As global water resources face growing threats from pollution and overuse, sustainable treatment solutions are urgently needed. Among these, adsorption stands out as an effective and versatile method for removing a broad spectrum of contaminants from water and wastewater. However, optimizing adsorption for large-scale applications is a complex challenge that demands both a solid understanding of adsorption science and the use of advanced computational tools. Computational Techniques for Modelling and Simulating Adsorption Processes for (Waste)Water Treatment addresses this challenge by providing a comprehensive guide integrating core adsorption principles with cutting-edge computational approaches for enhancing adsorption efficiency and system design. Structured to lead readers from fundamental concepts to advanced applications, the book includes:¿ an overview of water pollution and treatment ¿ a detailed exploration of adsorption principles and models¿ an introduction to general computational strategies for modelling and optimization, leading on to density functional theory, molecular dynamics, Monte Carlo simulations and QSAR techniques¿ AI and machine learning in adsorption modelling¿ computational fluid dynamics and system-level optimization. Together, these topics provide researchers, engineers, and practitioners with the tools needed to model, simulate, and optimize adsorption processes for more efficient and sustainable water treatment.