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

• Main Authors: Ali A. Rostami, Yezdi B. Pithawalla, Jianmin Liu, Michael J. Oldham, Karl A. Wagner, Kimberly Frost-Pineda, Mohamadi A. Sarkar
• Format: Article
• Language: English
• Published: MDPI AG 2016-08-01
• Series: International Journal of Environmental Research and Public Health
• Subjects: e-cigarette; aerosol; e-vapor product; EVP; passive vaping; modeling; computational model; secondhand exposure; exhaled breath; indoor air quality
• Online Access: http://www.mdpi.com/1660-4601/13/8/828

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.