(untitled) (Chemical Engineering Research Bulletin, 2026)
Energy scarcity is soaring due to the over exploitation of fossil fuel reserves in Bangladesh. On the contrary, a potential energy source i.e. organic municipal solid waste is creating a serious environmental hazard for municipalities ascribe to ineffective and commercially unviable waste management strategy. Therefore, the present study was performed on a dry anaerobic digestion process for biogas production from unsorted organic municipal solid waste. In batch digesters with a 5L effective capacity, the performance of the dry anaerobic digestion (DAD) process of solid waste was assessed during the period of 35 days of operation. Different factors i.e. temperature (35°C, 40°C, and 45°C), micro-nutrients (Na+, K+, Co+) and inoculum mixing ratio (Anaerobic sludge: Cow manure = 1:2, 1:3 and 2:1) were analyzed to observe the biogas production. The results show that biogas production was comparatively higher (approx. 375 mL/day) for 35°C where anaerobic sludge (AS) to cow manure (CS) ratio more than 1. The obtained gas composition was analyzed further to compare the biomethane production depending on these factors. A machine learning (ML) algorithm i.e. Random Forest Regressor was implemented to predict the biogas generation considering different parameters. The model showed performance with more than 77.8% accuracy (R-squared value). Future research can be performed by conducting experiments considering other factors which affects biogas generation and a better model can be implemented to predict the nature of biomethane production. Chemical Engineering Research Bulletin: 24 (Issue 1): 20-29