Computational modeling method to estimate secondhand exposure potential from exhalations during e-vapor product use under various real-world scenarios.

Potential secondhand exposure of exhaled constituents from e-vapor product (EVP) use is a public health concern. We present a computational modeling method to predict air levels of exhaled constituents from EVP use. We measured select constituent levels in exhaled breath from adult e-vapor product users, then used a validated computational model to predict constituent levels under three scenarios (car, office, and restaurant) to estimate likely secondhand exposure to non-users. The model was based on physical/thermodynamic interactions between air, vapor, and particulate phase of the aerosol. Input variables included space setting, ventilation rate, total aerosol amount exhaled, and aerosol composition. Exhaled breath samples were analyzed after the use of four different e-liquids in a cartridge-based EVP. Nicotine, propylene glycol, glycerin, menthol, formaldehyde, acetaldehyde, and acrolein levels were measured and reported based on a linear mixed model for analysis of covariance. The ranges of nicotine, propylene glycol, glycerin, and formaldehyde in exhaled breath were 89.44-195.70 µg, 1199.7-3354.5 µg, 5366.8-6484.7 µg, and 0.25-0.34 µg, respectively. Acetaldehyde and acrolein were below detectable limits; thus, no estimated exposure to non-EVP users is reported. The model predicted that nicotine and formaldehyde exposure to non-users was substantially lower during EVPs use compared to cigarettes. The model also predicted that exposure to propylene glycol, glycerin, nicotine and formaldehyde among non-users was below permissible exposure limits.

A comprehensive physiologically based pharmacokinetic (PBPK) model for nicotine in humans from using nicotine-containing products with different routes of exposure.

Physiologically based pharmacokinetic (PBPK) modeling can be a useful tool for characterizing nicotine pharmacokinetics (PK) from use of tobacco products. We expand a previously published PBPK model to simulate a nicotine PK profile, following single or multiple use of various tobacco products [cigarettes, smokeless tobacco, and electronic nicotine delivery systems, or a nicotine inhaler (NICOTROL)] The uptake route in the model was designed to allow for three uptake compartments: buccal cavity (BC), upper respiratory tract (URT) (conducting and transitional airways) and lower respiratory tract (alveolar region). Within each region, the model includes product-specific descriptions of the flux of nicotine into plasma, as well as the flux of nicotine from the BC and URT to the gastrointestinal tract. These descriptions are based on regional deposition and diffusion models of nicotine into plasma, which depends on the product type. Regional deposition flux combined with regional differences in physiological parameters (e.g., blood perfusion ratio and tissue thickness) play a key role in the product-specific PK profile of nicotine. The current model describes the slower flux of nicotine into plasma across the BC and URT, as well as the rapid flux known to occur in the alveolar region. Overall, the addition of the BC and respiratory tract compartments to the nicotine model provided simulation results that are comparable to the nicotine time-course plasma concentrations reported from clinical studies for the four product categories simulated.

Prediction of potential passive exposure from commercial electronic nicotine delivery systems using exhaled breath analysis and computational fluid dynamic techniques.

Use of computational fluid dynamic (CFD) modeling to predict temporal and spatial constituent exposure for non-electronic nicotine delivery systems (ENDS) users (passive exposure) provides a more efficient methodology compared to conducting actual exposure studies. We conducted a clinical study measuring exhaled breath concentrations of glycerin, propylene glycol, nicotine, benzoic acid, formaldehyde, acetaldehyde, acrolein, menthol and carbon monoxide from use of eight different commercial ENDS devices and a non-menthol and menthol cigarette. Because baseline adjusted levels of other constituents were not consistently above the limit of detection, the mean minimum and maximum per puff exhaled breath concentrations (N= 20/product) of glycerin (158.7-260.9µg), propylene glycol (0.941-3.58µg), nicotine (0.10-1.06µg), and menthol (0.432-0.605µg) from use of the ENDS products were used as input parameters to predict temporal and spatial concentrations in an environmental chamber, office, restaurant, and car using different ENDS use scenarios. Among these indoor locations and ENDS use scenarios, the car with closed windows resulted in the greatest concentrations while opening the car windows produced the lowest concentrations. The CFD predicted average maximum glycerin and propylene glycol concentration ranged from 0.25 to 1068µg m-3and 1.5 pg m-3to 13.56µg m-3,respectively. For nicotine and menthol the CFD predicted maximum concentration ranged from 0.16 pg m-3to 4.02µg m-3and 0.068 pg m-3to 2.43µg m-3, respectively. There was better agreement for CFD-predicted nicotine concentrations than glycerin and propylene glycol with published reports highlighting important experimental and computational variables. Maximum measured nicotine levels from environmental tobacco smoke in offices, restaurants, and cars exceeded our maximum average CFD predictions by 7-97 times. For all the measured exhaled breath constituents and CFD predicted constituents, except for propylene glycol and glycerin, concentrations were less from use of ENDS products compared to combustible cigarettes. NCT number: NCT04143256.

