Receptor models are an effective tool for distinguishing between pollutant sources when emission profiles are not well known.  I will present the basic ideas and approaches to receptor modeling in this talk, with emphasis on the Positive Matrix Factorization (PMF) technique.  I will then describe its applications to analyze one year ambient data from a monitoring station in Dundee, UK in 2000.  Concentrations of NO, NO2, NOx, PM10, SO42-, NO3-, NH4+, Cl-, Na+, K+, Ca, Mg, Pb, Ni, Zn, Cu and meteorological elements were measured.  Five PM10 sources were successfully identified by the PMF receptor models.  They are marine aerosol, soil and construction dust, secondary aerosol of ammonium nitric, secondary aerosol of ammonium sulfate, and incinerator and fuel oil burning sources.  The source mass profiles derived by the PMF model well describe the source characteristics, including the measured and predicted total mass contribution of the five sources.  Advantages and shortcomings of receptor models are discussed.  Possible use of receptor models in indoor environments is explored.