Title

Investigating Carbon Footprint Reduction Potential Of Public Transportation In United States: A System Dynamics Approach

Keywords

CO mitigation 2; Policy making; Public transportation; System dynamics; Transportation mode choice

Abstract

As part of sustainable urban planning, the potential of public transportation modes has been studied to reduce CO2 emissions and energy consumption and to increase roadway safety. Increasing public transportation ridership shares compared to drive alone transportation mode would therefore be a giant step toward more environmentally friendly and stress-free cities, and so this study aims to propose possible public transportation policies to be adopted by policy makers or urban planners. Although public transportation is one of the sub-sections of urban planning, it has a wide variety of aspects that affect local societies and the environment, so a system dynamics approach is used to model and simulate the most realistic and practical CO2 mitigation scenarios for U.S. cities by adopting public transportation policies for future years. Based on historical data and applicable model validation processes, the behavior of the U.S. commuters’ transportation mode choice and the potential of transit transportation to mitigate CO2 emissions are both forecasted for future years up to 2050 under several possible policy scenarios. The results indicate that, in order to decrease fuel consumption and CO2 emission trends, marginal and ambitious scenarios should be implemented. For instance, increasing public transportation ridership by 9% has the potential to reduce CO2 emissions by 766,000 tonnes annually in 2050, whereas a 25% increase in ridership could potentially reduce cumulative CO2 emissions by 61.3 million tonnes.

Publication Date

10-1-2016

Publication Title

Journal of Cleaner Production

Volume

133

Number of Pages

1260-1276

Document Type

Article

Personal Identifier

scopus

DOI Link

https://doi.org/10.1016/j.jclepro.2016.06.051

Socpus ID

85006757785 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/85006757785

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