Comparative analysis of Eulerian and Lagrangian models for the simulation of fine and ultrafine particle dynamics in the wake of a heavy truck

Abstract

Predicting the turbulent dispersion of particulate pollutants is essential for understanding and mitigating the environmental impact of road traffic emissions, particularly those from heavy vehicles. This study examines the behavior of low-inertia particles in the turbulent wake of a heavy truck, a region dominated by complex and inhomogeneous airflow that significantly influences pollutant dynamics. Numerical simulations were performed based on the RANS-SST $k\omega$ model for carrier-phase flow characterization, and three different approaches were applied to model the dispersed phase, namely the Lagrangian eddy interaction model (EIM), the Eulerian diffusion-inertia model (DIM) and a scalar advection–diffusion equation. To assess the accuracy of these numerical models, experimental measurements were carried out in an open-circuit wind tunnel. Particle image velocimetry (PIV) was used to characterize airflow, while a low-pressure electric impactor (ELPI) measured particle concentrations.

While numerical simulations generally aligned with experimental data, the Lagrangian EIM model overestimated particle concentrations at the wake vortex periphery, highlighting some limitations in capturing particle-turbulence interactions in highly anisotropic and inhomogeneous flows. Conversely, the Eulerian DIM and scalar advection–diffusion models proved closer to the experimental results, reasonably reproducing low-inertia particle dispersion, where inertial effects were found to be negligible. These results underline the importance of selecting an appropriate combination of turbulence and particle models to simulate the dispersion of particulate pollutants, providing valuable information for improving forecasts of traffic-related pollution and its environmental and health impacts.