How Much Transportation Investment Is Needed for Expected Accessibility Enhancement Goal

Author(s):  
Hongzhi Lin ◽  
Yongping Zhang
Author(s):  
Cherie Gambino ◽  
T. Agami Reddy

Abstract Stakeholders in the aviation industry committed to a goal of 50% reduction in carbon emissions by the year 2050, to be achieved by reducing emissions 1.5% each year from 2020 onwards. There are multiple pathways to achieve this goal however; with, the most promising technology being Sustainable Aviation Fuels (SAF), which are biofuels blended with kerosene. As the industry shifts towards SAF, it is important to evaluate these fuels in terms of their long-term sustainability, and this is the objective of the current study. Sixteen types of fuels were assessed which include fossil, natural gas, electric, and SAF. A Multi Criterion Decision Making methodology was adopted which considers three categories, namely environmental, economic, and social aspects which in turn are broken up into 8 indicators in all (such as ecological footprints, cost of transportation, investment cost, operating costs, employment generation, and health & safety). A Monte Carlo analysis was also performed to analyze sensitivity of the results to the weights attributed to the three categories. The most sustainable fuel was found to be Hydrogen, with a score of 0.91 out of 1.0. The least sustainable were determined to be the military kerosene-based fuels (with the experimental fuel JP-8 + 100LT being the poorest with a normalized score of 0.50).


2018 ◽  
Vol 56 (1) ◽  
pp. 154-187 ◽  
Author(s):  
Chris L. Hess

Research often finds a positive relationship between public transportation investment and gentrification in nearby neighborhoods. This dynamic is particularly important in urban contexts that plan for transit-oriented development and creating future “walkability.” In this study, I demonstrate a link between transit investment and changing neighborhood racial and ethnic composition, using a case study of the recent light-rail project in Seattle, Washington. Descriptive analyses and difference-in-difference models suggest that affected neighborhoods in Seattle experienced rising shares of non-Hispanic Whites following the start of light-rail construction, while neighborhoods at the suburban periphery of the line saw substantial growth in racial and ethnic diversity. These findings highlight the role of transit infrastructure in restructuring demographic trajectories of nearby neighborhoods and contribute evidence about shifting patterns of residential segregation in the area around the transit line.


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