Abstract

Abstract Gasoline is a highly flammable liquid derived mainly from crude oil that is used primarily as an energy source for internal combustion engines. To be competitive, gasoline must meet certain standards of high quality such as Octane number, Ried Vapor Pressure (RVP), and minimal environmental pollutions. This work aims at optimizing the production of a high-quality gasoline blend that meets the Octane number, RVP, Economic and Environmental standards, using varying oxygenates. The gasoline blending was executed by employing the linear programming solver application in Microsoft excel using four blending components namely the Fluid catalytic cracking gasoline (FCCG), Straight run naphtha (SRN), Straight run gasoline (SRG), Butane, and varying Oxygenates. The Blending process was simulated in ASPEN HYSYS simulation software, and the output product was tested for pollutant emissions in the same software. The selected blend was further optimized to minimize emission using the Response Surface Methodology in MINITAB version 18. Upon gasoline blending optimization and emissions testing, four blends met our specifications namely, the MTBE blend, the ETBE-blend, the Ethanol-blend, 1-Butanol blend. After a simple weighting method, the Ethanol was selected as the optimal blend having a net savings of 67.09 tons/year and 476tons/year of NOx and TVOC emissions respectively, a net increase of 16.35 tons/year of TTC emissions. The Blend was further optimized using RSM. The optimization results showed that SRG was the main contributor to NOx emissions, ethanol was a significant contributor to the TTC emissions while Butane had no effect of both emissions. The new optimized ethanol-blend gave a further 90.42% reduction in NOx emissions, and 67.85% reduction in TTC emissions, but with an increased amount of ethanol in the blend. The economics of a gasoline blending plant was evaluated, giving a pay-back period of 2.46 year, NPV @ 10th year of $177.6 million, an internal rate of return of 57.36%, and a profitability index of 3.04. This showed that the process would be highly profitable.

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