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 T1 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 T2 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 T2 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 T2 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.
Funder
National Natural Science Foundation of China
Publisher
Springer Science and Business Media LLC
Reference54 articles.
1. Hoes OAC, Schilperoort RPS, Luxemburg WMJ, Clemens FHL, de Giesen NC (2009) Locating illicit connections in storm water sewers using fiber-optic distributed temperature sensing. Water Res 43(20):5187–5197
2. Brown E, Caraco D, Pitt R (2004) Illicit discharge detection and elimination, a guidance manual for program development and technical assessments 378. Center for Watershed Protection, Maryland
3. Irvine K, Rossi MC, Vermette S, Bakert J, Kleinfelder K (2011) Illicit discharge detection and elimination: low cost options for source identification and trackdown in stormwater systems. Urban Water J. 8(6):379–395
4. Ellis JB, Butler D (2015) Surface water sewer misconnections in England and Wales: pollution sources and impacts. Sci Total Environ 526:98–109
5. Xu ZX, Xu J, Yin HL, Jin W, Li HZ, He Z (2019) Urban river pollution control in developing countries. Nat Sustain. 2:158–160
Cited by
22 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献