Integral model of a reacting chlorine jet in ammonia nitrogen and treated primary effluent

Abstract

Chlorine is extensively used in disinfection processes in water and wastewater treatment processes. The chlorine is typically dosed by jet mixing, and yet no systematic study of chlorine jets has been conducted. In the Stonecutters Island Sewage Treatment Works (SCISTW) of the Hong Kong Harbour Area Treatment Scheme (HATS), concentrated chlorine solution (in sodium hypochlorite form) is injected into primary treated effluent in the form of turbulent dense jets. In view of the importance of sewage disinfection to the environmental impact, it is essential to understand the mixing and reaction of chlorine with ammonia nitrogen for disinfection dosage optimization. In this study, an integral buoyant jet model is developed for a chlorine jet reacting with ammonia nitrogen in CEPT sewage. The jet mixing and chlorine demand is studied by accounting for the stoichiometric reaction of chlorine and ammonia including breakpoint chlorination. Based on experiments of chlorine jet in ammonia solution, the stoichiometric mass ratio of chlorine to ammonia under dynamic mixing process is found to be 7.48. The chlorination kinetics model is then incorporated in a general model of a chlorine jet discharging into a coflowing primary treated sewage effluent, with the reaction ratio calibrated based on experimental measurements for the stagnant case. Significant chlorine demand can occur within a short distance (in the order of 0.1 m, or 1 s or less of travel time) from the dosing point due to the turbulent mixing and reaction with ammonia nitrogen and organic impurities. The chlorine demand of CEPT effluent increases with jet dosing total residual chlorine (TRC) concentration. At TRC < 2000 mg/L, the chlorine demand of sewage is mainly due to ammonia nitrogen (>60%), while for TRC ≫ 2000 mg/L, up to two thirds of chlorine demand can be induced by the oxidation of organic debris. Model predictions of chlorine demand and concentration agree well with laboratory experiments and field data.