This paper explores the stochastic properties of human urine production in order to assess the potential of combining urine separation with waste design. The aim is to provide specific information about the dynamics of urine production at a microscopic level for the design and the control of the urine waste stream. Based on measured data a stochastic model is developed that is capable of providing stochastic information on the frequency, timing, and volume of urine releases into each single toilet in a catchment. It is then demonstrated in a virtual case study that the design of the human wastewater stream in terms of urine content can (1) reduce the ammonia peak loads at dry weather flow conditions by approx. 30% (which could effectively substitute the expansion of wastewater treatment plants) and (2) reduce the impact of combined sewer overflows on the aquatic environment. With respect to the latter a reduction of more than 50% is demonstrated in terms of annual urine volume released via the overflow.
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