Transport and Uptake of MTBE and Ethanol Vapors in a Human Upper Airway Model

Zhang, Zhe; Kleinstreuer, Clement; Kim, Chong S.

doi:10.1080/08958370500434172

Cited by 26 publications

(14 citation statements)

References 39 publications

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“…35 Nanoparticles larger than 1 nm generally stick when they contact the airway surface (mucus layer), i.e., the perfectly absorbing wall condition (Y wall = 0) can be employed. Zhang et al 60 discussed the impact of wall absorption (i.e., Y wall " 0) on particle deposition, which holds usually for vapors and nanoparticles less than or equal 1 nm in diameter.…”

Section: Transport Equationsmentioning

confidence: 99%

Airflow and Nanoparticle Deposition in a 16-Generation Tracheobronchial Airway Model

2008

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In order to achieve both manageable simulation and local accuracy of airflow and nanoparticle deposition in a representative human tracheobronchial (TB) region, the complex airway network was decomposed into adjustable triple-bifurcation units, spreading axially and laterally. Given Q(in) = 15 and 30 L/min and a realistic inlet velocity profile, the experimentally validated computer simulation model provided some interesting 3-D airflow patterns, i.e., for each TB-unit they depend on the upstream condition, local geometry and local Reynolds number. Directly coupled to the local airflow fields are the convective-diffusive transport and deposition of nanoparticles, i.e., 1 nm < or = d(p) < or = 100 nm. The CFD modeling predictions were compared to experimental observations as well as analytical modeling results. The CFD-simulated TB deposition values agree astonishingly well with analytical modeling results. However, measurable differences can be observed for bifurcation-by-bifurcation deposition fractions obtained with these two different approaches due to the effects of more realistic inlet conditions and geometric features incorporated in the CFD model. Specifically, while the difference between the total TB deposition fraction (DF) is less than 16%, it may be up to 70% for bifurcation-by-bifurcation DFs. In addition, it was found that fully developed flow and uniform nanoparticle concentrations can be assumed beyond generation G12. For nanoparticles with d(p) > 10 nm, the geometric effects, including daughter-branch rotation, are minor. Furthermore, the deposition efficiencies at each individual bifurcation in the TB region can be well correlated as a function of an effective diffusion parameter.

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Section: Transport Equationsmentioning

confidence: 99%

Airflow and Nanoparticle Deposition in a 16-Generation Tracheobronchial Airway Model

2008

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“…Finally, the highly vascularized sub-epithelium region was assumed to form a blood layer. The resulting multilayer model is identical to the mucus-tissue-blood airway approximation considered by Cohen Hubal et al 9,10 and adds tissue and blood layers to the previous approximations considered by Keyhani et al, 22 Zhang and Kleinstreuer, 43 and Zhao et al 45 In this study, convection due to mucus motion was neglected and transport through the multilayer system was assumed to result from pure diffusion. This assumption was based on the relative rates of convective transport due to mucus motion compared with diffusive transport across the thin mucus layer.…”

Section: Model Of the Conducting Airway Wallsmentioning

confidence: 98%

“…Some studies assume high reactivity of the inhaled vapor and apply a zero concentration boundary condition at the wall surface. 36,38,42 Studies considering solubility and potential reactions in a mucus layer include Keyhani et al, 22 Zhang and Kleinstreuer, 43 and Zhao et al 45 Other studies have considered solubility and reactivity in a mucus-tissue representation of the URT. 9,10,14,24 However, as with previous studies, all computational models assume that steady state diffusion through the mucus or mucus and tissue layers is reached instantaneously.…”

Section: Introductionmentioning

confidence: 98%

“…A number of studies have considered the gas-phase transport and surface absorption of inhaled chemical species. 14,25,36,43,44 Other studies have more directly focused on the mass transport process through the walls of the respiratory tract. 3,4,7,8,[30][31][32] The mass transport of chemical species within the lining of the respiratory tract is controlled by solubility, diffusion, and wall structure.…”

Section: Introductionmentioning

confidence: 99%

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Transient Absorption of Inhaled Vapors into a Multilayer Mucus–Tissue–Blood System

