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
Shu-Hong Gao & Bin Liang
Water Security: Big Data-Driven Risk Identification, Assessment and Control of Emerging Contaminants [EPUB ebook]
Water Security: Big Data-Driven Risk Identification, Assessment and Control of Emerging Contaminants [EPUB ebook]
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Lingua Inglese ● Formato EPUB ● ISBN 9780443141713 ● Editore Shu-Hong Gao & Bin Liang ● Casa editrice Elsevier Science ● Pubblicato 2024 ● Scaricabile 3 volte ● Moneta EUR ● ID 9496072 ● Protezione dalla copia Adobe DRM
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