Sensor-based evaluation of a Urine Trap toilet in a shared bathroom

Abstract

Urine diversion in a No-Mix Toilet is a promising approach for sustainable fertilizers and reduction of the nutrient load for wastewater treatment; however, user adoption remains a challenge. This study evaluates the Urine Trap, a passive No-Mix toilet design based on the teapot effect, wherein the urine stream inlet is invisible to the user and therefore it does not impact the user experience for increased adoption. This study evaluated the nutrient separation performance of a Urine Trap flush toilet in a bathroom shared by women in two sites in India. Over three different testing periods, 841 uses of this squat plate were recorded in 50 days. Analytical measurements found 36 % separation efficiency for total nitrogen (TN). While effective, the Urine Trap under test by users did not yield a 70-80 % TN separation efficiency observed under engineering characterization. High temporal resolution data from sensors on waste collection tanks, the opening of the bathroom door, and cleansing water flow were used to gain insights into hygiene practices. The data showed a frequent habit of wetting the squat plate during physiological excretion, a hygienic practice that eases cleaning but degrades the teapot separation effect of the Urine Trap design. By using sensors, we demonstrate a method to non-invasively gain quantitative insights into hygiene practices to inform sanitation technologies deployment strategies for improved outcomes.

Keywords: Nitrogen pollution; Source-separation toilet; Time series analysis; Urine diversion; User testing.

Graphical abstract

Fig. 1

(A) Pictures of bathroom. (B) Schematic of the sensor-based data collection system.

Fig. 2

Data was collected in 3 periods indicated by vertical dashed lines: at site A for 14 days (period 1) and after a pause again for 20 days (period 2); site B 16 days (period 3). (A) Total Nitrogen daily values. (B) Daily volume in urine and feces tanks and number of uses. (C) Urine separation efficiency η_ΤΝ. Blue lines are average values by period from Table 1. Black horizontal line indicates ideal value η_ΤΝ ~ 86 % and red line the expected η_ΤΝ ~70 %.

Fig. 3

Histogram of duration of toilet use events for all the data (3 periods) of this study. The two Gaussian distributions from the Gaussian Mixed Model (GMM) fit represent: urination for mean duration of 61 s and defecation for mean duration 186 s. The intersection of the curves at t = 124 s is the threshold used to classify an event as defecation.

Fig. 4

Sensor data illustrating a urination event. After the user enters the bathroom, tap water starts to fill out a bucket, followed by 1.Urination 2. Cleansing 3. Bucket flush. The arrow segment in the insert indicates the volume ΔU attributed to urine.

Fig. 5

Wastewater volume over time during a toilet use as defined by door close position. Flowmeter values are shown as a.u. (A) Spray/Pour first, unclear when a physiological event occurs. (B) 1. a mug is poured, 2. urination, 3. pause attributed to defecation, 4. multiple flushes. (C) Alternative urination: liquid at physiological flow rate went mostly in the feces tank.

Fig. 6

Modeled vs predicted daily TN values for 16 days in period 3. Measured daily values TN_F (A) and TN_U (B) relative to number of subevents. (C) and (D) TN amount measured and predicted by waste stream. (E) η_TN predicted and measured by day. (F) predicted η_TN plotted against measured η_TN and linear fit.