A unified thermochemical conversion framework for hydrogen production from multiple biomass feedstocks

• Integrated Aspen Plus model simulates biomass-to-hydrogen conversion. • Nine Bangladeshi feedstocks assessed across gasification and upgrading stages. • Peak H 2 purity of 89.2 % achieved via PSA with 79 % recovery. • Simulation validated using RMSE (0.87) and MAE (1.7) metrics. • Optimal gasification near at −800 °C boosts H 2 yield and syngas quality. This study presents a validated, simulation-based thermochemical framework for hydrogen production from nine representative biomass feedstocks in Bangladesh. Using Aspen Plus, the integrated model encompasses DFB steam gasification, methanation and SMR as well as WGS reactions alongside hydrogen purification via pressure swing adsorption. Feedstocks-including food waste (FW), municipal solid waste (MSW), rice straw (RS), and wood residues (WR)-were evaluated across gasification temperatures from 500 °C to 1100 °C and steam-to-biomass ratios (SBRs) between 0.2 and 2.0. Hydrogen mole fractions peaked near 800 °C, reaching 65.2 % for MSW, 63.7 % for FW, and 61.5 % for green waste. Increasing SBR enhanced hydrogen yield by up to 30 % while reducing syngas lower heating value from 18 MJ/kg to 9 MJ/kg. Methanation temperature increases from 300 °C to 600 °C decreased CH 4 content from 82 % to 45 % and raised H 2 concentration in synthetic natural gas to 90 %. PSA purification achieved up to 89.2 % hydrogen purity with 79 % recovery. Model predictions aligned well with reference datasets (RMSE: 0.87; MAE: < 1.7). WR and FW delivered the highest hydrogen mass flow rates of 22 kg/hr and 20.5 kg/hr, respectively. Unlike previous studies, this work uniquely integrates all major thermochemical stages while evaluating underexplored biomass types, demonstrating the potential for decentralized, low-carbon hydrogen production. The results establish thermodynamic upper-bound benchmarks and highlight feedstock-dependent performance differences, offering insights relevant for early-stage pathway screening and regional resource assessment.