Urban air pollution poses a significant threat to human health, the environment and the quality of life of people throughout the world. In the United Kingdom 103 areas have been declared as local air quality management areas (LAQMA). While in India, 72 cities have been identified as cities having poor air quality/non-attainment area, i.e., the air quality in these cities are exceeding prescribed National Ambient Air Quality Standards (NAAQS). The transport sector is the principal source of local air pollution in urban areas, because of the increased vehicular population, vehicle kilometres travelled (VKT) and lack of infrastructure development. Many mathematical models have been widely used as tools in local air quality management in developed countries. Among them, ADMS  and AERMOD  models have been widely used for urban air quality management in Europe and the US, respectively. However, their applications are limited in developing countries like India due to the lack of readily available input data, time and the cost involved in collecting the required model input data. In this paper the performance evaluation of ADMS and AERMOD in predicting particulate matter (PM) concentrations at road sides in Chennai, India and Newcastle, UK is discussed. The statistical parameters such as Index of Agreement (IA), Fractional Bias (FB), Normalized Mean Square Error (NMSE), Geometric Mean Bias (MG) and Geometric Mean Variance (VG) have been used to evaluate the ADMS and AERMOD model performance. Results indicated that both the models are able to predict the pollutant concentrations with reasonable accuracy. The IA values for ADMS and AERMOD are found to be 0.39 and 0.37 and 0.48 and 0.44, respectively, for the Chennai and Newcastle study sites. © 2012 WIT Press.