Additionally, the daily per capita cost of the baseline Reclaimer relying on grid electricity was sensitive to the grid electricity price due to its high electricity consumption compared to the other systems (i.e., median electricity demands of 0.408 kWh•capita -1 •day -1 to operate the Reclaimer vs. 0.131 kWh•capita -1 •day -1 to operate the NEWgenerator and 0.008 kWh•capita -1 •day -1 to operate the Biogenic Refinery). The annual per capita CI scores were most sensitive to national diet and grid electricity carbon intensity. Systems with high direct emissions were highly sensitive to caloric intake (all NSS scenarios besides the alternative Biogenic Refinery treating excreta from UDDTs) where higher caloric intake results in a more energy-rich (measured as chemical oxygen demand, COD) excreta stream to be converted to direct emissions. The Biogenic Refinery scenario treating source-separated excreta from UDDTs has relatively low direct fugitive emissions due to its higher emptying frequency and is more sensitive to the vegetal and animal protein intake. Protein intake is directly related to the excreta stream nutrient content, with higher nutrient concentrations requiring greater chemical input requirements to meet treatment standards. Overall, NSS technology developers can better improve sustainability performance estimates by gathering locality-specific estimates for the key contextual parameters driving uncertainty. Effect of Contextual Drivers on Sustainability Performance. The effect of contextual drivers on daily per capita cost and annual CI scores was explored for the six NSS systems to highlight the impact location-specific variations have on NSS sustainability. The results of the sensitivity analysis were used to select four contextual drivers (two driving the uncertainty in cost and two driving the uncertainty in emissions) to vary for the analysis. Grid electricity price, labor wage, and price level ratio had high Spearman's rank correlation coefficients with respect to daily per capita cost for at least one NSS system. Although daily per capita cost was highly sensitive to the price level ratio for all six systems, it was not analyzed further because it is not a parameter that could be adjusted by sanitation developers due to its reliance on market exchange rates and purchasing power of the implementation country. Although, sanitation developers have little control over the electricity price and market labor rates in their implementation context, they are expected to have greater subnational variability and could be influenced by design and operational modifications (e.g., shifting electricity demand to off-peak hours at a reduced unit charge). Because baseline NSS systems demonstrated greater sensitivity to these parameters (relative to alternative systems; Figure ), the effect of labor wage and grid electricity price variations on daily per capita cost was explored using the baseline NSS systems (Figure ).