Increased attention has been given recently to the impact of the deposition of acidic species on the degradation of commercially important materials such as metals and paints. Although it has been appreciated for some time that air pollutants, especially SO2, can accelerate atmospheric corrosion and erosion processes, it has only been in the past few years that an aggressive effort has been made to develop damage functions that can be employed to predict the extent of corrosion or erosion for a given set of environmental conditions. To date all of the damage functions have been generated by conducting regression analyses on corrosion data obtained from field studies. These types of analyses have shed some light on which environmental factors play major roles in accelerating the degradation process above that expected due to natural weathering. In particular, it has been established that the ambient SO2 concentration and the time the exposed surfaces are wet play important roles in the corrosion rate of metals. However these damage functions are phenomenological models and their application to environmental conditions other than those from which they were derived may produce erroneous results. In order to evaluate the economic impact of various control strategies, reliable damage functions must be developed to predict the impact of a reduction in ambient SO2 concentration or the pH of the rain on the degradation process.