A quantitative structure-property relationship (QSPR) for estimating solid material-air partition coefficients of organic compounds

Abstract

The material-air partition coefficient (Kma) is a key parameter to estimate the release of chemicals incorporated in solid materials and resulting human exposures. Existing correlations to estimate Kma are applicable for a limited number of chemical-material combinations without considering the effect of temperature. The present study develops a quantitative structure-property relationship (QSPR) to predict Kma for a large number of chemical-material combinations. We compiled a dataset of 991 measured Kma for 179 chemicals in 22 consolidated material types. A multiple linear regression model predicts Kma as a function of chemical's Koa, enthalpy of vaporization (∆Hv), temperature, and material type. The model shows good fitting of the experimental dataset with adjusted R2 of 0.93 and has been verified by internal and external validations to be robust, stable and has good predicting ability (R2ext > 0.78). A generic QSPR is also developed to predict Kma from chemical properties and temperature only (adjusted R2 = 0.84), without the need to assign a specific material type. These QSPRs provide correlation methods to estimate Kma for a wide range of organic chemicals and materials, which will facilitate high-throughput estimates of human exposures for chemicals in solid materials, particularly building materials and furniture.