2006 Fiscal Year Final Research Report Summary
Wet weather behavior of unregulated pollutants and pathogens in combined sewer network
| Project/Area Number |
16360262
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| Research Category |
Grant-in-Aid for Scientific Research (B)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Civil and environmental engineering
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| Research Institution | the University of Tokyo |
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Principal Investigator |
FURUMAI Hiroaki The University of Tokyo, School of Enging, Professor, 大学院工学系研究科, 教授 (40173546)
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| Co-Investigator(Kenkyū-buntansha) |
NAKAJIMA Fumiyuki The University of Tokyo, Environmental Science Center, Associate Professor, 環境安全研究センター, 助教授 (30292890)
KATAYAMA Hiroyuki The University of Tokyo, School of Engineering, Lecturer, 大学院工学研究科, 講師 (00302779)
FUJITA Masafumi University of Yamanashi, Interdiscriplinary Graduate School of Medical and Engineering, Research Associate, 大学院医学工学総合研究部, 助手 (60362084)
KURISU Futoshi The University of Tokyo, School of Engineering, Lecturer, 大学院工学研究科, 講師 (30312979)
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| Project Period (FY) |
2004 – 2006
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| Keywords | Combined Sewer Overflow / Pipe Sediment / Pathogens / Virus / Distributed Model / Antibiotics / Quinone profile / Pollutant Runoff Analysis |
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| Research Abstract |
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.
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Research Products
(32 results)
