Wet weather behavior of unregulated pollutants and pathogens in combined sewer network

本研究项目的目的是揭示混合下水道溢流(CSO)产生的未受管制的微污染物和病原体在潮湿天气中的行为。进行了详细的现场调查，以表征污染物负荷、颗粒分布、悬浮微生物、包括病毒在内的与健康有关的微生物和抗生素等微污染物的日变化特征。根据污染源的不同，日变化可分为几种类型。抗生素浓度的变化似乎反映了各种抗生素的代谢和排泄特征。为了研究潮湿天气条件下管道沉积物的再悬浮现象，通过从水车向上游沙井注入清洁水来模拟雨水径流。针对合流制排水管网中细菌负荷与病毒负荷变化规律不同的问题，通过数学模型对合流制排水管网中的泥沙分布进行了评价，并提出了优先清洗管道的划分方案。模型模拟表明，对特定积沙的管道进行清洗是降低CSO污染物负荷的有效方法，提出了以最小化CSO污染物负荷为目标的排水系统运行算法。参考上游管道的实测值，对一种简单的在线水质预测的自回归模型进行了修正。改进了水流预报模型，以更好地模拟中小尺度降雨过程中CSO的发生。讨论了该算法在CSO管理实时控制系统中的应用前景。

The aim of this research project was to unveil the wet weather behavior of unregulated micropollutants and pathogens derived from combined sewer overflow (CSO). Detailed field survey was conducted to characterize the diurnal variation of the pollutant loads, particle size distribution, quinone profile of suspended microbes, health related microorganisms including viruses and micropollutants such as antibiotics. The diurnal variation was categorized into several patterns dependent on the pollutant source. The variation of antibiotics concentration seemed to reflect the metabolism and excretion characteristics of each antibiotic.To investigate the phenomenon of resuspension of pipe sediment under wet weather condition, the rainwater runoff was simulated by pouring clean water into an upstream manhole from a water wagon. Loads of bacteria in the downstream pipe exhibited a different varying pattern from that of viruses.A mathematical modeling was conducted to evaluate the sediment distribution in a combined sewer network and then a protocol to distinguish the priority pipes for cleaning was proposed. A model simulation revealed that cleaning of pipes which specifically accumulated sediments was effective for reducing the CSO pollutant load.Algorithm of sewer system operation to minimize the CSO pollutant load was developed. A simple auto-regression model for on-line water quality prediction was modified with referring a measured water quality value in an upstream pipe. Water flow prediction model was refined to provide a better simulation of CSO occurrence at medium- and small-size rainfall events. Future application of the algorithm to a real time control system for CSO management was discussed.