A total of 273 pine bark samples collected from various pine stands in Central and East Germany, South Norway, Poland, and Russia was analyzed with respect to 20 inorganic and organic substances (sulphate, nitrate, ammonia, calcium, 3 PAHs, 5 heavy metals, 9 other elements). Multivariate statistics were applied to characterize the multiple exposure of airborne pollutants in terms of major sources, deposition types and impact levels. The former was studied with factor analysis, whilst the latter two were addressed by applying cluster and discrimination analysis. Factor analysis of the concentration values suggest separation into three factors with the following characteristics: Factor 1 shows higher contributions from sulphate and calcium, factor 2 from fluoranthene, benzo(a)pyrene as well as from pyrene, and factor 3 from nitrate and ammonia, respectively. According to results from the cluster analysis, three major deposition types can be identified: "Industry and House heating", "Motor traffic", and "Agriculture". The first deposition type is characterized by high contents of sulphate and calcium. The other two deposition types contain specific composition profiles for nitrogen-containing components and PAHs. Impact levels are separately classified with the characteristic variables of main deposition types. Finally, discriminant analysis is used to allocate new bark samples to the classified deposition types and impact levels. The results demonstrate the usefulness of multivariate statistical techniques to characterize and evaluate multiple exposure patterns of airborne pollutants in forest ecosystems.