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Tryptophan-like fluorescence as a fingerprint of dry-weather misconnections into storm drainage system

机译:色氨酸样荧光作为恶劣天气误读的指纹变成风暴排水系统

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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 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. 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.
机译:暴风雨系统的不适当的干天气误解是全世界苛刻的环境问题,这导致意外的干燥天气放电进入表面水域。它通常需要大量的人力和资源来确定误解的来源并估计其贡献。在这项研究中,我们评估了使用快速和低成本的荧光光谱法从国内污水和河流流入的恶劣天气误解中定量风暴排水系统中的比例源贡献的可能性。为此目的,收集了误解源和风暴排水系统流出的样本,并在中国上海市中心集群中分析。结果表明,国内污水中色氨酸样T1的荧光峰强度(802?±126 AU)明显高于城市河水(57?±12 AU),而色氨酸样T2的荧光峰值强度城市河水(732?±304 AU)远高于国内污水(261?±64 AU),因为当地河流和上游流入化学中的藻类活性增加。然而,只有峰T2通过孵化实验中的保守行为试验,这可以用作定量识别误读的指纹。我们进一步开发了一种贝叶斯荧光质量平衡模型(FMBM),以推断恶劣天气误差在雨水排水系统中的百分比,作为源极和流出样本中峰T2的荧光强度的函数。结果发现,本网站的河水侵入百分比的最大后验概要估计估计高达20.8%,由现场调查结果验证。我们的研究结果暗示,原位荧光传感器和指纹荧光峰的贝叶斯FMBM可以应用于定性和定量的快速跟踪不适当的干天气误报,以低成本。

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