The deposition and the re-suspension of particulate matter (PM) in urban areas are the key processes that contribute not only to stormwater pollution,but also to air pollution.However,investigation of the deposition and the re-suspension of PM is challenging because of the difficulties in distinguishing between the resuspended and the deposited PM.This study created two Bayesian Networks (BN) models to explore the deposition and the re-suspension of PM as well as the important influential factors.The outcomes of BN modelling revealed that deposition and re-suspension of PM10 occurred under both,high-traffic and low-traffic conditions,and the re-suspension of PM2.5 occurred under low-traffic conditions.The deposition of PM10 under low-volume traffic condition is 1.6 times higher than under high-volume traffic condition,which is attributed to the decrease in PM10 caused by relatively higher turbulence under high-volume traffic conditions.PM10 is more easily resuspended from road surfaces compared to PM2.5 as the particles which larger than the thickness of the laminar airflow over the road surface are more easily removed from road surfaces.The increase in wind speed contributes to the increase in PM build-up by transporting particulates from roadside areas to the road surfaces and the airborne PM2.5 and PM10 increases with the increase in relative humidity.The study outcomes provide a step improvement in the understanding of the transfer processes of PM2.5 and PM10 between atmosphere and urban road surfaces,which in turn will contribute to the effective design of mitigation measures for urban stormwater and air pollution.