Abstract
Dewatered sludge is redundantly found in a municipal wastewater treatment plant, and the amount is increasing every year. However, the dewatered sludge could be used to power the membrane-less microbial fuel cell (ML-MFC), which is operated electrochemically via incorporation of electricity producing micro-organisms. The dewatered sludge normally acts as an electron donating substrate. Results showed that the ML-MFC produced voltage at about 927.7 ± 11.24 mV whereby 178.7 mg/L of chemical oxygen demand (COD) was removed after 240 h of incubation period. Nonetheless, voltage and COD removal values obtained from the dewatered sludge in the ML-MFC might differ every time the study is repeated because the availability of maximum biomass of electrogenic bacteria (EB) will be different due to the heterogeneous properties and EB performance inside the ML-MFC. The parametric uncertainty analysis of COD removal was then assessed using Monte Carlo simulation (stochastic variable) to determine the distribution probability affected by the fluctuation and variation of kinetic model parameters. From the study of 100 000 samples tested (simulation), the results show that the substrate removal (S) value ranged from 172.58 to 185.02 mg/L. The impact of each kinetic parameter on the ML-MFC performance was evaluated via sensitivity analysis. It is found that the ML-MFC performance significantly relied on the growth of EB present.
Highlights
The lack of access to clean electricity in developing nations has given importance to the development of low-cost, widely applicable energy technologies
Results showed that the membrane-less microbial fuel cell (ML-microbial fuel cells (MFCs)) produced voltage at about 927.7 ± 11.24 mV whereby 178.7 mg/L of chemical oxygen demand (COD) was removed after 240 h of incubation period
Voltage and COD removal values obtained from the dewatered sludge in the ML-MFC might differ every time the study is repeated because the availability of maximum biomass of electrogenic bacteria (EB) will be different due to the heterogeneous properties and EB performance inside the ML-MFC
Summary
The lack of access to clean electricity in developing nations has given importance to the development of low-cost, widely applicable energy technologies. As reported by Jollands, about 1.4 × 109 people around the world had no access to electricity, of which 2.7 × 106 of them depended on the traditional method of using biomass.[1] Most of these people originated from rural areas. It was predicted that this problem would continue to increase steadily until 2030. SubSaharan Africa continues to face the biggest challenge in terms of electricity access where only 31% of the population have an electricity source, and this is the lowest level recorded in the world.[3].
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