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Title: Gas-phase exposure history derived from material-phase concentration profiles
Author (s): Morrison, Glenn
Little, J.C.
Xu, Y.
Rao, M.
Enke, D.
Department/Lab Affiliations: Civil, Architectural & Environmental Engineering
Environmental Research Center
Keywords: Artificial neural network
Exposure
Exposure history
Indoor air pollution
Inverse diffusion
Issue Date: 2007
Publisher: Elsevier
Citation: GC Morrison, JC Little, Y Xu, M Rao, D Enke. Gas-phase exposure history derived from material-phase concentration profiles. Atmospheric Environment. 2007 41(15): 3276-3286.
Abstract: Non-reactive gas-phase pollutants such as benzene diffuse into indoor furnishings and leave behind a unique material-phase concentration profile that serves as a record of the past gas-phase indoor concentrations. The inverse problem to be solved is the diffusion equation in a slab such as vinyl flooring. Using knowledge of the present material-phase concentration profile in the slab, we seek to determine the historical material-phase concentration at the surface exposed to indoor air, and hence the historical gas-phase concentration, which can be used directly to determine exposure. The problem as posed has a unique solution that may be solved using a variety of approaches. We use a trained artificial neural network (ANN) to derive solutions for hypothetical exposure scenarios. The ANN results show that it is possible to estimate the intensity and timing of past exposures from the material-phase concentration profile in a building material. The overall method is limited by (1) the resolution of techniques for measuring spatial material-phase concentration profiles, (2) how far back in time we seek to determine exposure and (3) the representational power of the ANN solution. For example, we estimate that this technique can estimate exposure to phenol up to 0.5 y in the past from analyses of vinyl flooring.
Type: Article - Journal
text
Copyright Notice: This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.
FULL COPYRIGHT INFORMATION:
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Publisher URL:
http://dx.doi.org/10.1016/j.atmosenv.2006.07.055
Link to this page:
http://scholarsmine.mst.edu/post_prints/Gas-PhaseExposureHistoryDerivedFromMaterial_09007dcc803f64b1.html



titleGas-phase exposure history derived from material-phase concentration profiles
contributor.authorMorrison, Glenn
contributor.authorLittle, J.C.
contributor.authorXu, Y.
contributor.authorRao, M.
contributor.authorEnke, D.
contributor.deptlabCivil, Architectural & Environmental Engineering
contributor.deptlabEnvironmental Research Center
contributor.sponsorNational Science Foundation
subjectArtificial neural network
subjectExposure
subjectExposure history
subjectIndoor air pollution
subjectInverse diffusion
date.issued2007
publisherElsevier
identifier.citationGC Morrison, JC Little, Y Xu, M Rao, D Enke. Gas-phase exposure history derived from material-phase concentration profiles. Atmospheric Environment. 2007 41(15): 3276-3286.
identifier.pub.URI
http://dx.doi.org/10.1016/j.atmosenv.2006.07.055
description.abstractNon-reactive gas-phase pollutants such as benzene diffuse into indoor furnishings and leave behind a unique material-phase concentration profile that serves as a record of the past gas-phase indoor concentrations. The inverse problem to be solved is the diffusion equation in a slab such as vinyl flooring. Using knowledge of the present material-phase concentration profile in the slab, we seek to determine the historical material-phase concentration at the surface exposed to indoor air, and hence the historical gas-phase concentration, which can be used directly to determine exposure. The problem as posed has a unique solution that may be solved using a variety of approaches. We use a trained artificial neural network (ANN) to derive solutions for hypothetical exposure scenarios. The ANN results show that it is possible to estimate the intensity and timing of past exposures from the material-phase concentration profile in a building material. The overall method is limited by (1) the resolution of techniques for measuring spatial material-phase concentration profiles, (2) how far back in time we seek to determine exposure and (3) the representational power of the ANN solution. For example, we estimate that this technique can estimate exposure to phenol up to 0.5 y in the past from analyses of vinyl flooring.
typeArticle - Journal
type.DCMITypetext
type.statusFinal version
rightsThis material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.
rights.URI
http://www.elsevier.com/wps/find/authorsview.authors/authorsrights
date.accessioned2007-04-11T17:00:48Z
date.available2007-12-17T20:46:31Z
identifier.persist.URI
http://scholarsmine.mst.edu/post_prints/Gas-PhaseExposureHistoryDerivedFromMaterial_09007dcc803f64b1.html