Abstract
Polymeric materials flowing through the technosphere are repositories of organic chemicals throughout their life cycle. Equilibrium partition ratios of organic chemicals between these materials and air (KMA) or water (KMW) are required for models of fate and transport, high-throughput exposure assessment and passive sampling. KMA and KMW have been measured for a growing number of chemical/material combinations, but significant data gaps still exist. We assembled a database of 363 KMA and 910 KMW measurements for 446 individual compounds and nearly 40 individual polymers and biopolymers, collected from 29 studies. We used the EPI Suite and ABSOLV software packages to estimate physicochemical properties of the compounds and we employed an empirical correlation based on Trouton's rule to adjust the measured KMA and KMW values to a standard reference temperature of 298 K. Then, we used a thermodynamic triangle with Henry's law constant to calculate a complete set of 1273 KMA and KMW values. Using simple linear regression, we developed a suite of single parameter linear free energy relationship (spLFER) models to estimate KMA from the EPI Suite-estimated octanol-air partition ratio (KOA) and KMW from the EPI Suite-estimated octanol-water (KOW) partition ratio. Similarly, using multiple linear regression, we developed a set of polyparameter linear free energy relationship (ppLFER) models to estimate KMA and KMW from ABSOLV-estimated Abraham solvation parameters. We explored the two LFER approaches to investigate (1) their performance in estimating partition ratios, and (2) uncertainties associated with treating all different polymers as a single "bulk" polymeric material compartment. The models we have developed are suitable for screening assessments of the tendency for organic chemicals to be emitted from materials, and for use in multimedia models of the fate of organic chemicals in the indoor environment. In screening applications we recommend that KMA and KMW be modeled as 0.06 ×KOA and 0.06 ×KOW respectively, with an uncertainty range of a factor of 15.
Highlights
The intensity at which chemicals are produced is growing on a global scale
We present models for partition ratios to six categories of polymeric materials that are de ned based on the 2D chemical structures of their corresponding monomers: polyethylene, polyurethane, polydimethylsiloxane, carbohydrates, polyoxymethylene and nylons. 3D structural differences among the materials associated with properties such as degree of crystallinity, density, porosity and permeability were not taken into spLFER models
Our initial hypothesis was that spLFERs would prove to be more suitable for screening-level applications where the polymer is treated as a bulk substance or the chemical and/or polymeric material are poorly characterized
Summary
The intensity at which chemicals are produced is growing on a global scale. World chemical sales in 2013 increased by about V70 billion compared with 2012, and investment in the synthesis of new chemicals has notably increased over the past ve years.[1]. Partition ratios between polymeric materials and air (KMA) or water (KMW) are required for models of fate and transport of organic chemicals in the indoor environment, e.g. houses, workplaces and vehicles, that have been developed to describe exposure pathways to humans and explain variability of indoor concentrations.[6] In recent years there has been increasing interest in measuring partition ratios of organic chemicals for polymers such as polyurethane and polydimethylsiloxane that are present in the indoor environment and are used as passive samplers of air and water by environmental analytical chemists. KMA and KMW have been measured for a growing number of substances and materials, but signi cant data gaps still exist to reliably quantify these partition ratios for the myriad of organic chemicals and polymers that humans might encounter in a typical day
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