High Occupancy Toll (HOT) lanes were recently proposed for I-85 in Atlanta as a way to relieve congestion and provide a reliable commute time for single occupant drivers that are willing to pay a toll. It is important to evaluate the air quality impacts of such a proposal to meet environmental regulations, such as the National Environmental Policy Act (NEPA) and Transportation Conformity Regulations.
The goal of this study is to understand how vehicle mass emissions change as a result of implementing HOT lanes on I-85 in Atlanta . This is done by considering a number of factors affect mass vehicle emissions, such as vehicle activity, vehicle speeds, vehicle age distributions, and vehicle class distributions. These factors are incorporated into a base scenario, which models the current condition on I-85 with HOV lanes, and a future scenario, which models the implementation of HOT lanes on this corridor. The base scenario mainly uses data from a data collection effort by Georgia Tech during the summer of 2007 on the I-85 corridor, while the future scenario makes alterations to these data using information from other cities that have already implemented HOT lanes.
The MOBILE-Matrix modeling tool, which was recently developed by Georgia Tech [16], was used to run the emissions analysis using the input factors from these data sources. This tool calculated mass emissions for five pollutants: HC, NOx, CO, PM2.5, and PM10. The results show very small increases in mass emissions for NOx, CO, PM2.5, and PM10, and very small decreases in mass emissions for HC. Therefore, the implementation of HOT lanes on I-85 in Atlanta is unlikely to violate the Transportation Conformity Rule. For NEPA purposes, this analysis could be used to make the case that air quality impacts are not significant, and therefore further detailed analyses are not required.
Identifer | oai:union.ndltd.org:GATECH/oai:smartech.gatech.edu:1853/29692 |
Date | 10 July 2008 |
Creators | Kall, David |
Publisher | Georgia Institute of Technology |
Source Sets | Georgia Tech Electronic Thesis and Dissertation Archive |
Detected Language | English |
Type | Thesis |
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