Agriculture-Bioenergy Nexus: Transforming Waste into Wealth offers a comprehensive exploration of agricultural waste-to-bioenergy, covering a range of topics from fundamental principles to advanced technologies and real-world applications. It provides case studies and practical insights alongside actionable guidance for practitioners, investors, and policymakers, ensuring the application of theoretical knowledge to practical scenarios. The book offers a holistic understanding of bioenergy conversion processes, challenges, and opportunities of agricultural waste. Practical insights are provided for effective project planning and implementation, including overcoming technological and economic challenges. This is supported by detailed technoeconomic analysis aiding decision-making for investors and project planners, and an overview of sustainable environmental practices to align with industry standards. Actionable insights on planning and executing bioenergy projects are also presented. The book bridges disciplines, offering a multidisciplinary approach that connects agriculture, bioenergy, and environmental science, fostering a holistic understanding of the agriculture-bioenergy nexus. Agriculture-Bioenergy Nexus: Transforming Waste into Wealth is an invaluable interdisciplinary reference for academics, researchers, practitioners, and policymakers working across the agriculture and bioenergy sectors.
Artificial Intelligence for the Water-Energy-Food Nexus considers the interrelationships between water, energy, and food, which are key to sustainable development, and the potential of artificial intelligence (AI) as a tool to facilitate research and development within and between these areas. The first chapter introduces the water-energy-food nexus, including the three dimensions of the nexus (water-energy nexus, water-food nexus, and energy-food nexus), assessment and analysis methods, challenges and opportunities, trends, and future perspectives. The second chapter discusses artificial intelligence techniques, such as machine learning, natural language processing, machine or computer vision, and automation and robotics. This is followed by in-depth chapters that study the application of AI techniques to the three different sectors that form the nexus, covering water treatment processes, wastewater management, water quality and pollution, water resource management, renewable energy systems, load monitoring, grid management and smart grid, optimization and process control, energy consumption, energy storage, smart energy forecasting, and sorting and classification, detection, safety, prediction, control, quality analysis, production process optimization, and packaging in the context of the food industry. The final chapter brings everything together by presenting the applications of AI to the water-energy nexus, water-food nexus, energy-food nexus, and water-energy-food nexus. This book is of interest to all those who are looking to understand and utilize AI techniques in the context of energy, water, food, sustainable development, or other interdisciplinary areas, including researchers, advanced students, faculty, engineers, R&D, industry professionals, and policy makers.
Advanced Energy Management: Digitalization and AI for the Internet of Energy presents the latest advances in the fields of distributed renewable systems, advanced controls, and energy management of nonlinear energy behaviours. The book addresses the problems of energy resilience under extreme climate and extreme events and presents new applications for energy-efficient, low-carbon and energy-reliable cities. The book explains how energy management is used in multi-energy systems for improved power dispatch, fast response, dynamic ageing, techno-economic performance. The introduction provides a comprehensive overview of artificial intelligence applications for renewable energy systems. The subsequent sections delve into various aspects, such as the interconnection between climate change and multi-energy systems, the role of big data and digitalization in sustainable energy supply, the integration of renewable energy sources, and the application of machine learning in power forecasting, demand predictions, and energy storage. Following this, the book explains demand-side management and grid-response controls in integrated energy management systems (IEMSs), and energy management systems (EMSs) in integrated energy systems and power grid with artificial intelligence. Dedicated chapters review peer-to-peer and blockchain-based energy sharing and trading, dynamic pricing and decision making in distributed energy markets, as well as city-scale energy resilience and robustness with distributed energy systems. Finally, the ethical, regulatory, and policy considerations of applying artificial intelligence in energy systems and energy management are discussed, and detailed Sustainability and Environmental Impact Analyses are presented. Advanced Energy Management: Digitalization and AI for the Internet of Energy is an invaluable reference for students, researchers, and industry professionals seeking advanced energy management strategies, and will be of interest to anyone involved in carbon neutrality solutions.
Artificial Intelligence in Chemical Engineering explores the integration of artificial intelligence (AI) into various facets of chemical engineering. The book introduces historical information, highlights current state and trends in AI applications, and discusses challenges and opportunities within the field. Foundational principles of AI and machine learning are thoroughly covered, giving readers a solid understanding of basic AI principles, machine learning algorithms, and the crucial processes of model training and validation. The book then delves into the critical phase of data acquisition and preprocessing for AI models, addressing strategies for data collection, ensuring data quality, and techniques for feature engineering and selection.Subsequent chapters cover a wide spectrum of AI applications in chemical engineering. From supervised and unsupervised learning for process modeling to the advanced realm of deep learning applications, this book explores neural networks, convolutional and recurrent architectures, and their real-world applications in process optimization and analysis.
