Applications of Artificial Intelligence in Removal of Emerging Contaminants

Sustainable Approach for Environmental Clean-up and Circular Economy

Mika Sillanpää, Riti Thapar Kapoor

• Publisher: Elsevier
• Year: 2025
• Topic: Biological Sciences
• eBook ISBN:
  9780443267802
• Subtopic: Environmental Science
• Index: Biological Sciences

Applications of Artificial Intelligence in Removal of Emerging Contaminants: Sustainable Approach for Environmental Clean-up and Circular Economy focuses on the exploitation of various Artificial Intelligence (AI) tools to treat emerging contaminants and the restoration of contaminated sites. The book addresses critical environmental issues and challenges faced by society to meet such challenges. It highlights artificial intelligence and machine learning tools in the removal of environmental contaminants, such as industrial effluents, air, and to overcome limitations of conventional methods, predict water quality parameters and decrease the chances of error.Advanced tools, updated information, and future directions for researchers and scientists working in the bioremediation of emerging contaminants, bioenergy and reutilization of waste biomass in the production of value-added products for environmental safety are also thoroughly discussed. - Provides knowledge on various emerging pollutants which are hazardous to the environment, human health, and the applications of different artificial intelligence (AI) tools for the bioremediation of contaminant removal - Explores different aspects of biological methods using AI tools, including solutions for recycling and reuse - Highlights ways AI can assist scientists to make smart and effective decisions on the identification of suitable sorbents to enhance the performance of the sorption process and protect our environment

Table of contents

• Title of Book
• 1. Artificial intelligence in pollution emission control of municipal solid waste incineration process: Status and future prospects
• 2. Predicting the compressive strength of sustainable cement mortar composite incorporating biochar: A machine learning modeling approach
• 3. Mapping European innovation and policy landscapes using deep learning: Technologies for sustainable wastewater management
• 4. Artificial intelligence in removal of emerging contaminants: A sustainable approach for environmental cleanup and circular economy
• 5. Application of conventional methods and artificial intelligence tools for wastewater treatment: Recent advancements and future prospects
• 6. Role of conventional methods and artificial intelligence technologies for wastewater treatment: a comparative study
• 7. Challenges with artificial intelligence and machine learning methods for implementation in water treatment and monitoring
• 8. Application of artificial intelligence in the development of circular bioeconomy
• 9. Recent advances in the use of artificial intelligence for the optimization and automation of adsorption processes for wastewater treatment
• 10. Artificial intelligence: Historical background, types of tools, and applications for a sustainable future
• 11. Application of artificial intelligence–based modeling for the removal of emerging contaminants from aqueous system: Recent advancements and future prospects
• 12. Harnessing artificial intelligence: Technologies, tools, and their role in advancing environmental sustainability
• 13. Application of artificial intelligence prediction models for nature-based wastewater treatment
• Index