This book examines the central role of computational methods in understanding, predicting, and mitigating air pollution, a critical challenge for both public health and environmental sustainability. The book offers foundations of air pollution modeling, emphasizing computational fluid dynamics for simulating pollutant dispersion and transport in relation to urban landscapes, meteorological conditions, and airflow. These approaches are complemented by statistical methods and models that broaden the scope of air quality simulations.While highlighting major advances, the book also addresses persistent challenges: the demand for greater model accuracy, the need to manage uncertainty, the complexity of urban systems, and the computational intensity of many techniques. Developments such as parallel computing and reduced-order models are presented as promising directions for overcoming these obstacles.