The Handbook of Microalgae-Based Processes and Products: Fundamentals and Advances in Energy, Food, Feed, Fertilizer, and Bioactive Compounds, Second Edition provides a complete overview of all aspects involved in the production and utilization of microalgae resources at commercial scale. Divided into five parts (fundamentals, microalgae-based processes, microalgae-based products, and engineering approaches applied to microalgal processes and products, and trends and advancements in microalgae technology), the book explores the microbiology and metabolic aspects of microalgae, microalgal production systems, wastewater treatment based in microalgae, CO2 capture using microalgae, microalgae harvesting techniques, and extraction and purification of biomolecules from microalgae. It covers the largest number of microalgal products of commercial relevance, including biogas, biodiesel, bioethanol, biohydrogen, single-cell protein, single-cell oil, biofertilizers, pigments, polyunsaturated fatty acids, bioactive proteins, peptides and amino acids, bioactive polysaccharides, sterols, bioplastics, UV-screening compounds, and volatile organic compounds. Moreover, it presents and discusses the available engineering tools applied to microalgae biotechnology, such as process integration, process intensification, and techno-economic analysis applied to microalgal processes and products, microalgal biorefineries, life cycle assessment, and exergy analysis of microalgae-based processes and products. The coverage of a broad range of potential microalgae processes and products in a single volume makes the Handbook of Microalgae-Based Processes and Products: Fundamentals and Advances in Energy, Food, Feed, Fertilizer, and Bioactive Compounds, 2nd Edition an indispensable reference for engineering researchers in academia and industry in the fields of bioenergy, sustainable development, and high-value compounds from biomass, as well as graduate students exploring those areas. Engineering professionals in bio-based industries will also find valuable information here when planning or implementing the use of microalgal technologies.
Restoration and Sustainable Development of Mine-Affected Soils and Degraded Lands: Advances for Natural Resources Conservation and Land Sustainability explores the latest advancements across various aspects of sustainable post-mining land development. The chapters begin with an assessment of environmental legacies resulting from mining activities across different environmental areas covering the pedosphere, biosphere, hydrosphere, and atmosphere, and considers their interconnections and material fluxes. This is followed by prediction and analysis of the environmental benefits and challenges linked to mine closure and the transition to renewable energy at the local and regional levels. Further chapters investigate the social and economic opportunities and obstacles concerning mine closure and the phasing out of coal, viewed from regional, national, and global perspectives. There is also discussion of management approaches that consider environmental, socio-economic, and political challenges, aiming to draw insights from both successful experiences and lessons learned from research and experiences focusing on barriers and failures. The text concludes with an examination of the connection between soil and human health in mine-affected areas. This much needed collection offers mining engineers, soil scientists, and environmental resource managers an invaluable resource for their current and future work.
Cybersecurity Defensive Walls in Edge Computing dives into the creation of robust cybersecurity defenses for increasingly vulnerable edge devices. This book examines the unique security challenges of edge environments, including limited resources and potentially untrusted networks, providing fundamental concepts for real-time vulnerability detection and mitigation through novel system architectures, experimental frameworks, and AI/ML techniques. Researchers and industry professionals working in cybersecurity, edge computing, cloud computing, defensive technologies, and threat intelligence will find this to be a valuable resource that illuminates critical aspects of edge-based security to advance theoretical analysis, system design, and practical implementation of defensive walls. With a focus on fast-growing edge application scenarios, this book offers valuable insights into strengthening real-time security for the proliferation of interconnected edge devices.
Application of Phase Change Materials in Energy Storage and Conversion Systems explores the application of phase change materials in energy storage and conversion systems. Broken into thirteen chapters, the book begins with an overview of renewable energy systems and storage with one chapter dedicated specifically to thermal energy storage systems. The book then presents phase change materials, the basis for PCM modelling, how to design a thermal energy storage system, and the factors affecting PCM energy storage capacity. Various applications, including those as TES and in buildings, are covered before the book concludes with coverage of the CFD approach for PCM modelling and TES with PCM optimization techniques. Written for engineers, researchers, students, and designers of energy storage systems alike, Application of Phase Change Materials in Energy Storage and Conversion Systems will be a welcomed resource to all who wish to better understand the role of PCMs in energy storage.
Perspectives on Artificial Intelligence and Internet of Things for Sustainable Environment addresses the pressing environmental concerns due to rapid urbanization, deforestation, pollution, and more, by leveraging artificial intelligence and Internet of Things. This book provides valuable insights to readers on the integration of AI with IoT, equipping them with the knowledge to utilize these technologies for a sustainable future. This book also serves as a bridge between theoretical knowledge and practical application, offering tailored practices for integrating AI and IoT. Through a series of case studies and applications, readers will gain hands-on experience and will be empowered to make informed decisions on the selection and application of various AI and IoT frameworks for environmental sustainability.
Advances in Treatment Methods Towards Emerging Contaminants: Sources, Occurrences and Health Effects serves as a comprehensive guide to all aspects of emerging contaminant detection, monitoring, analysis, and remediation. This book provides a theoretical overview and practical guidance for researching all the fundamental aspects of emerging contaminants including transformations and toxicology of emerging pollutant and contaminants. In addition to outlining recent advances to existing detection techniques to monitor emerging contaminants, this book provides case studies for new remediation, transformation and monitoring techniques, including those that utilize green technology and nanotechnology. Advances in Treatment Methods Towards Emerging Contaminants will be a valuable guide for researchers, academics and industry experts working with environmental monitoring end emerging contaminants – including chemists and chemical engineers working on new analysis and remediation or transformation strategies to tackle the removal of environmental contaminants. This book will also be a useful guide to policy makers looking at pollution and contaminant control measures or students at graduate level and above working in waste treatment and remediation.