The human health effects of fine particulate matter (PM2.5) have provided impetus for the establishment of new air quality standards or guidelines in many countries. This has led to the need for information on the main sources responsible for PM2.5. In urban locations being impacted by regional-scale transport, source-receptor relationships for PM2.5 are complex and require the application of multiple receptor-based analysis methods to gain a better understanding. This approach is being followed to study the sources of PM2.5 impacting southern Ontario, Canada, and its major city of Toronto. Existing monitoring data in the region around Toronto and within Toronto itself are utilized to estimate that 30-45% of the PM2.5 is from local sources, which implies that 55-70% is transported into the area. In addition, there are locations in the city that can be shown to experience a greater impact from local sources such as motor vehicle traffic. Detailed PM2.5 chemical characterization data were collected in Toronto in order to apply two different multivariate receptor models to determine the main sources of the PM2.5. Both approaches produced similar results, indicating that motor-vehicle-related emissions, most likely of local origin, are directly responsible for about 20% of the PM2.5. Gasoline engine vehicles were found to be a greater overall contributor (13%) compared to diesel vehicles (8%). Secondary PM2.5 from coal-fired power plants continues to be a significant contributor (20-25%) and also played a role in enhancing production of secondary organic carbon mass (15%) on fine particles. Secondary fine particle nitrate was the single most important source (35%), with a large fraction of this likely related to motor vehicle emissions. Independent use of different receptor models helps provide more confidence in the source apportionment, as does comparison of results among complementary receptor-based data analysis approaches.