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

本研究的目的是揭示污水合流溢流（CSO）中不受管制的微污染物和病原体在潮湿天气中的行为。通过详细的野外调查，研究了污染物负荷、悬浮微生物的粒径分布、醌谱、病毒等健康相关微生物和抗生素等微污染物的日变化特征。根据不同的污染源，日变化可分为几种模式。抗生素浓度的变化似乎反映了每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，采用从运水车向上游人孔注入清水的方法模拟了雨水径流。下游管道中的细菌负荷表现出与病毒不同的变化模式。建立了综合污水管网泥沙分布的数学模型，并在此基础上提出了一种区分优先清洗管道的方案。模型模拟结果表明，对积聚沉积物的管道进行清洗可有效降低CSO污染物负荷。提出了以CSO污染物负荷最小为目标的排污系统运行算法。参考上游管道的水质测量值，对在线水质预测的简单自回归模型进行了修正。对水流预测模型进行了改进，以更好地模拟中小尺度降雨事件中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.