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Optimization modeling and economics assessment on simultaneous struvite and bioelectricity production from waste nutrient solution in the microbial fuel cell
被引:0
|作者:
Sreelakshmi, C.
[1
]
Kiruthika, S.
[2
]
Jeyalakshmi, R.
[1
]
机构:
[1] SRM Inst Sci & Technol, Coll Engn & Technol, Dept Chem, Kattankulathur 603203, Tamil Nadu, India
[2] SRM Inst Sci & Technol, Coll Engn & Tehnol, Dept Chem Engn, Kattankulathur 603203, Tamil Nadu, India
关键词:
Bioelectricity;
Microbial fuel cell;
Response surface methodology;
Struvite;
Wastewater;
PRECIPITATION;
RECOVERY;
D O I:
10.1016/j.bej.2025.109705
中图分类号:
Q81 [生物工程学(生物技术)];
Q93 [微生物学];
学科分类号:
071005 ;
0836 ;
090102 ;
100705 ;
摘要:
Several Sustainable Development Goals (SDGs) emphasize community well-being and environmental health. Addressing food and energy demands while ensuring a clean environment remains a global challenge. This study investigates nutrient recovery as struvite and bioelectricity generation from nutrient-rich wastewater using a dual-chamber microbial fuel cell (MFC). Response Surface Methodology with Central Composite Design (CCD) optimized Phosphorus (P) recovery at minimal cost. Simulation parameters, including the N:P ratio, chemical oxygen demand (COD), and cathodic aeration rate, were tested. Results showed that P recovery efficiency was influenced by the N:P ratio and COD, while power density was primarily impacted by COD. Optimized conditions of N:P =1, COD = 3000 mg/L, aeration =150 mL/min achieved 90 % P recovery as magnesium ammonium phosphate hexahydrate (struvite, MgNH4PO4.6H2O) with a power density of 860 mW/m2. The estimated cost based on CCD simulations was 2.5-2.6 USD/m3within a 5 % deviation under optimal conditions of N:P = 2, COD = 3000 mg/L, aeration =150 mL/min. These findings highlight the potential of integrating MFCs into wastewater treatment plants (WTPs) for nutrient recovery, COD reduction, and bioelectricity production. This approach offers a viable solution for sustainable wastewater management but requires careful assessment of Technology Readiness Level (TRL) and System Readiness Level (SRL) for large-scale implementation.
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