dissemination mechanism of antibiotic resistance genes (ARGs) in water environment

5. Environmental behavior and risk of antibiotic resistance genes (ARGs) in water environment

6. Pathogens in engineered water system

7. Environmental ecology and health risk assessment of pathogens in the environment

8. Ecological health assessment of natural water bodies by plankton

9. Analytical approaches, occurrence, migration and transformation mechanisms of emerging contaminants in multiple media

10. Biosensors and Biodegradation for Emerging contaminants based on Synthetic Biology

11. Advanced detection technologies for emerging contaminants based on sensors

12. Optical Real-time Online Sensing Technologies and Challenges for Emerging Contaminants

13. Suspect and nontarget screening technologies for emerging contaminants

14. Detection methods for emerging microplastics

15. High-throughput sequencing based bioinformatics identification technologies for emerging biological contaminants

16. Mining technologies for functional gene markers of emerging contaminants

17. Statistical analysis and visualization of biological sequencing big data

18. Association of antimicrobial biodegradation with the evolution of antimicrobial resistance in ecosystems

19. Microbial Transformation of Per- and Polyfluoroalkyl Substances (PFAS)

20. Microbial dehalogenation mechanisms and prospects of bioremediation of persistent halogenated organic contaminants

21. Bacterial and Genetic Resources for Typical Emerging Pharmaceuticals and Personal Care Products (PPCPs) Degradation

22. Plastic contaminants in water and recent advances for bioremediation

23. Fate of emerging chemical contaminants in wastewater treatment system

24. Fate and risk management of antibiotic resistance genes (ARGs) in anaerobic digestion

25. Electron transfer regulation-based biotechnologies for emerging contaminants treatment

26. Physicochemical control technologies for emerging contaminants in sewage treatment plants

27. Nature-based control technologies for emerging contaminants

28. Leveraging weak electrical stimulation and artificial intelligence for sustainable microbial dehalogenation in groundwater remediation

29. Using isotope tracers to elucidate the fate of organic micropollutants in the environment

30. Modeling processes and sensitivity analysis of machine learning methods for environmental data

31. Advances in pollution source identification in the integrated drainage system

32. Data-driven management strategies for carbon emissions and emerging contaminants control in wastewater treatment plants

33. A Julia based activated sludge modeling program toward emerging contaminants management

34. Mathematical modelling for emerging contaminants during wastewater treatment

35. Current developments in machine learning models with boosting algorithms for the prediction of water quality

36. New situation of water resources management and water pollution control

37. The value of water resources and the emerging contaminants management

Product details

  • Edition: 1
  • Latest edition
  • Published: June 12, 2024
  • Language: English

About the editors

BL

Bin Liang

Dr. Bin Liang is a professor at Harbin Institute of Technology, Shenzhen, P.R. China. He received his PhD from Harbin Institute of Technology in 2014. Dr. Liang’s research focuses on ecological risk assessment and management of water contaminants. He has systematically investigated the biodegradation mechanisms of emerging contaminants (e.g., antimicrobial agents, refractory organic nitrogen/halide) in water reclamation and treatment systems. He is especially interested in developing green technologies for environmental management and novel methods for environmental monitoring. He has published over 100 Science Citation Index (SCI) papers (18 in high-impact journals ES&T, Water Res and Appl Environ Microbiol), 1 Springer book (as the second editor), 1 standard, and has been authorized 5 patents. His publications have been cited 4000 times, with an H-index of 42. He is a member of the Youth Innovation Promotion Association of the Chinese Academy of Sciences and has won the second prize of the National Technological Invention Award (2020), the first prize of the Environmental Protection Science and Technology Award (2017), the Industry-University-Research Cooperation Innovation Award (2021), and the Microbial Ecology Youth Science and Technology Innovation Award (2015).
Affiliations and expertise
Professor, Harbin Institute of Technology, School of Civil & Environmental Engineering, Shenzhen, P.R. China

SG

Shu-Hong Gao

Dr. Shuhong Gao is an assistant professor at Harbin Institute of Technology, Shenzhen, P.R. China. She received her PhD from The University of Queensland in 2017. Dr. Gao’s research focuses on emerging contaminants in urban water, as well as antibiotic resistance, and pathogens related to wastewater epidemiology. She has systematically investigated microplastic-mediated ecological risks and biosafety in aquatic environments. She is particularly interested in “omics” analysis of environmental microbes. She has initiated the construction of Global Water Pathogen Database to unravel the occurrence of pathogens in aquatic systems and to clarify the mechanisms between bio-pollutants transmission and health risks. She presided or participated in over 10 (inter)national/provincial projects. She is the Early-Career Editorial Board member of journal of Environmental Science and Ecotechnology. She has won the Travel Award of 2017 ASM Microbe and the Travel Award of 2019 Chinese Environmental Scholars Forum and was recognized as Overseas high-caliber personnel (Level C) in 2020. She has published over 50 SCI papers (12 in high-impact journals ES&T and Water Res, total citations over 1450), with an H-index of 21.
Affiliations and expertise
Assistant Professor, Harbin Institute of Technology, School of Civil & Environmental Engineering, Shenzhen, P.R. China

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