Nowadays urban pollution exposure from road transport has become a great concern in major cities throughout the world. A modelling framework has been developed to simulate Personal Exposure Frequency Distributions (PEFDs) as a function of urban background and roadside pollutant concentrations, under different traffic conditions. In this paper, we present a technique for classifying roads, according to their traffic conditions, using the traffic characteristics and fleet compositions. The pollutant concentrations data for 2001 from 10 Roadside Pollution Monitoring (RPM) units in the city of Leicester were analysed to understand the spatial and temporal variability of the pollutant concentrations patterns. It was found that variability of pollutants during the day can be associated with specific road traffic conditions. Statistical analysis of two urban and two rural Automated Urban and Rural Network (AURN) background sites for particulates suggests that PM2.5 and PM10 are closely related at urban sites but not at rural sites. The ratio of the two pollutants observed at Marylebone was found to be 0.748, which was applied to Leicester PM10 data to obtain PM2.5 profiles. These results are being used as an element in the PEFDs model to estimate the impact of urban traffic on exposure.