摘要
生化需氧量（biochemical oxygen demand,BOD）是表征有机物污染程度的综合性指标,传统的检测方法为5 d 20℃培养法,费时费力,不宜现场实时监测.以MnO2代替金属铂作阴极催化剂、以阳离子交换膜代替昂贵的质子交换膜,构建单室微生物燃料电池（microbial fuel cell）型BOD传感器,考察外接电阻、阳极液pH值、检测时间和清洗时间对检测效果的影响,并用该传感器检测实际水样BOD值,与传统BOD5值进行比较.结果表明：①以廉价MnO2为阴极催化剂,阳离子交换膜为隔膜,构建的单室MFC型BOD传感器成本低,结构简单,操作方便,可用于BOD的在线检测;②该BOD传感器的适宜运行条件为样品pH7.0,外接电阻12 kΩ,检测时间2 h,清洗时间2～10 min;③实际水样检测结果显示,传感器最低检出限为0.2 mg/L,测量线性范围为BOD浓度5～50 mg/L,最佳测定范围为BOD浓度20～40 mg/L,精确度为0.33%,标准曲线线性相关系数达0.999 2,与BOD5比较,相对误差在4.0%以内.
The 5-d biochemical oxygen demand（BOD5） test is the most conventional method to determine the concentration of biodegradable organics in wastewater.However,this method is time-consuming and usually requires experience and skill to produce creditable results,which is also not suitable for on-line measurements.This study described a single-chamber mediator-less microbial fuel cell（MFC）-type BOD sensor as an alternative method to BOD5.In such MFC,MnO2 was used as the cathode catalyst instead of Pt and the expensive proton exchange membrane was replaced with the cation exchange membrane.The factors including the external resistance,pH of anolyte,the reaction time and rinse time on BOD sensor were explored,and the results were compared with the values determined by BOD5.The experimental results showed that the optimal conditions are： the external resistance of 12 kΩ,pH of 7.0,and the reaction period of 2 h and the rinse time of 2-10 min.The low detection limit is 0.2（mg/L） and the precsion is 0.33%.This study indicates that MFC-type sensor can be used as a reliable method to determine BOD in wastewater,supported by the good linear correlation between BOD concentration and coulombs generation（regression coefficient,R^2=0.9992） and the small relative error of 4% between MFC-type sensor and BOD5.Such device provides a low-cost,easy-operated,fast-response,sensitive and reliable method to measure BOD in wastewater,and also is suitable for on-line measurements.
出处
《环境科学》
EI
CAS
CSCD
北大核心
2009年第10期3099-3103,共5页
Environmental Science
基金
国家自然科学基金项目(20777013)
广东省自然科学基金项目(07006759)
广东省科学院科技创新引导项目(CX200704)
