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Water Security: Big Data-Driven Risk Identification, Assessment and Control of Emerging Contaminants
Hoofdkenmerken
Auteur: Bin Liang, Shu-Hong Gao, Hongcheng Wang
Titel: Water Security: Big Data-Driven Risk Identification, Assessment and Control of Emerging Contaminants
Uitgever: Elsevier S & T
ISBN: 9780443141713
ISBN boekversie: 9780443141706
Editie: 1
Prijs: € 196.62
Verschijningsdatum: 12-06-2024
Inhoudelijke kenmerken
Categorie: Environmental Science
Taal: English
Imprint: Elsevier (S\u0026T)
Technische kenmerken
Verschijningsvorm: E-book
 

Inhoudsopgave:

\u003cp\u003e\u003ci\u003eWater Security: Big Data-Driven Risk Identification, Assessment and Control of Emerging\u003c/i\u003e \u003ci\u003eContaminants\u003c/i\u003e 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.\u003c/p\u003e\u003cul\u003e\u003cli\u003eCovers the detection, high-throughput analyses, and environmental behavior of the typical emerging chemical and biological contaminants\u003c/li\u003e\u003cli\u003eFocuses on chemical and biological big data driven aquatic ecological risk assessment models and techniques\u003c/li\u003e\u003cli\u003eHighlights the intelligent management and control technologies and policies for emerging contaminants in water environments\u003c/li\u003e\u003c/ul\u003e
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