Comparison of Control Strategies for Greenhouse Gas Emissions from Public Transit Buses in Ohio and its Climatic Implications

摘要

The transportation sector is one of the largest feeders of greenhouse gas (GHG) emissions in the United States. The GHG emissions are a cause of serious concern because of their effect on human health and their co-inhabitants. Reducing pollution levels for a healthier future is widely debated and is the need of the hour as because each time GHG emission doubles, there is a 5.4°F rise in temperature. For every degree temperature increment, the chances of an extreme weather event occurrence increases. One of the prime strategies that have been put in place to further reduce pollution is switching to public transportation as we move into the future. In years to come, however, the increasing demand and pressure would necessitate the adoption of strategies that would reduce pollution from public transit system. There is immense scope in various possible control strategy options to cut down emission levels from public transit systems such as alternative fuels, land-use management, inspection and maintenance of in-use vehicles, and vehicle scrappage etc. In this thesis, an effort is made to identify strategies and perform modelling operations in freeware to estimate the capacity of the strategies to curb emissions from public transit buses in the State of Ohio. Projections for ten years (2015-2025) into future emissions from public transit buses in Ohio have been analyzed under three scenarios: the worst case, base case, and the best case. Historical datasets have been used to a large extent during the study to understand and predict future vehicular population. Since, future predictions possess a certain degree of uncertainty; a sensitivity analysis has been performed to check how subtle the output values are with respect to the input parameters. The contribution of predicted emission levels on radiative forcing have been linked to figure out the overall impact on the temperature of the Ohio region in ten years to come.;Computer modelling using software such as GREET, MOVES2014, and mixed-use trip generation model were used primarily to establish the futuristic emission trends for public transit buses. The uncertainty of the datasets obtained is tested using what-if scenario analysis. Of all the strategies discussed, the biodiesel fuel has been found to be the most efficient followed by natural gas and its blends, land-use planning and inspection and maintenance of transit buses, in that order. 80 % reduction in CO2 emissions can be achieved if the control strategies were to be used as in the best case scenario in Ohio. As a result of reduction in emissions, the reduction in temperature would be 0.005 °C approximately.