A mathematical programming approach to reducing carbon dioxide emissions in the petroleum refining industry

While fossil fuels supplied around 90% of the developed world's energy in 2008, the resulting CO 2 emissions took a tremendous toll on the environment. As power plants, factories, and oil refineries are the largest CO 2 emitters, it is vital to find greener ways to extract, refine and utilize fossil fuels. In this paper, we introduce a nonlinear mixed-integer programming model which is intended to help decision makers evaluate the operational cost of different alternatives for reducing CO 2 emissions at petroleum refineries such as powering the refineries using renewable energy sources. To validate our model, we solve several small-size instances of the problem using the BARON solver in GAMS.