Aerosol Resuspension under Realistic Flows: integrating Near-Surface Physics into a Lagrangian CFD Model

Aerosol resuspension is a critical yet underexplored source of airborne particles, contributing to air quality challenges and exposure risks in environments ranging from healthcare and agriculture to transportation, industry, and nuclear safety. Despite its importance, resuspension remains underrepresented in aerosol transport and dispersion modelling due to the complexity of its underlying physics. Existing mechanistic, probabilistic, and semi-empirical models often rely on simplifying assumptions, which can lead to significant discrepancies between predictions and observations, limiting their reliability for real-world applications.
This research aims to further understand the dynamics of aerosol resuspension by developing a high-resolution CFD-based model that captures the fundamental physics more comprehensively than current approaches. Specifically, we investigate how aerodynamic forces, variability in particle-surface adhesion and morphology affect rolling or sliding thresholds and influence resuspension rates under realistic atmospheric conditions. The model uses a three-dimensional Lagrangian approach with six-degree-of-freedom particle motion within turbulent flow (Stokes regime, Re ≤ 1), enabling detailed analysis of near-surface interactions. It incorporates boundary layer theory, turbulent eddy behaviour, contact mechanics, and adhesive/repulsive force distributions to capture the critical mechanisms that govern detachment events. The model is designed to be flexible, accommodating diverse particle sizes, shapes, and surface topologies to replicate complex environmental and occupational scenarios. Current progress includes operational boundary layer and contact mechanics modules capable of simulating variable particle morphologies on flat surfaces. Key challenges encountered involve accurately resolving particle-surface contact at appropriate mesh and temporal resolutions, as well as implementing realistic adhesive forces while balancing computational cost in high-fidelity simulations.
Once completed, the model will be validated against experimental trajectory and detachment rates data and benchmarked against established Eulerian resuspension models. Ultimately, improving the capabilities for predicting aerosol resuspension addresses critical health and safety concerns as it helps better anticipate hazards associated with particle exposure and transport and supports better risk mitigation strategies for harmful aerosols in the environment.