Particle Deposition in Large-Scale Human Tracheobronchial Airways Predicted by Single-Path Modelling

Area of Science:

• Aerosol science
• Respiratory physiology
• Computational fluid dynamics

Background:

• Particle deposition patterns in human airways influence health effects.
• Accurate estimation of particle trajectory in large-scale airway models remains challenging.

Purpose of the Study:

• Investigate particle trajectory and deposition mechanisms in a large-scale human airway model (generations G3-G10).
• Analyze deposition patterns for particles (1-10 μm) under varying Reynolds numbers (100-2000).
• Consider inertial impaction, gravitational sedimentation, and combined deposition mechanisms.

Main Methods:

• Utilized a truncated single-path, large-scale human airway model.
• Employed a stochastically coupled boundary method for simulations.
• Examined particle deposition efficiency based on particle diameter and Reynolds number.

Main Results:

• Deposition of smaller particles (<4 μm) increased with airway generations due to sedimentation.
• Deposition of larger particles decreased with airway generations due to inertial impaction.
• Developed formulas for Stokes number and Reynolds number to predict deposition efficiency.

Conclusions:

• Formulas can predict deposition efficiency, aiding in assessing atmospheric aerosol dose-effect.
• Smaller particle deposition in deeper generations is linked to lower inhalation rates and diseases.
• Larger particle deposition in proximal generations is linked to higher inhalation rates and diseases.