To explore avenues for improving the sustainability of the OP, we varied the estimates of several parameters that were identified in the sensitivity analysis. The assumption of the number of users per toilet will impact the number of toilets necessary to support populations that excreta treated by the OP (i.e., 12,000 people). In our models, this assumption will influence waste collection as well as toilet construction and operation and maintenance. To investigate the impact of the number of users per toilet on user cost and GHG emissions per user, we varied this parameter from 1 to 35 users per toilet (Figure ). At the extreme case of 1 user per toilet (i.e., all 12,000 people have their own toilet), the total user costs were 0.31 [0.25 -0.38] USD•cap -1 •d -1 for the mixed excreta and 0.41 [0.36 -0.49] USD•cap -1 •d -1 for the source-separated excreta (Figure ). These estimates of user cost drastically decrease until approximately 10 users per toilet to 0.06 [0.04 -0.07] USD•cap -1 •d -1 for the mixed excreta and 0.10 [0.08 -0.12] USD•cap -1 •d -1 for the source separated excreta. At the extreme case of 35 users per toilet, the costs for both scenarios plateaus to 0.03 [0.02 -0.04] USD•cap -1 •d -1 for the mixed excreta and 0.08 [0.07 -0.09] USD•cap - 1 •d -1 for the source-separated excreta. Similar trends were observed for the GHG emissions as a function of the number of users per toilet; however, the reduction in GHG emissions for increased number of users is not as drastic (Figure ). Specifically, at 1 user per toilet, the total GHG were 148 [124 -173] kg CO2 eq•cap -1 •yr -1 for the mixed excreta and 163 [145 -184] kg CO2 eq•cap - 1 •yr -1 for the source-separated excreta. Here, the capital intensive urine-diverting dry toilets have higher emissions than the direct emissions intensive pit latrines. While at 10 users per toilet, the total GHG were 55 [34 -81] kg CO2 eq•cap -1 •yr -1 for the mixed excreta and 23 [21 -27] kg CO2 eq•cap -1 •yr -1 for the source-separated excreta. For the mixed excreta, the already high and uncertain direct emissions from pit latrines do not efficiently scale with the number of users. On the other hand, since urine-diverting dry toilets have low direct emissions (from frequent emptying), their GHG emissions (primarily capital) can scale with the increased number of users per toilet. emissions. This analysis was performed holding all other parameters constant. The box and whisker plots show original estimates with the median values (center line), 25th and 75th percentiles (bottom and top of box), 10th and 90th percentiles (lower and upper whiskers), and 5th and 5th percentiles (points on either end of the whiskers) from the uncertainty analysis with 1,000 Monte Carlo simulations. The original assumptions for the number of users per toilet was generally 3 -35 (median of 4 people per household with a standard deviation of 1.8 and 3-5 households per toilet).