Parameter simulation study of dust drift during wheat drilling using a validated CFD model

Seed coating with plant protection products (PPP) is widely used to protect crops from pests and diseases. However, dust generated during sowing can lead to environmental emissions of active ingredients. Dust drift is influenced by particle properties, environmental conditions, and drilling machine design, and current experimental approaches are limited in scope and reproducibility. To address this, a validated Computational Fluid Dynamics (CFD) model was used to simulate dust drift under controlled virtual conditions. Three-dimensional models of pneumatic and mechanical seeders operating on fields were created to solve the Reynolds-averaged Navier–Stokes equations using the SST turbulence model. The airflow field was simulated within a large atmospheric boundary layer, and dust emission, transport, and deposition were modeled with an Eulerian–Lagrangian one-way coupled approach considering drag, buoyancy, and turbulent dispersion. A factorial simulation study comprising 240 wheat-sowing scenarios was conducted, varying driller type, wind speed (1–10 m s⁻¹), soil roughness, tractor speed (6 and12 km h⁻¹), particle size distribution (fine, medium, coarse), and shape (spherical, realistic). Results showed that pneumatic seeders produced higher drift than mechanical ones due to airflow assistance. Finer particles and stronger winds increased airborne dust and off-field deposition, while particle shape had a minor but measurable influence. Dust remained airborne far beyond the field edge, with air concentrations often exceeding surface deposition. The resulting dataset provides a comprehensive basis for developing simplified, data-driven dust drift prediction tools and for proposing mitigation measures in seed-drilling operations.