Tryptophan-like fluorescence as a fingerprint of dry-weather misconnections into storm drainage system
Hailong Yin, Yue Wang, Yang Yang, Jingshui Huang, Zuxin Xu
Abstract
Abstract Background Inappropriate dry-weather misconnections into storm drainage system are a demanding environmental problem worldwide, which leads to unexpected dry-weather discharge into surface waters. It often costs a large amount of manpower and resources to identify the source of misconnections and estimate its contributions. In this study, we evaluated the possibility of quantifying proportional source contribution in a storm drainage system with dry-weather misconnections from domestic sewage and river water inflow, using rapid and low-cost fluorescence spectroscopy methods. For this purpose, samples of both misconnection sources and outflows of storm drainage system were collected and analyzed in a downtown catchment of Shanghai, China. Results Results showed that fluorescent peak intensity of tryptophan-like T 1 in domestic sewage (802 ± 126 a.u.) was significantly higher than that in urban river water (57 ± 12 a.u.), while fluorescent peak intensities of tryptophan-like T 2 in urban river water (732 ± 304 a.u.) was much higher than that in domestic sewage (261 ± 64 a.u.) due to increased algal activity in the local river and upstream inflow chemistry. However, only peak T 2 passed the conservative behavior test in the incubation experiments, which could be used as a fingerprint for quantitatively identifying the misconnections. We further developed a Bayesian fluorescence mass balance model (FMBM) to infer the percentage of dry-weather misconnections into the storm drainage system as a function of fluorescence intensities of peak T 2 in the samples of sources and outflow. It was found that the maximum posteriori probability estimate of the percentage of river water intrusion into the storm drains was up to 20.8% in this site, which was validated by the results of on-site investigation. Conclusion Our findings implied that in situ fluorescent sensors and Bayesian FMBM for the fingerprint fluorescence peak could be applied to fast track inappropriate dry-weather misconnections into storm drainage system qualitatively and quantitatively with low costs.