Centre for Technology in Water and Wastewater, School of Civil and Environmental Engineering, University of Technology Sydney, Sydney, NWS 2007, Australia.
Centre for Technology in Water and Wastewater, School of Civil and Environmental Engineering, University of Technology Sydney, Sydney, NWS 2007, Australia; NTT Institute of Hi-Technology, Nguyen Tat Thanh University, Ho Chi Minh City, Viet Nam; Joint Research Centre for Protective Infrastructure Technology and Environmental Green Bioprocess, Department of Environmental and Municipal Engineering, Tianjin Chengjian University, Tianjin 300384, China.
Sci Total Environ. 2021 Nov 15;795:148755. doi: 10.1016/j.scitotenv.2021.148755. Epub 2021 Jul 1.
This study investigates the performance of microbial fuel cells (MFC) for on-line monitoring ammonium (NH-N) in municipal wastewater. A double chamber microbial fuel cell (MFC) was established in a continuous mode under different influent ammonium concentrations ranging from 5 to 40 mg L. Results indicated that excess ammonium would inhibit the activity of electrogenic bacteria in the anode chamber and consequently affect electricity production. An inversely linear relationship between concentration and voltage generation was obtained with coefficient R 0.99 and the MFC could detect up to 40 mg L of NH-N. Notably, no further decline was observed in voltage output and there was in fact a further increase in ammonia concentration (>40 mg L). The stability and high accuracy of ammonium-based MFC biosensors exposed competitive results compared to traditional analytical tools, confirming the biosensor's reliability. Furthermore, pH 7.0; R 1000 Ω and HRT of 24 h are the best possible conditions for the MFC biosensor for monitoring ammonium. The simplicity in design and operation makes the biosensor more realistic for practical application.
本研究考察了微生物燃料电池（MFC）在在线监测城市废水中氨（NH-N）方面的性能。在不同的进水氨浓度（5 至 40 mg/L）下，采用连续模式建立了双室微生物燃料电池（MFC）。结果表明，过量的氨会抑制阳极室内产电菌的活性，从而影响电能的产生。浓度与电压生成之间呈反比线性关系，相关系数 R 为 0.99，MFC 可检测高达 40 mg/L 的 NH-N。值得注意的是，电压输出没有进一步下降，实际上氨浓度（>40 mg/L）进一步增加。与传统分析工具相比，基于氨的 MFC 生物传感器具有稳定性和高精度，证实了其可靠性。此外，pH 值为 7.0、电阻 R 为 1000 Ω 和水力停留时间（HRT）为 24 h 是 MFC 生物传感器监测氨的最佳条件。该生物传感器设计和操作简单，更适用于实际应用。
