SignificanceProtocols for testing and reporting emissions of Harmful and Potentially Harmful Constituents (HPHCs) from electronic cigarettes (e-cigs) are lacking. The premise of this study is that multi-path relationships may be developed to describe interactions between product characteristics, use behavior and emissions to develop appropriate protocols for tobacco product regulatory compliance testing.MethodsThis study proposes a framework consisting of three component terms: HPHC mass concentration, HPHC mass ratio and total particulate mass (TPM) concentration. The framework informs experiments to investigate dependence of aerosol emissions from five electronic cigarettes spanning several design generations and three e-liquids for six repeated trials at each of ten flow conditions.ResultsResults are reported for TPM concentration as a function of flow conditions spanning the range of natural environment topography observed in prior studies. An empirical correlation describing TPM concentration as a function of flow conditions and coil power setting (6, 7.5 and 10 watts) for the Innokin iTaste MVP 2.0 vaporizer with Innokin iClear 30 dual coil tank is presented. Additional results document the impact of flow conditions and wick and coil design on TPM concentration through comparison of the Innokin iClear 30 (upper coil, capillary action wick) and the Innokin iClear X.I (lower coil, gravity fed wick) operated at 7.5 watts. The impact of e-liquid on TPM concentration is illustrated by comparing emissions from an NJOY Vape Pen filled with AVAIL Arctic Blast, Tobacco Row, and Mardi Gras e-liquids. TPM concentration is shown to depend upon flow conditions across a range of e-cigarette product designs including cig-a-like, pen-style, box-mod and emergent disposable-cartridge style devices.ConclusionsA framework provides a foundation for reporting emissions across a variety of e-cigs, e-liquids and research laboratories. The study demonstrates TPM concentration is a function of topography behavior (i.e. puff flow rate and puff duration) for varying device operating power and product characteristics.

A framework describing the joint effect of user topography behavior and product characteristics of one exemplar device on the total particulate mass (TPM) and aerosol constituent yield delivered to a user is presented and validated against seven user-specific ‘playback’ emissions observations. A pen-style e-cig was used to collect emissions across puff flow rates and durations spanning the range observed in the natural environment. Emissions were analyzed with GC-MS and used to construct empirical correlations for TPM concentration and nicotine mass ratio. TPM concentration was demonstrated to depend upon both puff flow rate and duration, while nicotine mass ratio was not observed to be flow-dependent under the conditions presented. The empirical model for TPM and nicotine yield demonstrated agreement with experimental observations, with Pearson correlation coefficients of r = 0.79 and r = 0.86 respectively. The mass of TPM and nicotine delivered to the mouth of an e-cig user are dependent upon the puffing behavior of the user. Product-specific empirical models of emissions may be used in conjunction with participant-specific topography observations to accurately quantify the mass of TPM and nicotine delivered to a user.

Standardized topography protocols for testing cigarette emissions include the Federal Trade Commission/International Standard Organization (FTC/ISO), the Massachusetts Department of Health (MDPH), and Health Canada (HC). Data are lacking for how well these protocols represent actual use behavior. This study aims to compare puff protocol standards to actual use topography measured in natural environments across a range of cigarette brands. Current smokers between 18 and 65 years of age were recruited. Each participant was provided with a wPUM™ cigarette topography monitor and instructed to use the monitor with their usual brand cigarette ad libitum in their natural environment for one week. Monitors were tested for repeatability, and data were checked for quality and analyzed with the TAP™ topography analysis program. Data from n = 26 participants were analyzed. Puff flow rates ranged from 17.2 to 110.6 mL/s, with a mean (STD) of 40.4 (21.7) mL/s; durations from 0.7 to 3.1 s, with a mean (STD) of 1.5 ± 0.5 s; and volumes from 21.4 to 159.2 mL, with a mean (STD) of 54.9 (29.8) mL. Current topography standards were found to be insufficient to represent smoking across the wide range of real behaviors. These data suggest updated standards are needed such that emissions tests will provide meaningful risk assessments.

Computational models are useful for understanding respiratory physiology. Crucial to such models are the boundary conditions specifying the flow conditions at truncated airway branches (terminal flow rates). However, most studies make assumptions about these values, which are difficult to obtain in vivo. We developed a computational fluid dynamics (CFD) model of airflows for steady expiration to investigate how terminal flows affect airflow patterns in respiratory airways. First, we measured in vitro airflow patterns in a physical airway model, using particle image velocimetry (PIV). The measured and computed airflow patterns agreed well, validating our CFD model. Next, we used the lobar flow fractions from a healthy or chronic obstructive pulmonary disease (COPD) subject as constraints to derive different terminal flow rates (i.e., three healthy and one COPD) and computed the corresponding airflow patterns in the same geometry. To assess airflow sensitivity to the boundary conditions, we used the correlation coefficient of the shape similarity (R) and the root-mean-square of the velocity magnitude difference (Drms) between two velocity contours. Airflow patterns in the central airways were similar across healthy conditions (minimum R, 0.80) despite variations in terminal flow rates but markedly different for COPD (minimum R, 0.26; maximum Drms, ten times that of healthy cases). In contrast, those in the upper airway were similar for all cases. Our findings quantify how variability in terminal and lobar flows contributes to airflow patterns in respiratory airways. They highlight the importance of using lobar flow fractions to examine physiologically relevant airflow characteristics.