First Name:
Meredith
Last Name:
Branham
Major Department:
Mathematical Sciences
Thesis Director:
Eric Marland
Date of Thesis:
May 2014
Earth's climate is changing because of anthropogenic emissions of greenhouse gases. To fully quantify alternatives for adapting to or mitigating these changes we need to carefully characterize emission and uptake of carbon dioxide (CO2). A large percentage of anthropogenic CO2 emissions come from large point sources. In the US over 40% of fossil-fuel derived CO2 emissions are attributable to large point sources. This thesis will show the importance in addressing the spatial uncertainty in large point sources. The US point source dataset, eGRID will be analyzed to assess spatial uncertainty in point source CO2 data and identify locational characteristics of power plants. Available data will be analyzed to develop approaches to reducing and clarifying spatial uncertainty. The analyses from this paper provides a greater understanding of drivers of uncertainty in point source emissions and methods for addressing uncertainty in repurposed data. Keywords: uncertainty, carbon dioxide, point source