Because the performance of the NSS systems has been shown to vary dramatically depending on the implementation context, a sensitivity analysis was conducted to reveal which contextual parameters influenced the outcomes of cost and CI scores across all six systems and 77 countries. The uncertainty analysis used for assessing sensitivity included applying uncertainty to 16 contextual parameters while setting the remaining technological parameters constant. This approach allowed for a clear understanding of the impact of contextual parameters without the influence of design/operational decisions and technological parameters . Of the 16 contextual parameters, liquefied petroleum gas (LPG) price and CRT labor wage were only included in the NEWgenerator and Reclaimer scenarios, and OP wages (six labor wage types) and household size were only included for the Biogenic Refinery scenarios. The remaining seven contextual parameters were included in all six NSS systems. For each NSS scenario and country combination (462 combinations from six systems and 77 countries), 1,000 Monte Carlo simulations with Latin Hypercube Sampling were performed to vary the contextual parameters across defined distributions. Spearman's rank order correlation coefficients were calculated to characterize the sensitivity of per capita daily cost and CI scores to contextual parameter uncertainties. A correlation coefficient was calculated for each country evaluated (i.e., 77 correlation coefficients calculated for a single input and output pair within a NSS system), and correlation coefficients across countries were compiled and plotted to identify generalizable trends (Figure ).