Biochar-Based Catalysts for Removal of Environmental Contaminants: Advanced Treatment Technologies Using Computational Tools offers a comprehensive exploration of cutting-edge research and future directions in utilizing waste biomass for biochar catalyst development and environmental remediation. The book delves into the application of computational tools for wastewater and industrial effluent treatment, soil remediation, and air pollutant removal. From an in-depth analysis of AI and ML tools in enhancing process efficiency to case studies showcasing the practical implications of biochar-based catalysts, the book equips readers with the knowledge and strategies needed to address environmental challenges effectively.
Researchers and policymakers will find guidance on planning future research endeavors and making informed decisions to unlock the full potential of waste biomass resources for sustainable development and the circular bio-economy. Readers from a variety of backgrounds will find this to be a great resource that bridges the gap between current knowledge and future strategies, offering a roadmap towards achieving carbon neutrality and environmental sustainability.
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. List of contributors - p. ix 7. Preface - p. xiii 8. Chapter 1. Integrating computational approaches with biochar-based functional catalysts for forecasting air/soil pollution and remediation of air/soil pollutants from environment - p. 1 9. Chapter 2. Case studies on recent advances in applicability of computational tools for design, optimization, and automation of biochar-based catalysts for treatment of industrial effluents - p. 29 10. Chapter 3. Use of artificial intelligence tools in agro-waste management and development of biochar-based catalysts and their application for environmental cleanup - p. 57 11. Chapter 4. Green algorithms: artificial intelligence and machine learning synergy for biochar-based effluent remediation - p. 81 12. Chapter 5. Applications of artificial intelligence tools for the adsorption of pharmaceutical compounds from wastewater/industrial effluents - p. 101 13. Chapter 6. Artificial neural networks for prediction of biochar yield, development of functional catalysts, and their application in bioremediation - p. 129 14. Chapter 7. Current trends and future prospects of artificial intelligence and machine learning tools for the removal of pollutants in industrial effluents by using biochar-based catalysts - p. 139 15. Chapter 8. Removal of pharmaceutical compounds from wastewater by using artificial intelligence tools: current trends and future prospects - p. 171 16. Chapter 9. Application of artificial intelligence tools in development of biochar-based photocatalysts for removal of emerging environmental contaminants - p. 185 17. Chapter 10. Application of machine learning tools for prediction of fertilizers/pesticides/dye adsorption onto agricultural waste-derived biochar/modified biochar for clean environment - p. 199 18. Chapter 11. Exploring the application of artificial intelligence and machine learning tools in the removal of emerging pollutants from industrial effluents by biochar-based catalysts: current applications and future prospects - p. 227 19. Chapter 12. Integration of artificial intelligence tools with green adsorbent technologies for sustainable removal of pharmaceutical compounds from wastewater - p. 251 20. Chapter 13. Artificial intelligence-driven techno-economic and life cycle assessment of biochar-based catalysts for contaminant removal and waste recycling: a comparative study of developing and developed nations - p. 281 21. Index - p. 307
Biochar-Based Catalysts for Removal of Environmental Contaminants: Advanced Treatment Technologies Using Computational Tools offers a comprehensive exploration of cutting-edge research and future directions in utilizing waste biomass for biochar catalyst development and environmental remediation. The book delves into the application of computational tools for wastewater and industrial effluent treatment, soil remediation, and air pollutant removal. From an in-depth analysis of AI and ML tools in enhancing process efficiency to case studies showcasing the practical implications of biochar-based catalysts, the book equips readers with the knowledge and strategies needed to address environmental challenges effectively.
Researchers and policymakers will find guidance on planning future research endeavors and making informed decisions to unlock the full potential of waste biomass resources for sustainable development and the circular bio-economy. Readers from a variety of backgrounds will find this to be a great resource that bridges the gap between current knowledge and future strategies, offering a roadmap towards achieving carbon neutrality and environmental sustainability.
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. List of contributors - p. ix 7. Preface - p. xiii 8. Chapter 1. Integrating computational approaches with biochar-based functional catalysts for forecasting air/soil pollution and remediation of air/soil pollutants from environment - p. 1 9. Chapter 2. Case studies on recent advances in applicability of computational tools for design, optimization, and automation of biochar-based catalysts for treatment of industrial effluents - p. 29 10. Chapter 3. Use of artificial intelligence tools in agro-waste management and development of biochar-based catalysts and their application for environmental cleanup - p. 57 11. Chapter 4. Green algorithms: artificial intelligence and machine learning synergy for biochar-based effluent remediation - p. 81 12. Chapter 5. Applications of artificial intelligence tools for the adsorption of pharmaceutical compounds from wastewater/industrial effluents - p. 101 13. Chapter 6. Artificial neural networks for prediction of biochar yield, development of functional catalysts, and their application in bioremediation - p. 129 14. Chapter 7. Current trends and future prospects of artificial intelligence and machine learning tools for the removal of pollutants in industrial effluents by using biochar-based catalysts - p. 139 15. Chapter 8. Removal of pharmaceutical compounds from wastewater by using artificial intelligence tools: current trends and future prospects - p. 171 16. Chapter 9. Application of artificial intelligence tools in development of biochar-based photocatalysts for removal of emerging environmental contaminants - p. 185 17. Chapter 10. Application of machine learning tools for prediction of fertilizers/pesticides/dye adsorption onto agricultural waste-derived biochar/modified biochar for clean environment - p. 199 18. Chapter 11. Exploring the application of artificial intelligence and machine learning tools in the removal of emerging pollutants from industrial effluents by biochar-based catalysts: current applications and future prospects - p. 227 19. Chapter 12. Integration of artificial intelligence tools with green adsorbent technologies for sustainable removal of pharmaceutical compounds from wastewater - p. 251 20. Chapter 13. Artificial intelligence-driven techno-economic and life cycle assessment of biochar-based catalysts for contaminant removal and waste recycling: a comparative study of developing and developed nations - p. 281 21. Index - p. 307
