This 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.
| Identifer | oai:union.ndltd.org:uvic.ca/oai:dspace.library.uvic.ca:1828/1264 |
| Date | 20 November 2008 |
| Creators | Hystad, Perry Wesley |
| Contributors | Keller, Peter |
| Source Sets | University of Victoria |
| Language | English, English |
| Detected Language | English |
| Type | Thesis |
| Rights | Available to the World Wide Web |
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