亚硝酸盐
化学
检出限
氧化剂
电化学
生物膜
电化学气体传感器
无机化学
电极
色谱法
细菌
硝酸盐
有机化学
生物
遗传学
物理化学
作者
Xiaoyun Li,Xu Yang,Mengyao Cui,Yiliang Liu,Jingting Wang,Lixia Zhang,Guoqiang Zhan
标识
DOI:10.1016/j.scitotenv.2022.154178
摘要
Real-time nitrite control in water is necessary for environmental safety and human health, and has triggered the research and development of novel detection methods. Previous studies have made great progress on enzyme-free and enzyme electrochemical sensors. However, enzyme-free sensors have low selectivity and a complex preparation process, and enzyme sensors have short lifetimes, and these issues need to be addressed. In this work, we proposed for the first time a highly specific and sensitive biofilm sensor based on nitrite-oxidizing bacteria (NOB) for the bio-electrochemical detection of nitrite in water. The mechanism of nitrite detection was attributed to the competition of oxygen between aerobic respiration of the NOB and the cathode oxygen reduction on the carbon felt electrode, resulting in a decrease in current. This decrease in current (ΔI) had a linear relationship with the nitrite concentration in the range of 0.1 to 1 mg L-1 and 1 to 10 mg L-1, which was corresponding to the sensitivities of 48.62 and 2.24 μA mM-1 cm-2, respectively. And the limit of detection (LOD) was calculated to be 0.033 mg L-1 (2.39 μM) with a signal-to-noise ratio of 3. Moreover, several common interfering ions had no effect on the nitrite detection owing to the functional microbial species (NOB) and weakly electrochemical behavior of electrode at the low potential of -0.1 V, showing high specificity for nitrite detection of biofilm sensor. Therefore, the actual nitrified wastewater was well detected by the biofilm sensor. In addition, allylthiourea (ATU) took good effect on the resistance of the influence of ammonia oxidizing bacteria (AOB) in the biofilm sensor, maintaining the high selectivity of biofilm sensor in case the biofilm sensor was fouled with AOB. The biofilm sensor in our work showed good selectivity, sensitivity and stability in long-term detection.
科研通智能强力驱动
Strongly Powered by AbleSci AI