Methanation of CO2 using H2 obtained by renewable energy sources has been gaining attention as one of the promising options for utilizing captured CO2 and surplus power obtained when intermittent power sources such as solar and wind energy are used. Herein, kinetics of CO2 methanation over Ni/ZrO2 was studied using a tubular quartz reactor at 0.9 MPa. The Sabatier reaction (CO2 + 4H2 = CH4 + 2H2O, ΔH r 298K = – 165 kJ mol–1) was carried out under stoichiometric gas feeding (CO2/H2 = 1/4 v/v to CH4/H2O = 1/2 v/v), and its reaction rate was determined. The exothermic nature of CO2 methanation and extremely high catalytic activities increased the reaction temperature to 400–600 °C even when the feed-gas temperature was as low as 250–400 °C, and the gas hourly space velocity was as high as 3 × 106 h–1. Nonlinear regression analyses based on one- and multistep kinetic models were used to investigate the reaction rates to estimate the kinetic parameters. Both models with optimized parameters can reproduce the experimentally obtained CH4 formation rates for the entire range of the feed-gas conversion with a coefficient of determination (R 2) of over 0.98.

CO 2 methanation, which converts CO 2 and hydrogen into methane as fuel, is one of the promising candidates for the development of CO 2 utilization technologies. Recently, a highly active catalyst made of Ni/ZrO 2 for methanation has been developed, and is currently investigated as a potential use in a highperformance reactor. However, design of reactor must be carried out carefully, since this reaction is highly exothermic, which may cause reactor runaway and deterioration of catalysts. For this problem, a mathematical model that can predict the behavior inside the reactor is necessary. In this work, we consider the methanation reaction of CO 2 in a reactor model and estimate the kinetic parameters in the reaction rate model from experimental data. In the parameter estimation using literature values and Tikhonov regularization, eight kinetic parameters in the rate equations were identified from 64 data points with a wide range of conditions. We confirm that molar fractions at the reactor exit predicted by this reactor model are in good agreement with the experimental results. Furthermore, the developed model was validated to predict the compositions and temperature that were not used in the estimation. We expect the developed model will be a powerful tool for the reactor design.