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

Introduction:
This text presents a computational modeling method to predict air levels of exhaled constituents from e-vapor product (EVP) use, with the goal of estimating potential secondhand exposure to non-users. The study measured select constituent levels in exhaled breath from adult e-vapor product users and used a validated computational model to predict constituent levels under three scenarios (car, office, and restaurant) to estimate likely secondhand exposure to non-users.

Key points:

* The study measured levels of nicotine, propylene glycol, glycerin, menthol, formaldehyde, acetaldehyde, and acrolein in exhaled breath samples during the use of four different e-liquids in a cartridge-based EVP.
* 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.
* The study found that acetaldehyde and acrolein were below detectable limits in exhaled breath after EVP use.
* The model was based on physical/thermodynamic interactions between air, vapor, and the 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.

Main message:
The study demonstrates a computational modeling method to estimate secondhand exposure to exhaled constituents from EVP use, and the results suggest that the potential for non-users to be exposed to harmful chemicals is lower during EVP use compared to cigarette smoking. The model can be used to inform regulatory decisions and guidelines around EVP use in various settings. It is important to note that more research is needed to fully understand the potential health impacts of EVP use on both users and non-users.

Edmiston JS, Rostami aa, Liang q, Miller S, Sarkar Ma. Computational modeling method to estimate secondhand exposure potential from exhalations during e-vapor product use under various real-world scenarios. Internal and emergency medicine. 2022;17(7):2005-2016. doi:10.1007/s11739-022-03061-2