Integrated simulation and statistical optimization of eucalyptus globulus air gasification using Aspen Plus and RSM

Biomass gasification provides a sustainable route for renewable energy production, but its performance is governed by operating conditions. In this study, equilibrium modelling of Eucalyptus globulus woodchips in a downdraft gasifier with a solid–gas separator was performed using Aspen Plus. A Box–Behnken design was applied to evaluate the effects of temperature (350–1000 °C), equivalence ratio (0.10–0.30), and moisture content (0–25 %). Higher temperatures substantially enhanced syngas quality, increasing H2 from 4 to 16 mol% and CO from 0 to 22 mol%, raising the LHV by 52 % and improving CGE from 28 to 55 %. Conversely, increasing moisture from 0 to 25 % reduced H2, CO, and CH4 by 35–60 %, lowering syngas LHV by 20 %, CGE by 42 %, and CCE by 30 %. Increasing ER from 0.10 to 0.30 decreased H2, CO, and CH4 by 40–70 % and reduced LHV by 45 %. Tar yield decreased sharply with operating severity, with temperature, ER, and moisture reducing tar by 97 %, 75 %, and 16 %, respectively. The RSM models showed high predictive accuracy (R2 > 95 %), with temperature contributing >79 % to H2 formation and over 87 % to CGE. Optimal conditions were 809.7 °C, an equivalence ratio of 0.10, and 6.5 % moisture, producing a CGE of 71.05 %, LHV of 8.07 MJ/Nm3, and CCE of 83.40 %, with syngas compositions of H2 (18.69 %), CO (25.26 %), CO2 (8.83 %), and CH4 (2.68 %), and a composite desirability of 0.655. Sensitivity analysis confirmed that these operating setpoints are robust to feedstock variations. This integrated modelling and optimization approach provides a practical tool for biomass gasification system design.