This work presents an advanced source apportionment approach that estimates the uncertainties of the positive matrix factorization model. The selection of the environmentally meaningful solutions is challenging in such models and a systematic approach to identify and sort the factors is important. We applied this method to a novel data set covering one yearly cycle at three sites in Estonia. The main results showed that biomass burning dominates in winter, while biogenic sources prevail in summer.