Parametric study of waste tires through CO2–aided gasification: An investigation of enhanced H2-production using artificial neural network model

Abstract This study presents the waste tire gasification in CO2 atmosphere aiming to produce higher H2 production. At first stage, the waste tire was gasified in horizontal tube reactor in CO2 assistance under different ranges of reaction temperature, heating rate, and residence time. The maximum H2 and gas yields of 46.28 mol % and 72.43 wt. % were obtained at higher temperature of 900 ℃, lower heating rate of 10 ℃/min), and lower residence time of 20 min. While; the tar and char products were decreased considerably from 15.34 to 4.24 wt. % and 35.23 to 23.25 wt. %, respectively. LHV and H2/CO molar ratio of syngas ranged from 9.80-11.07 MJ/Nm3 and 1.41 to 2.18, respectively. Artificial neural network (ANN) model provided a strong relationship among the three variables and the four responses .i.e. estimated regression coefficient (R2) values were obtained as; 0.90, 0.94, 0.93, and 0.96 for H2, CO, CO2, and CH4 respectively. Later, the waste tire was heated from room temperature to 900°C under the heating rates of 10, 20, and 30 ℃/min in thermogravimetric analyzer (TGA). TGA thermograms showed three different degradation stages correspondence to moisture loss, devolatilization and char gasification. The kinetic parameters (activation energy (Ea)), R2 were estimated using Kissinger–Akahira–Sunose (KAS) model. The Ea and R2 were found to be 38.99 kJ/mol and 1.0 for stage 1, 63.01 kJ/mol and 0.94 for stage 2, and 84.73 kJ/mol and 0.91 for stage 3.