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Date

1-17-2014

Description

Identification and Characterization of PM2.5 and VOC Hot Spots on Arterial Corridor by Integrating Probe Vehicle, Traffic, and Land Use Data: 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 (PM2.5) and volatile organic compound (VOC) hot spot locations on urban arterial corridors. An emission hot spot is defined as a fixed location along a corridor in which the mean pollutant concentrations are consistently above the 85th percentile of pollutant concentrations when considering all other locations along the corridor during the same time period. In order to collect data for this study, an electric vehicle was equipped with instruments designed to measure PM2.5 and VOC 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 are used to better understand which data sources are most valuable in estimating PM2.5 and VOC hot spot locations consistent with empirical data, as well as which variables have the greatest impact on emissions and pollutant levels at a microscale level. This research highlights the importance of considering both consistency and peak emission levels 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.

Subjects

Traffic congestion -- Environmental aspects, Air quality management, Transportation -- Management -- Environmental aspects

Disciplines

Transportation | Urban Studies and Planning

Persistent Identifier

http://archives.pdx.edu/ds/psu/18401

Identficaton and Characterization of Pollutant Hot Spots Integratng Probe Vehicle, Traffic and Land Use Data

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