The purpose of this study is to explore the use of integrated probe vehicle, traffic and land use data to identify and characterize fine particulate matter (PM[subscript 2.5]) hot spot locations on urban arterial corridors. In addition, a preliminary analysis is conducted to consider volatile organic compound (VOC) hot spot locations. A pollutant hot spot is defined as a location on a corridor in which the mean pollutant concentrations are consistently above the 85th percentile of pollutant concentrations when compared to all locations along the corridor. In order to collect data for this study, an electric vehicle was equipped with instruments designed to measure PM[subscript 2.5] and total VOC (TVOC) concentrations. Second-by-second measurements were performed for each pollutant from both the right and left sides of the vehicle. Detailed meteorological, traffic and land use data is also available for this research. The results of a statistical analysis, including multiple regression, are used to better understand which data sources are most valuable in estimating PM[subscript 2.5] hot spot locations consistent with empirical data; knowledge is gained as to which variables have the strongest statistical relationships with traffic emissions and pollutant levels at a corridor level. A preliminary analysis is also completed to consider which variables are statistically related to TVOC hot spot locations. This research highlights the importance of considering both consistency and magnitude of pollutant concentrations when identifying hot spot locations. An objective of this research is to develop a method to identify urban arterial hot spot locations that provides a balance of efficiency (in terms of capital expenses, time, resources, expertise requirements, etc.) and accuracy.
| Identifer | oai:union.ndltd.org:pdx.edu/oai:pdxscholar.library.pdx.edu:open_access_etds-2534 |
| Date | 13 December 2013 |
| Creators | Bell, Katherine Eleanor |
| Publisher | PDXScholar |
| Source Sets | Portland State University |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Dissertations and Theses |
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