335
Views
4
CrossRef citations to date
0
Altmetric
Research Article

Transport and deposition of ultrafine particles in the upper tracheobronchial tree: a comparative study between approximate and realistic respiratory tract models

ORCID Icon, , ORCID Icon &
Pages 1125-1135 | Received 23 Aug 2020, Accepted 22 Dec 2020, Published online: 07 Jan 2021
 

Abstract

This paper presents a computational fluid dynamics (CFD) study of air-particle flows in the upper tracheobronchial tree. Two respiratory tract models, including a parametrically controlled approximate airway model developed by Kitaoka (KG model) and a CT-based patient specific airway (realistic model) were used. Assuming laminar, quasi-steady, three-dimensional air flow and spherical non-interacting ultrafine particles in sequentially bifurcating rigid bronchial airways, airflow patterns and particle transport/deposition in these two airway models were evaluated and compared. Overall deposition efficiency data was compared with the widely adopted ICRP data published by The International Commission on Radiological Protection. Good deposition efficiency agreements were observed between the present respiratory tract models and the ICRP data, which validated the numerical prediction accuracy of the present computational fluid-particle dynamics (CFPD) model. For the two respiratory models, the comparison showed both difference and similarity between the approximate KG model and the realistic model. Specifically, the realistic model showed more complicated airflow patterns due to the increased surface irregularity. The deposition efficiency data revealed a deposition preference in the first-generation airways compared to the rest regions. For ultrafine particles smaller than 10 nm, Brownian diffusion remains the dominant particle deposition mechanism. However, for ultrafine particles with size ranging from 10 nm to 100 nm, the deposition efficiency decreased dramatically with the 100 nm particles approaching to zero deposition in the present bronchial tree scope. The generation-by-generation deposition data presented in this paper is indispensable to the formulation of new lung inhalation exposure models.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This study was funded by Australian Research Council (Project ID: DE180101138 and DE210101549).

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 61.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.