Modeling residential fine particulate matter infiltration : implications for exposure assessment

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dc.contributor.authorHystad, Perry Wesley
dc.contributor.supervisorKeller, Peter
dc.date.accessioned2008-11-20T18:09:24Z
dc.date.available2008-11-20T18:09:24Z
dc.date.copyright2007en_US
dc.date.issued2008-11-20T18:09:24Z
dc.degree.departmentDepartment of Geography
dc.degree.levelMaster of Science M.Sc.en_US
dc.description.abstractThis research investigates the difference between indoor and outdoor residential fine particulate matter (PM2.5) and explores the feasibility of predicting residential PM2.5 infiltration for use in exposure assessments. Data were compiled from a previous study conducted in Seattle, Washington, USA and a new monitoring campaign was conducted in Victoria, British Columbia, Canada. Infiltration factors were then calculated from the indoor and outdoor monitoring data using a recursive mass balance model. A geographic information system (GIS) was created to collect data that could be used to predict residential PM2.5 infiltration. Spatial property assessment data (SPAD) were collected and formatted for both study areas, which provided detailed information on housing characteristics. Regression models were created based on SPAD and different meteorological and temporal variables. Results indicate that indoor PM2.5 is poorly correlated to outdoor PM2.5 due to indoor sources and significant variations in residential infiltration. A model based on a heating and non-heating season, and information on specific housing characteristics from SPAD was able to predict a large portion of the variation within residential infiltration. Such models hold promise for improving exposure assessment for ambient PM2.5.en_US
dc.identifier.urihttp://hdl.handle.net/1828/1264
dc.languageEnglisheng
dc.language.isoenen_US
dc.rightsAvailable to the World Wide Weben_US
dc.subjectfine particulate matteren_US
dc.subjectparticulate matteren_US
dc.subjectresidentialen_US
dc.subjectinfiltrationen_US
dc.subject.lcshUVic Subject Index::Humanities and Social Sciences::Social Sciences::Geographyen_US
dc.titleModeling residential fine particulate matter infiltration : implications for exposure assessmenten_US
dc.typeThesisen_US

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