A Spatial Multi-Criteria Framework for Data-Driven Anaerobic Co-Digestion Substrate Selection in Tropical Regions

The transition to a circular bioeconomy in developing economies is frequently hindered by the operational failure of biogas facilities due to feedstock supply discontinuity. Whilst biochemical potential is traditionally the primary selection criterion, this study postulates that logistic reliability serves as the governing constraint for sustainable implementation. To validate this paradigm shift, a spatially explicit decision-making framework integrating Shannon Entropy and TOPSIS was developed and applied to a representative tropical agro-industrial region. By evaluating conflicting criteria covering logistic availability, technical efficiency, and biochemical stability, the model identified Annual Residue Production as the dominant weighting factor. Results established Cattle Manure as the universal baseload substrate essential for mitigating seasonality risks, outweighing higher-yielding but intermittent agricultural residues. Spatial analysis further revealed distinct bioenergy clusters dictating tailored technological strategies: a high-potential Rice-Livestock cluster suitable for centralised industrial plants overseeing recalcitrant biomass, and a Cassava-Livestock cluster favourable for decentralised, low-tech digestion. This data-driven approach demonstrates that successful substrate selection must transcend theoretical yield maximisation to prioritise supply chain reliability, providing a robust roadmap for de-risking bioenergy investments in tropical regions.