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.
1. Title of Book - p. i 2. Cover image - p. i 3. Title page - p. ii 4. Table of Contents - p. iii 5. Copyright - p. iv 6. Contributors - p. xiii 7. Preface - p. xvii 8. 1. Artificial intelligence in pollution emission control of municipal solid waste incineration process: Status and future prospects - p. 1 9. 2. Predicting the compressive strength of sustainable cement mortar composite incorporating biochar: A machine learning modeling approach - p. 39 10. 3. Mapping European innovation and policy landscapes using deep learning: Technologies for sustainable wastewater management - p. 63 11. 4. Artificial intelligence in removal of emerging contaminants: A sustainable approach for environmental cleanup and circular economy - p. 77 12. 5. Application of conventional methods and artificial intelligence tools for wastewater treatment: Recent advancements and future prospects - p. 109 13. 6. Role of conventional methods and artificial intelligence technologies for wastewater treatment: a comparative study - p. 151 14. 7. Challenges with artificial intelligence and machine learning methods for implementation in water treatment and monitoring - p. 181 15. 8. Application of artificial intelligence in the development of circular bioeconomy - p. 221 16. 9. Recent advances in the use of artificial intelligence for the optimization and automation of adsorption processes for wastewater treatment - p. 247 17. 10. Artificial intelligence: Historical background, types of tools, and applications for a sustainable future - p. 279 18. 11. Application of artificial intelligence–based modeling for the removal of emerging contaminants from aqueous system: Recent advancements and future prospects - p. 299 19. 12. Harnessing artificial intelligence: Technologies, tools, and their role in advancing environmental sustainability - p. 313 20. 13. Application of artificial intelligence prediction models for nature-based wastewater treatment - p. 323 21. Index - p. 353
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.
1. Title of Book - p. i 2. Cover image - p. i 3. Title page - p. ii 4. Table of Contents - p. iii 5. Copyright - p. iv 6. Contributors - p. xiii 7. Preface - p. xvii 8. 1. Artificial intelligence in pollution emission control of municipal solid waste incineration process: Status and future prospects - p. 1 9. 2. Predicting the compressive strength of sustainable cement mortar composite incorporating biochar: A machine learning modeling approach - p. 39 10. 3. Mapping European innovation and policy landscapes using deep learning: Technologies for sustainable wastewater management - p. 63 11. 4. Artificial intelligence in removal of emerging contaminants: A sustainable approach for environmental cleanup and circular economy - p. 77 12. 5. Application of conventional methods and artificial intelligence tools for wastewater treatment: Recent advancements and future prospects - p. 109 13. 6. Role of conventional methods and artificial intelligence technologies for wastewater treatment: a comparative study - p. 151 14. 7. Challenges with artificial intelligence and machine learning methods for implementation in water treatment and monitoring - p. 181 15. 8. Application of artificial intelligence in the development of circular bioeconomy - p. 221 16. 9. Recent advances in the use of artificial intelligence for the optimization and automation of adsorption processes for wastewater treatment - p. 247 17. 10. Artificial intelligence: Historical background, types of tools, and applications for a sustainable future - p. 279 18. 11. Application of artificial intelligence–based modeling for the removal of emerging contaminants from aqueous system: Recent advancements and future prospects - p. 299 19. 12. Harnessing artificial intelligence: Technologies, tools, and their role in advancing environmental sustainability - p. 313 20. 13. Application of artificial intelligence prediction models for nature-based wastewater treatment - p. 323 21. Index - p. 353
