Enhancement of ICRP's Lung Deposition Model for Pathogenic Bioaerosols

Guha, Sudipto; Hariharan, Prasanna; Myers, Matthew R.

doi:10.1080/02786826.2014.975334

Cited by 53 publications

(42 citation statements)

References 58 publications

(54 reference statements)

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“…The MPPD model has been used in diverse research elds including pure inorganic aerosol, bioaerosol, indoor sources, cigarettes, and biomass burning. [34][35][36][37][38] To calculate the number dose of particle deposition in each airway generation, the deposition rate (DR) during 3D printing operation was calculated by the eqn (1):…”

Section: Aerosol Deposition Modelmentioning

confidence: 99%

Characteristics of nanoparticle formation and hazardous air pollutants emitted by 3D printer operations: from emission to inhalation

et al. 2019

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Section: Aerosol Deposition Modelmentioning

confidence: 99%

Characteristics of nanoparticle formation and hazardous air pollutants emitted by 3D printer operations: from emission to inhalation

et al. 2019

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Section: Applicationsmentioning

confidence: 99%

“…A critical benefit of the ICRP model is owed to its open sources, thanks to which users can modify it for adaptation to their specific requirements [38]. For example, Guha et al (2014) modified the ICRP model to investigate the effects of pathogenic bioaerosols such as botulinum toxin (BTX), influenza virus, and Bacillus anthracis on human health [38]. There are some differences between their model and the original one: 1) The modified ICRP model could automatically calculate the shape factor of nonspherical particles, 2) it could implement the normal size distributions of the purified monomers of bioaerosols, and 3) it could convert the lung deposition estimation from a function of age to a function of height due to the relations between these two factors.…”

Section: Applicationsmentioning

confidence: 99%

“…However, the deposition per unit surface area was higher for infants, due to their smaller lung and lung area. Therefore, infants are more susceptible to biological aerosols, especially B. anthracis, due to their weaker immunity [38,40].…”

Section: Applicationsmentioning

confidence: 99%

“…The deposition in each section of the lung (DEi) can be calculated via the following equation [38]: The filter efficiency was calculated as:…”

Section: Introductionmentioning

confidence: 99%

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Prediction of Aerosol Deposition in the Human Respiratory Tract via Computational Models: A Review with Recent Updates

et al. 2020

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The measurement of deposited aerosol particles in the respiratory tract via in vivo and in vitro approaches is difficult due to those approaches' many limitations. In order to overcome these obstacles, different computational models have been developed to predict the deposition of aerosol particles inside the lung. Recently, some remarkable models have been developed based on conventional semi-empirical models, one-dimensional whole-lung models, three-dimensional computational fluid dynamics models, and artificial neural networks for the prediction of aerosol-particle deposition with a high accuracy relative to experimental data. However, these models still have some disadvantages that should be overcome shortly. In this paper, we take a closer look at the current research trends as well as the future directions of this research area.Atmosphere 2020, 11, 137 2 of 27 PM Cd , and PM Pb ), the annual limit values are 6, 5, and 500 ng/m 3 , respectively (Directives 1999/30/EC and 2008/50/EC) [9]. Inhaled drug therapy can be a useful option against many lung diseases such as asthma or COPD. The efficiency of pharmaceutical aerosols depends on their deposition in the airways, especially the upper generations [10]. The estimation of aerosol transportation and deposition in the human lung can therefore indicate strategies for the prevention or alleviation of health effects from inhaled toxic particles or new drug-aerosol delivery approaches that can overcome the limitations of inhalers [11]. Atmospheric-aerosol deposition in the human respiratory tract (RT) can be directly measured by monitoring and comparing inhaled and exhaled particle concentrations. However, due to experimental limitations, the regional dose in the respiratory system is hard to measure experimentally but can be predicted by the application of different mathematical models. Suitable mathematical models are those that show a reasonable correlation between results obtained from modeling and empirical measurements [12]. Computational models generally consist of three elements: (1) a mathematical formulation that describes the relevant physical and chemical processes, (2) the setting of specific initial and boundary conditions, and (3) the solving of equations for the specified geometry. The accuracy of a computational model depends on the extent to which these elements are realistic. Additionally, regardless of the computational model that is applied, four types of input data are required: (1) lung morphometry, (2) breathing pattern, (3) particle properties, and (4) gas/vapor properties (Figure 1) [4]. The effects of these input data to the computational models were introduced in the review of Rostami (2009) and Hussain et al. (2011) [4,13]. In this review, we only present the advances of lung geometry models due to their strong relations to the accuracies of the computational models [4,13].

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Research Perspectives on Air Pollution and Human Health in Asia

Guinot

Annesi‐Maesano²

2017

Air Pollution in Eastern Asia: An Integrated Perspective

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Enhancement of ICRP's Lung Deposition Model for Pathogenic Bioaerosols

Cited by 53 publications

References 58 publications

Characteristics of nanoparticle formation and hazardous air pollutants emitted by 3D printer operations: from emission to inhalation

Characteristics of nanoparticle formation and hazardous air pollutants emitted by 3D printer operations: from emission to inhalation

Prediction of Aerosol Deposition in the Human Respiratory Tract via Computational Models: A Review with Recent Updates

Research Perspectives on Air Pollution and Human Health in Asia

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