Predicting airborne chloride deposition in marine bridge structures using an artificial neural network model

•The ANN model successfully predicted the airborne chloride deposition content in a coastal bridge.•The meteorological and topographical parameters used in this study were closely related to the generation and transportation of airborne chloride.•Based on the selection of the sampling site, the R2-values with and without deicing salt effect were 0.85 and 0.97, respectively.•The sampling site was a more significant governing factor for chloride deposition than the bridge height.