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.