A study on the effect of temperature and micro- nutrients in biogas production by dry anaerobic digestion of municipal solid waste

Authors

  • Abdullah Bin Murad Department of Chemical Engineering & Polymer Science, Shahjalal University of Science & Technology, Sylhet, Bangladesh
  • Syed Readwan Ahmed Department of Chemical Engineering & Polymer Science, Shahjalal University of Science & Technology, Sylhet, Bangladesh
  • Azhar Uddin Shehab Department of Chemical Engineering & Polymer Science, Shahjalal University of Science & Technology, Sylhet, Bangladesh
  • Salma Akhter Department of Chemical Engineering & Polymer Science, Shahjalal University of Science & Technology, Sylhet, Bangladesh
  • Abu Yousuf School of Aerospace and Mechanical Engineering, University of Oklahoma, Norman, OK, USA

DOI:

https://doi.org/10.3329/cerb.v24i1.86734

Keywords:

Anaerobic digestion, Biomethane production, Machine learning, Municipal solid waste, Renewable energy

Abstract

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

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Published

2026-01-06

How to Cite

Murad, A. B., Ahmed, S. R., Shehab, A. U., Akhter, S., & Yousuf, A. (2026). A study on the effect of temperature and micro- nutrients in biogas production by dry anaerobic digestion of municipal solid waste. Chemical Engineering Research Bulletin, 24(1), 20–29. https://doi.org/10.3329/cerb.v24i1.86734

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