Department of Civil, Construction, and Environmental Engineering, San Diego State University, 5500 Campanile Drive, San Diego, CA 92182, United States of America; Department of Civil and Environmental Engineering, Stanford University, 450 Serra Mall, Stanford, CA 94305, United States of America.
Department of Civil, Construction, and Environmental Engineering, San Diego State University, 5500 Campanile Drive, San Diego, CA 92182, United States of America.
Sci Total Environ. 2020 May 20;718:137206. doi: 10.1016/j.scitotenv.2020.137206. Epub 2020 Feb 8.
Fluorescence spectroscopy has been increasingly used to detect sewage and other anthropogenic contaminants in surface waters. Despite progress in successfully detecting bacterial and sewage inputs to rivers over diverse spatial scales, the use of fluorescence-based in-situ sensors to track contaminant inputs during storm events and to discern bacterial contamination from background natural organic matter (NOM) fluorescence have received less attention. A portable, submersible fluorometer equipped with tryptophan (TRP)-like and humic-like fluorescence sensors was used to track inputs of untreated wastewater added to natural creek water in a laboratory sewage spill simulation. Significant, positive correlations were observed between TRP fluorescence, the TRP:humic ratio, percent wastewater, and Escherichia coli concentrations, indicating that both the TRP sensor and the TRP:humic ratio tracked wastewater inputs against the background creek water DOM fluorescence. The portable fluorometer was subsequently deployed in an urban creek during a storm in 2018. The peak in TRP fluorescence was found to increase with the rising limb of the hydrograph and followed similar temporal dynamics to that of caffeine and fecal indicator bacteria, which are chemical and biological markers of potential fecal pollution. Results from this study demonstrate that tracking of TRP fluorescence intensity and TRP:humic ratios, with turbidity correction of sensor outputs, may be an appropriate warning tool for rapid monitoring of sewage or other bacterial inputs to aquatic environments.
荧光光谱学已被越来越多地用于检测地表水的污水和其他人为污染物。尽管在不同的空间尺度上成功检测到河流中细菌和污水的输入方面取得了进展，但荧光原位传感器在跟踪风暴事件中的污染物输入以及辨别细菌污染与背景天然有机物（NOM）荧光方面的应用却受到较少关注。本研究使用配备色氨酸（TRP）样和腐殖质样荧光传感器的便携式潜水式荧光计，追踪添加到天然溪水中未经处理的污水输入，以模拟实验室污水溢出。TRP 荧光、TRP：腐殖质比、污水百分比和大肠杆菌浓度之间存在显著的正相关关系，表明 TRP 传感器和 TRP：腐殖质比均能追踪污水输入，以抵消背景溪流水体 DOM 荧光。随后，便携式荧光计在 2018 年的一场城市暴雨中部署在一条城市溪中。TRP 荧光的峰值随流量图的上升支而增加，并与咖啡因和粪便指示菌的时间动态相似，咖啡因和粪便指示菌是潜在粪便污染的化学和生物标志物。本研究的结果表明，跟踪 TRP 荧光强度和 TRP：腐殖质比，并对传感器输出进行浊度校正，可能是快速监测污水或其他细菌输入水生环境的一种合适的预警工具。
