In vitro measurement and dynamic modeling-based approaches for deposition risk assessment of inhaled aerosols in human respiratory system
Journal
Atmospheric Environment
Journal Volume
95
Pages
268-276
Date Issued
2014
Author(s)
Hsieh N.-H.
Abstract
Respiratory deposition dynamics of inhaled particle are developed rapidly in recent decades. Understandings of aerosol properties are useful for predicting respiratory deposition risk. This study conducted an aerosol exposure experiment to quantify the respiratory deposition dynamics of inhaled aerosols, and to infer the deposition risk probability. The experimental aerosols included reference oil droplets and road dust particles. This study developed an aerosol dynamic model to simulate time-dependent particle concentration in exposure chamber and respiratory system. The parameters of particle loss in exposure chamber and deposition in respiratory system can be estimated by experimental measurements. The deposition risks were estimated through particle size distributions and size-dependent deposition fractions. We showed that the experimental and predicted deposition fractions were consistent with the previous invivo, invitro and in silico studies. We found that the generated aerosols were polydisperse that followed a lognormal distribution with geometric mean diameters of 0.52 and 0.26μm for resuspended oil droplet and road dust, respectively. The deposition rate estimates range from 0.015 to 0.362 and 0.013 to 0.157s-1 in particle size ranging from 0.3 to 3.0 and 0.3 to 4.0μm for oil droplet and road dust, respectively. Result also revealed that inhaled oil droplet had higher respiratory deposition risk than road dust aerosol. Our study has major implications for the respiratory tract burden of inhaled fine particles from long-term exposure in ambient air based on our developed probabilistic risk model. ? 2014 Elsevier Ltd.
Subjects
Dynamic modeling; Inhalation exposure; Particulate matter; Respiratory deposition; Risk assessment
SDGs
Other Subjects
Aerosols; Drops; Dust; Dynamic models; Particle size; Respiratory system; Risk assessment; Risk perception; Roads and streets; Deposition dynamics; Deposition fractions; Geometric mean diameters; Human respiratory system; Inhalation exposure; Log-normal distribution; Particle concentrations; Particulate Matter; Deposition; aerosol; estimation method; health risk; numerical model; particle size; respiratory disease; size distribution; aerosol; article; atmospheric deposition; computer model; deposition dynamics; dust; geometry; in vitro study; in vivo study; inhalation; long term exposure; measurement; particle size; priority journal; probability; respiratory system; risk assessment
Type
journal article