Abstract
![CDATA[Pollutant particles emission has been a major source of worry for many years due to their negative health impacts. For health risk assessment, it is critical to understand how to assess pollutant particles transportation and deposition (TD) in human lung airways. Many researchers have studied airflow and particle TD in lungs through realistic and non-realistic lung models. However, the impact of pollution particles TD in the CT-scan-based realistic lung has not been fully addressed. This study investigates pollutant particle (traffic, smoke and dust) TD in human lungs based on different physical activities using computational fluid dynamics (CFD). The size and the density of pollutant particles were assumed to be different. Three different flow rates corresponding to different physical activity patterns are considered: sleeping pattern (Qin=15 L/min), resting pattern (Qin=30 L/min), and intense breathing pattern (Qin=60 L/min), where Qin is the inhalation flow rate. The uniform particle size distributions were considered to simulate the traffic, smoke, and dust particles deposition in the realistic lung airways. According to the findings, small diameter of the particle can go into the deep airways. However, dust particles with the larger diameter (10 µm) and lowest density (400 kg/m3) can also enter the deep airways. The outcomes of this study will aid in determining the amount of physical activity that should be taken into account when considering potential health risks.]]
Original language | English |
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Title of host publication | The 3rd International Symposium on Computational Particle Technology, 17-21 November 2021, Suzhou, China and Melbourne, Australia |
Publisher | ARC Hub for Computational Particle Technology |
Pages | 136-136 |
Number of pages | 1 |
Publication status | Published - 2021 |
Event | International Symposium on Computational Particle Technology - Duration: 1 Jan 2021 → … |
Conference
Conference | International Symposium on Computational Particle Technology |
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Period | 1/01/21 → … |