Tian

Longest

2009

Ann Biomed Eng

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Previous studies have approximated the absorption of vapors into the walls of the respiratory tract as a steady state process. However, non-dimensional analysis indicates that the absorption of vapors in the conducting airways is time-dependent over the timescale of a breathing cycle. The objective of this study was to evaluate the mass transport of sample chemical species through a simple multilayer system composed of mucus, tissue, and blood components on a transient basis. Individual multilayer models were considered that represent the wall dimensions of the nasal extrathoracic (ET(2)), bronchial (BB), and bronchiolar (bb) airways. Sample vapors considered were acetaldehyde and benzene, which are highly soluble and moderately soluble in mucus, respectively. To determine absorption, mass transport was calculated based on an existing analytical steady state solution, a new analytical transient solution, and a numerical transient solution. Results indicated that concentrations within the mucus and tissue layers were highly time dependent in the ET(2) and BB regions and moderately time dependent in the bb airways over the timescale of an inhalation cycle, which is approximately 1-2 s. Fluxes of vapors into the tissue and blood varied with time for approximately 6-8 s in the BB region and 0.6-0.8 s in the bb model. The associated transient blood uptake of acetaldehyde and benzene in the upper ET(2) and BB regions varied from steady state values by a factor of approximately 30 after 1 s. Under similar conditions, transient uptake in the bb model varied from steady state conditions by a factor of approximately 1.3. Surprisingly, inclusion of chemical reactions in the mucus and tissue modified the transient uptake predictions only for very large values of reaction rate coefficients (K > 100 min(-1)). In summary, transient effects significantly impact the absorption of vapors into the walls of the upper respiratory tract (ET(2) and BB regions) and may largely diminish the effects of chemical reactions over the timescale of an inhalation cycle. Furthermore, the transient analytical solution that was developed provides the basis for an improved boundary condition in future CFD simulations of air-phase transport and wall absorption.

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“…6,20,31,36,38,45 This distributed parameter approach simulates the airflow dynamics and transport and uptake of vapors in 3D models of the respiratory system. The advantage of this approach is that localized predictions of gas dosimetry can be obtained that are based on accurate geometries representative of the respiratory system.…”

Section: Introductionmentioning

confidence: 99%

Derivation of Mass Transfer Coefficients for Transient Uptake and Tissue Disposition of Soluble and Reactive Vapors in Lung Airways

et al. 2011

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Evaluation of vapor uptake by lung airways and subsequent dose to lung tissues provides the bridge connecting exposure episode to biological response. Respiratory vapor absorption depends on chemical properties of the inhaled material, including solubility, diffusivity, and metabolism/reactivity in lung tissues. Inter-dependent losses in the air and tissue phases require simultaneous calculation of vapor concentration in both phases. Previous models of lung vapor uptake assumed steady state, one-way transport into tissues with first-order clearance. A new approach to calculating lung dosimetry is proposed in which an overall mass transfer coefficient for vapor transport across the air-tissue interface is derived using air-phase mass transfer coefficients and analytical expressions for tissue-phase mass transfer coefficients describing unsteady transport by diffusion, first-order, and saturable pathways. Feasibility of the use of mass transfer coefficients was shown by calculating transient concentration levels of inhaled formaldehyde in the human tracheal airway and surrounding tissue. Formaldehyde tracheal air concentration and wall-flux declined throughout the breathing cycle. After the inhalation period, peak tissue concentration moved from the air-tissue interface into the tissue due to desorption into the air and continued diffusional transport across the tissue layer. While model predictions were performed for formaldehyde, which serves as a model of physiologically relevant, highly reactive vapors, the model is equally applicable to other soluble and reactive compounds.

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Transport and Uptake of MTBE and Ethanol Vapors in a Human Upper Airway Model

Cited by 26 publications

References 39 publications

Airflow and Nanoparticle Deposition in a 16-Generation Tracheobronchial Airway Model

Airflow and Nanoparticle Deposition in a 16-Generation Tracheobronchial Airway Model

Transient Absorption of Inhaled Vapors into a Multilayer Mucus–Tissue–Blood System

Derivation of Mass Transfer Coefficients for Transient Uptake and Tissue Disposition of Soluble and Reactive Vapors in Lung Airways

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