Comparison of experimentally measured and computational fluid dynamic predicted deposition and deposition uniformity of monodisperse solid particles in the Vitrocell® AMES 48 air-liquid-interface in-vitro exposure system.

Accurately determining the delivered dose is critical to understanding biological response due to cell exposure to chemical constituents in aerosols. Deposition efficiency and uniformity of deposition was measured experimentally using monodisperse solid fluorescent particles with mass median aerodynamic diameters (MMAD) of 0.51, 1.1, 2.2 and 3.3 µm in the Vitrocell® AMES 48 air-liquid-interface (ALI) in vitro exposure system. Experimental results were compared with computational fluid dynamic, (CFD; using both Lagrangian and Eulerian approaches) predicted deposition efficiency and uniformity for a single row (N = 6) of petri dishes in the Vitrocell® AMES 48 system. The average experimentally measured deposition efficiency ranged from 0.007% to 0.43% for 0.51-3.3 µm MMAD particles, respectively. There was good agreement between average experimentally measured and the CFD predicted particle deposition efficiency, regardless of approach. Experimentally measured and CFD predicted average uniformity of deposition was greater than 45% of the mean for all particle diameters. During this work a new design was introduced by the manufacturer and evaluated using Lagragian CFD. Lagragian CFD predictions showed better uniformity of deposition, but reduced deposition efficiency with the new design. Deposition efficiency and variability in particle deposition across petri dishes for solid particles should be considered when designing exposure regimens using the Vitrocell® AMES 48 ALI in vitro exposure system.

A distributed computational model for estimating room air level of constituents due to aerosol emission from e-vapor product use.

Most indoor air quality models reported in the literature are well-mixed models. A well-mixed model estimates the room average concentration of constituents from sources. It does not provide information on (1) how far and how fast the emitted chemicals travel in the indoor space? And (2) how the concentration changes as a function of distance from the emission source? We developed a distributed model, using computational fluid dynamics and thermodynamics principles, which allows for aerosol dispersion in an indoor space and includes evaporation and condensation of constituents in a multi-compound aerosol mixture. The distributed model can estimate the spatial and temporal variations of the concentration of individual constituents present in the emitted aerosol in vapor and particulate phases separately. Results from the model were compared with the published experimental data and were found to be in good agreement. A sensitivity analysis was performed to evaluate the impact of various parameters that affect the air level of the emitted constituents within an indoor space, including rate of emission, the rate of air exchange, etc. The model can also be used to estimate the level of second hand exposure in a confined space where e-vapor products (EVPs) are used.

Determination of Selected Chemical Levels in Room Air and on Surfaces after the Use of Cartridge- and Tank-Based E-Vapor Products or Conventional Cigarettes.

There is an ongoing debate regarding the potential of secondhand exposure of non-users to various chemicals from use of e-vapor products (EVPs). Room air levels of 34 chemicals (nicotine, propylene glycol (PG), glycerol, 15 carbonyl chemicals, 12 volatile organic chemicals (VOCs), and four selected trace elements) were measured where EVPs and cigarettes were used by n = 37 healthy adult tobacco users in an exposure chamber. The products used were MarkTen® 2.5% Classic (Group I), a Prototype GreenSmoke® 2.4% (Group II), Ego-T® Tank with subjects' own e-liquids (Group III) and subjects' own conventional cigarettes (Group IV). Products were used under controlled conditions and 4-h ad libitum use. Background (without subjects) and baseline levels (with subjects) were measured. Cumulative 4-h. levels of nicotine, PG and glycerol measured were several-fold below the time-weighted average limits used in workplace exposure evaluation. Most the other chemicals (>75%) were at or below the limit of quantification during EVP use. Significant levels of chemicals (17 out of 34) were observed in Group IV. Overall, our results indicate that under the study conditions with the products tested, cumulative room air levels of the selected chemicals measured over 4-h were relatively small and were several-fold below the current occupational regulatory and consensus limits.

