The prediction model of regression for the CO removal from exhaust using plasma- catalyst process

Abstract

Abstract Background. The present study considers the main physicochemical parameters included in the optimum removal efficiency of carbon monoxide (CO) using the plasma-driven catalysis reactor. Material and Methods. A nonthermal plasma (NTP) –catalyst process was applied to investigate the removal efficiency of CO. The interaction of proposed factors such as; temperature, space-time, propane concentration, applied voltage, and the current was studied to estimate the optimum conditions of CO removal efficiency. Data analysis of experiments was done using General Linear Model (GLM) analysis in SPSS (version 22.0.) and fit linear regression model in MATLAB R2013a software. Results and Discussion. The results showed the interaction of temperature and space-time play a key role in CO removal (P-value <0.05). This interaction was found significantly positive with a decrease in space-time. The effect of applied voltage and current (i.e., two main parameters of power consumption) was found significant in the interaction model of C3H8/CO ratio with temperature, as well as space-time. Also, the presented regression model of results confirms the meaningful effect of interactions. Reduction of space-time is known as an energy consumption parameter controlled by reactor gap discharge, gas composition, and inner electrode material. The effect of propane presence as a reducer agent in the gas composition was found significant in the interaction model of space-time and temperature. Conclusion. Considering physicochemical parameters in designing NTP- catalyst reactors can influence energy efficiency significantly.