Our world is moving towards virtual and augmented reality. Widespread use of wearable virtual and augmented reality technology is imminent. The research activities in this area are greater than ever. On the other hand, increasing urbanization worldwide is increasing the amount of air pollution city dwellers are exposed to, and related health issues, such as asthma, are on the rise. In this thesis I am presenting a technical solution using augmented reality to visualize the local air pollution asthma patients are exposed to, in hopes that it will improve their quality of life. Presenting data in 3D works as a bridge between quantitative content and human intuition, and, thus, is a critical segment of the logical path from data to knowledge and understanding. Therefore, many data analysis applications convert tabular data into visual components, such as graphs, pie charts or maps, and it has become much easier today to display data in 3D. Effective data visualization is a crucial part of research in the era of "big data". Many complex data sets can be simplified using effective tools for data visualization. Complex data sets, no matter how descriptive, are of no use if we cannot recognize patterns in them. This thesis aims at developing a method for future use of augmented reality by providing an application for display of environmental pollution data. Its research focus is to simplify the way to represent data in augmented reality enough so that it can be perceived intuitively. To demonstrate my concept, I implemented a simulation program, which combines a 3D model of an existing part of a city with immersive and interactive features. It provides a first person view, allows movement similar to walking, has a radar system for movement tracking, and visual components for the representation of air pollution. The software prototype developed in this thesis covers three parts of National City in San Diego.