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ORCID

https://orcid.org/0000-0003-4891-9035

Document Type

Open Access Thesis

Embargo Period

11-10-2019

Degree Program

Civil Engineering

Degree Type

Master of Science in Civil Engineering (M.S.C.E.)

Year Degree Awarded

2019

Month Degree Awarded

May

Abstract

The transportation sector is considered one of the major contributors to greenhouse gas (GHG) emissions in metropolitan areas, and any efforts to reduce these emissions requires strategic management of multiple transportation modes. This paper presents a method to identify opportunities to reduce GHG emissions by expanding commuter bus services and incentives to shift commuters from private cars to transit. The approach uses a nested multinomial logit model for mode choice in a region that includes driving alone, carpooling, walking, cycling, and using four possible transit modes (ferry, commuter rail, rapid transit and bus) by walk access or driving access. A model of existing conditions was calibrated with data from the Boston metropolitan area. Using an emission factor model based on average speeds from the California Air Resources Board (CARB), the net effect of new commuter bus service on GHG emissions from transportation was estimated. Potential GHG reductions are weighed against the capital and operating costs of new transit services to quantify the cost-effectiveness of a new commuter bus service for isolated origin-destination pairs. This modeling framework is used to optimize fares and bus frequency in order to identify the corridors with the most cost-effective potential for GHG reduction. Results are presented for the Boston region, demonstrating the feasibility of implementation and the potential magnitude of benefits for cost-effectively reducing GHG emissions associated with transportation. The method is general and can be applied in other cities around the world.

First Advisor

Dr. Eric Gonzales

Second Advisor

Dr. Eleni Christofa

Third Advisor

Dr. Song Gao

Creative Commons License

Creative Commons Attribution 4.0 License
This work is licensed under a Creative Commons Attribution 4.0 License.

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