This study investigates the application of an advanced receptor model to highly time resolved aerosol concentration data. Aerosol mass concentration data, ambient gas measurements, and meteorological data were collected from August 20 to September 25, 2003 in Toronto, Ontario, Canada. A suite of instruments, including an aerosol mass spectrometer (AMS), was incorporated into the study which produced a diverse air quality data set. A Multilinear Engine receptor modelling script was developed to combine aerosol mass concentration data, meteorological data and time-of-day information so as to resolve sources contributing to Toronto's aerosol pollution. The inclusion of particle size resolved organic mass concentrations into the receptor modelling allowed for improved interpretation of the modelling results. The combination of a highly time resolved and diverse air quality data set, and the application of advanced receptor modelling, allowed for a more complete description of contributing aerosol sources as compared to previous studies.