Many of todays environmental problems, such as air pollution and climate change, are closely related to surprisingly small changes in the composition of our atmosphere. A large variety of very sensitive experimental methods are used today to track these changes with the goal to monitor how human activity impacts the atmosphere and to provide information on which to base possible solutions. Among the many methods to study and monitor atmospheric composition, optical remote sensing has become one of the most widely used techniques. In the ultraviolet and visible spectral regions, where the sun intensity has its maximum and many artificial light sources exist, the method of choice to measure trace gases is Differential Optical Absorption Spectroscopy (DOAS). Examples of DOAS applications include atmospheric chemistry research, emission measurements from industrial facilities, monitoring of volcano activity, global air pollutant observations from space, etc.

DOAS is a method that relies on the measurements of narrow band trace gas absorption features in light originating from the sun, artificial light sources, or solar light scattered in the atmosphere. A number of challenges emerge from this approach. Trace gas absorption features are often present at the same wavelength range and need to be separated accurately from each other. Similarly, the spectral structure of the respective light and the impact of unwanted absorbers must be separated from the trace gas absorptions of interest. As the trace gas absorptions are often very weak, a number of instrumental effects have to be considered when deriving concentrations and their uncertainties. These challenges have lead to the development of numerical retrieval methods, which are at the heart of the DOAS method.

In this talk I will give a general introduction into the DOAS method and present some of its most significant applications. I will discuss the mathematical methods to retrieve trace concentrations from optical absorption measurements and point out the current limitations of the retrieval approach and thus the DOAS method in general.