Leow Aaron, Burkhardt Jonathan, Platten William E, Zimmerman Brian, Brinkman Nichole E, Turner Anne, Murray Regan, Sorial George, Garland Jay
University of Cincinnati, Department of Biomedical, Chemical, and Environmental Engineering, 2901 Woodside Drive, Cincinnati, OH 45221, USA.
National Homeland Security Research Center, United States Environmental Protection Agency, 26 W. Martin Luther King Dr., Cincinnati, OH 45268, USA.
Environ Sci (Camb). 2017;3(2):224-234. doi: 10.1039/C6EW00226A.
Real-time monitoring of water reuse systems ensures the production of high quality water to protect human health at the point-of-use. In this study, several online real-time sensors were utilized to monitor effluent from a wastewater fed laboratory-scale membrane bioreactor (MBR) under natural and simulated failure conditions. These simulated failures included adding reactor mixed liquor to emulate a membrane breach, and spiking MS2 bacteriophage into the reactor to create a high viral load, which might be observed during an outbreak. The CANARY event detection software was used to analyze sensor data and report changes in water quality that might be indicative of poor system behavior. During simulated failure conditions, CANARY reported 20 alarms, accurately detecting each failure. During natural operating conditions, 219 alarms were produced and 189 were attributed to known events (, system and sensor maintenance). The remaining alarms (23) during natural operating conditions were considered to have an unknown cause. However, 13 of those had signal deviations similar to known events, but could not be definitively linked to a source. The results of this study suggest that real-time monitoring in conjunction with CANARY analysis may be useful as an early warning system for monitoring the effluent of water reuse systems, and may help to quickly identify treatment malfunctions or other abnormal conditions.
对水再利用系统进行实时监测可确保生产出高质量的水,从而在使用点保护人类健康。在本研究中,使用了多个在线实时传感器,在自然条件和模拟故障条件下监测来自以废水为进水的实验室规模膜生物反应器(MBR)的出水。这些模拟故障包括添加反应器混合液以模拟膜破裂,以及向反应器中加入MS2噬菌体以产生高病毒载量,这在疫情爆发期间可能会出现。使用CANARY事件检测软件分析传感器数据,并报告可能表明系统运行不佳的水质变化。在模拟故障条件下,CANARY报告了20次警报,准确检测到了每次故障。在自然运行条件下,产生了219次警报,其中189次归因于已知事件(如系统和传感器维护)。自然运行条件下其余的警报(23次)被认为原因不明。然而,其中13次警报的信号偏差与已知事件相似,但无法明确与某个源头相关联。本研究结果表明,结合CANARY分析的实时监测可作为水再利用系统出水监测的预警系统,有助于快速识别处理故障或其他异常情况。