Increasing need for food and feed throughout the world has contributed to the direct growth in cereal grain production in the U.S. Due to the high volume of grains handled, there exists an increased hazard to workers from the dust generated. Most control measures developed to avoid dust accumulation within the grain handling and processing industry are based on the use of dust collection systems. But, there is limited knowledge of the physical processes of dust separation from the grain surface and its dispersion characteristics. The working hypothesis of this proposed research is that dust generation during grain handling depends on the surface characteristics such as adhesion and surface energy. Our preliminary studies indicate that the dust adhesion force depends on the grain velocity during conveying. We also found that a coupled discrete element method (DEM) – computational fluid dynamics (CFD) model could accurately predict the dust separation process. Through this proposed research, we aim to conduct fundamental analyses of the adhesion and surface energy characteristics of dust particles. In addition, the dust cloud formation pattern will be studied under controlled conditions and at a grain handling facility. A coupled DEM-CFD approach will be used to analyze the high dust generation zones such as grain receiving and flow of grains through chutes. Based on the fundamental understanding developed and through mathematical analysis, we propose to develop equipment for dust control and mitigation. The results from this study would benefit grain handling and processing industry to protect worker safety, reduce dust explosions, and save costs.