Positive Matrix Factorisation (PMF) analysis was applied to PM10 chemical composition and particle Number Size Distribution (NSD) data measured at an urban background site (North Kensington) in London, UK for the whole of 2011 and 2012. The PMF analyses revealed six and four factors respectively which described seven sources or aerosol types. These included Nucleation, Traffic, Diffuse Urban, Secondary, Fuel Oil, Marine and Non-Exhaust/Crustal sources. Diffuse Urban, Secondary and Traffic sources were identified by both the chemical composition and particle number size distribution analysis, but a Nucleation source was identified only from the particle Number Size Distribution dataset. Analysis of the PM10 chemical composition dataset revealed Fuel Oil, Marine, Non-Exhaust Traffic/Crustal sources which were not identified from the number size distribution data. The two methods appear to be complementary, as the analysis of the PM10 chemical composition data is able to distinguish components contributing largely to particle mass whereas the number particle size distribution dataset is more effective for identifying components making an appreciable contribution to particle number. Analysis was also conducted on the combined chemical composition and number size distribution dataset revealing five factors representing Diffuse Urban, Nucleation, Secondary, Aged Marine and Traffic sources. However, the combined analysis appears not to offer any additional power to discriminate sources above that of the aggregate of the two separate PMF analyses. Day-of-the-week and month-of-the-year associations of the factors proved consistent with their assignment to source categories, and bivariate polar plots which examined the wind directional and wind speed association of the different factors also proved highly consistent with their inferred sources.