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Abstract
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.