Modeling of Mixing and Rapid Chlorine Demand in Sewage Disinfection with Dense Chlorine Jets
AbstractA concentrated 10% chlorine solution (in sodium hypochlorite) with a specific gravity of 1.2 is used for the disinfection of treated primary effluent in the Stonecutters Island Sewage Treatment Works (SCISTW) in Hong Kong. The chlorine solution is injected in the form of coflowing dense jets...
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Veröffentlicht in: | Journal of environmental engineering (New York, N.Y.) N.Y.), 2017-11, Vol.143 (11) |
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Sprache: | eng |
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Zusammenfassung: | AbstractA concentrated 10% chlorine solution (in sodium hypochlorite) with a specific gravity of 1.2 is used for the disinfection of treated primary effluent in the Stonecutters Island Sewage Treatment Works (SCISTW) in Hong Kong. The chlorine solution is injected in the form of coflowing dense jets into a sewage flow of approximately 1.4 million m3/day, with a target dosing rate of 10–20 mg/L (or an initial dilution of 5,000 to 10,000). The large sewage flow to chlorine dosing flow ratio has resulted in insufficient mixing and high chlorine demand as a result of the fast reaction of chlorine with organic and inorganic substances in the sewage. An integral jet model is developed to predict the jet mixing in the initial contact region of chlorine and sewage, accounting for chemical kinetics of the chlorine–sewage reaction. The model is calibrated using field data obtained from experiments using real sewage and chlorine solution in a field-scale physical model inside the sewage treatment works. The mathematical model is used to guide experimentation of various alternatives to reduce the chlorine demand. It is found that under the same chlorine dosage, diluting the concentrated chlorine solution by four times (i.e., containing 2.5% available chlorine) and doubling the number of injection jets can result in the reduction of chlorine demand by 10–15%. The chlorine dosage optimization was supported by extensive field measurements and three-dimensional (3D) computational fluid dynamics (CFD) simulations. |
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ISSN: | 0733-9372 1943-7870 |
DOI: | 10.1061/(ASCE)EE.1943-7870.0001274 |