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

Cuiyun Ou, Jian Hang, Jiajia Hua, Yuguo Li, Qihong Deng, Bo Zhao and Hong Ling ()
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Cuiyun Ou: School of Atmospheric Sciences, Sun Yat-sen University, and Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai 519082, China
Jian Hang: School of Atmospheric Sciences, Sun Yat-sen University, and Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai 519082, China
Jiajia Hua: China Meteorological Administration Xiong’an Atmospheric Boundary Layer Key Laboratory, Baoding 071800, China
Yuguo Li: Department of Mechanical Engineering, The University of Hong Kong, Hong Kong, China
Qihong Deng: College of Public Health, Zhengzhou University, Zhengzhou 450001, China
Bo Zhao: China Meteorological Administration Xiong’an Atmospheric Boundary Layer Key Laboratory, Baoding 071800, China
Hong Ling: School of Atmospheric Sciences, Sun Yat-sen University, and Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai 519082, China

IJERPH, 2023, vol. 20, issue 5, 1-15

Abstract: The health effects of particles are directly related to their deposition patterns (deposition site and amount) in human airways. However, estimating the particle trajectory in a large-scale human lung airway model is still a challenge. In this work, a truncated single-path, large-scale human airway model (G3–G10) with a stochastically coupled boundary method were employed to investigate the particle trajectory and the roles of their deposition mechanisms. The deposition patterns of particles with diameters ( dp ) of 1–10 μm are investigated under various inlet Reynolds numbers ( Re = 100–2000). Inertial impaction, gravitational sedimentation, and combined mechanism were considered. With the increasing airway generations, the deposition of smaller particles ( dp < 4 μm) increased due to gravitational sedimentation, while that of larger particles decreased due to inertial impaction. The obtained formulas of Stokes number and Re can predict the deposition efficiency due to the combined mechanism in the present model, and the prediction can be used to assess the dose-effect of atmospheric aerosols on the human body. Diseases in deeper generations are mainly attributed to the deposition of smaller particles under lower inhalation rates, while diseases at the proximal generations mainly result from the deposition of larger particles under higher inhalation rates.

Keywords: computational fluid dynamics (CFD); large-scale human airway; single-path modelling; particle deposition mechanism; deposition prediction (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2023
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