Assessment of the biogas potential of a small-scale biodigester using ASPEN plus simulation

The increasing demand for sustainable energy and challenges in organic waste management in developing countries necessitate optimised biogas production systems. This study aims to evaluate the biogas generation potential of small-scale anaerobic digesters using kitchen waste, with a focus on the impact of feedstock composition (carbohydrates, lipids, and proteins) on methane yield, gas quality, and environmental benefits. Using ASPEN Plus V14 process simulation, three feedstock scenarios were modelled to predict methane (CH₄), carbon dioxide (CO₂), and hydrogen sulphide (H₂S) concentrations. Results revealed methane yields ranging from 40.68% to 54.4%, with protein-rich feedstock (Scenario 3) achieving the highest CH4 output, but at the expense of elevated H2S levels (2.38%). Scenario 1 (55% carbohydrates) demonstrated a methane concentration of 50.22%, translating to annual wood fuel savings of ~ 2,450 kg per household. The findings highlight the trade-offs between biogas yield and purity, emphasising the need for co-digestion strategies, gas scrubbing, and feedstock optimisation to enhance sustainability. This study underscores the role of small-scale digesters in reducing deforestation, mitigating greenhouse gas emissions, and improving energy access in developing countries.

Authors

Institutions

Publication Details

Journal
Discover Energy
Published
2025-11-11
DOI
https://doi.org/10.1007/s43937-025-00099-z
Primary Topic
Anaerobic Digestion and Biogas Production
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Assessment of the biogas potential of a small-scale biodigester using ASPEN plus simulation

Mubarick Issahaku, Francis Kemausuor, Nana Sarfo Agyemang Derkyi
Discover Energy
Anaerobic Digestion and Biogas Production
article

Assessment of the biogas potential of a small-scale biodigester using ASPEN plus simulation

Mubarick Issahaku, Francis Kemausuor, Nana Sarfo Agyemang Derkyi
article en

Abstract

The increasing demand for sustainable energy and challenges in organic waste management in developing countries necessitate optimised biogas production systems. This study aims to evaluate the biogas generation potential of small-scale anaerobic digesters using kitchen waste, with a focus on the impact of feedstock composition (carbohydrates, lipids, and proteins) on methane yield, gas quality, and environmental benefits. Using ASPEN Plus V14 process simulation, three feedstock scenarios were modelled to predict methane (CH₄), carbon dioxide (CO₂), and hydrogen sulphide (H₂S) concentrations. Results revealed methane yields ranging from 40.68% to 54.4%, with protein-rich feedstock (Scenario 3) achieving the highest CH4 output, but at the expense of elevated H2S levels (2.38%). Scenario 1 (55% carbohydrates) demonstrated a methane concentration of 50.22%, translating to annual wood fuel savings of ~ 2,450 kg per household. The findings highlight the trade-offs between biogas yield and purity, emphasising the need for co-digestion strategies, gas scrubbing, and feedstock optimisation to enhance sustainability. This study underscores the role of small-scale digesters in reducing deforestation, mitigating greenhouse gas emissions, and improving energy access in developing countries.

Discover EnergyVol. 5(1)
Kwame Nkrumah University of Science and Technology (GH), University of Energy and Natural Resources (GH), University for Development Studies (GH)
Openalex Percentile: Top 64%
Anaerobic Digestion and Biogas Production
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.