Development/verification of methods for measurement of exhaled breath and environmental e-vapor product aerosol.

Concerns have been raised about the potential health effects of potential bystander exposure to exhaled aerosols from e-vapor products (EVPs). An exhaled breath collection system (EBS) was developed and analytical methods were verified for collection and analysis of exhaled breath from users of EVPs. Analytical methods were adapted and verified for collection of environmental air samples during EVP use in an exposure chamber. Analysis of constituents in exhaled breath focused on nicotine, propylene glycol, and glycerin (because these are reported as the major constituents in EVPs) and selected carbonyl compounds (acetaldehyde, acrolein, and formaldehyde). Analysis of environmental samples included nicotine, propylene glycol, glycerin, 12 volatile organic compounds (VOCs), 15 carbonyl compounds and 4 metals. The EBS and analytical methods used were found to be suitable for collection and analysis of the target constituents in exhaled breath. Environmental sampling for background levels of VOCs and carbonyl compounds found only acetone, acetaldehyde, benzene, ethylbenzene, formaldehyde, isoprene, methyl ethyl ketone, hexaldehyde, propionaldehyde, and toluene above the limit of quantification in some samples. None of the targeted metals were detected. Background levels of VOCs and carbonyl compounds were consistent with levels previously reported for ambient air.

A Well-Mixed Computational Model for Estimating Room Air Levels of Selected Constituents from E-Vapor Product Use.

Concerns have been raised in the literature for the potential of secondhand exposure from e-vapor product (EVP) use. It would be difficult to experimentally determine the impact of various factors on secondhand exposure including, but not limited to, room characteristics (indoor space size, ventilation rate), device specifications (aerosol mass delivery, e-liquid composition), and use behavior (number of users and usage frequency). Therefore, a well-mixed computational model was developed to estimate the indoor levels of constituents from EVPs under a variety of conditions. The model is based on physical and thermodynamic interactions between aerosol, vapor, and air, similar to indoor air models referred to by the Environmental Protection Agency. The model results agree well with measured indoor air levels of nicotine from two sources: smoking machine-generated aerosol and aerosol exhaled from EVP use. Sensitivity analysis indicated that increasing air exchange rate reduces room air level of constituents, as more material is carried away. The effect of the amount of aerosol released into the space due to variability in exhalation was also evaluated. The model can estimate the room air level of constituents as a function of time, which may be used to assess the level of non-user exposure over time.

Computational modeling of aerosol deposition in respiratory tract: a review.

This review article is intended to serve as an overview of the current status of the computational tools and approaches available for predicting respiratory-tract dosimetry of inhaled particulate matter. There are two groups of computational models available, depending on the intended use. The whole-lung models are designed to provide deposition prediction for the whole lung, from the oronasal cavities to the pulmonary region. The whole-lung models are generally semi-empirical and hence provide more reliable results but within the range of parameters used for empirical correlations. The local deposition or computational fluid dynamics (CFD)-based models, on the other hand, utilize comprehensive theoretical and computational approaches but are often limited to upper respiratory tracts. They are based on theoretical principles and are applicable to a wider range of parameters, but less accurate. One of the difficulties with modeling of aerosol deposition in human lung is related to the complexity of the airways geometry and the limited morphometric data available. Another difficulty corresponds to simulation of the realistic physiological conditions of lung environment. Furthermore, complex physical and chemical phenomena associated with dense and multicomponent aerosols complicate the modeling tasks. All of these issues are addressed in this review. The progress made in each area in the last three decades and the challenges ahead are discussed along with some suggestions for future direction. The following subjects are covered in this review: introduction, aerosol deposition mechanisms, elements of a computational model, respiratory-tract geometry models, whole-lung models, CFD based models, cigarette smoke deposition models, and conclusion.