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Experimentally Validated Mathematical Model of Analyte Uptake by Permeation Passive Samplers

Abstract

A mathematical model describing the sampling process in a permeation-based passive sampler was developed and evaluated numerically. The model was applied to the Waterloo Membrane Sampler (WMS), which employs a polydimethylsiloxane (PDMS) membrane as a permeation barrier, and an adsorbent as a receiving phase. Samplers of this kind are used for sampling volatile organic compounds (VOC) from air and soil gas. The model predicts the spatio-temporal variation of sorbed and free analyte concentrations within the sampler components (membrane, sorbent bed and dead volume), from which the uptake rate throughout the sampling process can be determined. A gradual decline in the uptake rate during the sampling process is predicted, which is more pronounced when sampling higher concentrations. Decline of the uptake rate can be attributed to diminishing analyte concentration gradient within the membrane, which results from resistance to mass transfer and the development of analyte concentration gradients within the sorbent bed. The effects of changing the sampler component dimensions on the rate of this decline in the uptake rate can be predicted from the model. Performance of the model was evaluated experimentally for sampling of toluene vapors under controlled conditions. The model predictions proved close to the experimental values. The model provides a valuable tool to predict changes in the uptake rate during sampling, to assign suitable exposure times at different analyte concentration levels, and to optimize the dimensions of the sampler in a manner that minimizes these changes during the sampling period.

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Publication details

The article was received on 11 Jul 2017, accepted on 14 Sep 2017 and first published on 14 Sep 2017


Article type: Paper
DOI: 10.1039/C7EM00315C
Citation: Environ. Sci.: Processes Impacts, 2017, Accepted Manuscript
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    Experimentally Validated Mathematical Model of Analyte Uptake by Permeation Passive Samplers

    F. Salim, M. Ioannidis and T. Gorecki, Environ. Sci.: Processes Impacts, 2017, Accepted Manuscript , DOI: 10.1039/C7EM00315C

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