Science Inventory

Experimental Method Development for Estimating Solid-phase Diffusion Coefficients and Material/Air Partition Coefficients of SVOCs

Citation:

Liu, X., Z. Guo, AND N. Roache. Experimental Method Development for Estimating Solid-phase Diffusion Coefficients and Material/Air Partition Coefficients of SVOCs. ATMOSPHERIC ENVIRONMENT. Elsevier Science Ltd, New York, NY, 89:78-84, (2014).

Impact/Purpose:

This is a product for CSS 2.3.1. It is to develop a chamber testing method for measuring material/air partition coefficients (K) and solid phase diffusion coefficients (D) for SVOCs.

Description:

The solid-phase diffusion coefficient (Dm) and material-air partition coefficient (Kma) are key parameters for characterizing the sources and transport of semivolatile organic compounds (SVOCs) in the indoor environment. In this work, a new experimental method was developed to estimate parameters, Dm and Kma. The SVOCs chosen for study were polychlorinated biphenyl (PCB) congeners, including PCB-52, PCB-66, PCB-101, PCB-110, and PCB-118. The test materials included polypropylene, high density polyethylene, low density polyethylene, polytetrafluoroethylene, polyether ether ketone, glass, stainless steel and concrete. Two 53-liter environmental chambers were connected in series, with the relatively stable SVOCs source in the source chamber and the test materials, made as small “buttons”, in the test chamber. Prior to loading the test chamber with the test materials, the test chamber had been dosed with SVOCs for 12 days to “coat” the chamber walls. During the tests, the material buttons were removed from the test chamber at different exposure times to determine the amount of SVOC absorbed by the buttons. SVOC concentrations at the inlet and outlet of the test chamber were also monitored. The data were used to estimate the partition and diffusion coefficients by fitting a sink model to the experimental data. The parameters obtained were employed to predict the accumulation of SVOCs in the sink materials using an existing mass transfer model. The model prediction agreed reasonably well with the experimental data.

Record Details:

Record Type:DOCUMENT( JOURNAL/ PEER REVIEWED JOURNAL)
Product Published Date:06/03/2014
Record Last Revised:04/30/2015
OMB Category:Other
Record ID: 307509