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Numerical study of nano and micropollutant particle transport and deposition in realistic human lung airways

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43 Citations (Scopus)

Abstract

For respiratory health risk assessment, it is essential to evaluate the transportation and deposition (TD) of pollutant particles in human lung airways, which are responsible for lung diseases. Studies to date improved the knowledge of the particle TD in airways. However, the understanding of the TD of different pollutant particles in realistic airways has not been fully understood. This study investigates TD of three types of pollutant particles: traffic, smoke and dust, with various sizes ranging from nano- to micro-scales in the mouth–throat and tracheobronchial lung airways of a human lung using computational fluid dynamics (CFD). Three different physical activities are considered: sleeping, resting, and intense breathing, corresponding to inhalation flow rates of Qin = 15, 30 and 60 L/min, respectively. Nearly 99.8% of 10-μm traffic particles are deposited in the upper lung airways considered here. However, the TD efficiency of 10-μm dust particles is reduced to 64.28% due to the reduction in particle density. Nanoparticles have a much smaller deposition efficiency than microparticles because impaction effect of microparticles is stronger. Only less than 10% of 5-nm traffic particles are deposited in the airways for all three flow rates, allowing over 90% of particles to reach the deep lung. An important finding is that the effects of density on the particle TD of nanoparticles are much weaker than that of microparticles. At 15 L/min flow rate, the difference between the deposition efficiencies of the heaviest traffic particles and the lightest dust particles is only 3.5%. The effects of particle density on the deposition efficiencies of nano- and micro-particles are different from each other because impaction and diffusion dominate the TD of nano- and micro-particles, respectively. Density only affects impaction significantly but has little effect on diffusion.

Original languageEnglish
Article number117364
Number of pages16
JournalPowder Technology
Volume402
DOIs
Publication statusPublished - Apr 2022

Bibliographical note

Publisher Copyright:
© 2022 Elsevier B.V.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

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