Stage III. Mapping the critical pathways for technology R&D. We leveraged the uncertainty and sensitivity analyses above to identify key drivers for the economic and environmental sustainability of an encapsulated system. These driving factors are either decision variables (e.g., HRT), which can be readily optimized upon system design, or technological uncertainty (e.g., bead lifetime), which relies on technological advancement to attain desirable values. To characterize the sustainability frontier and to quantitatively delineate targets for technology R&D, the encapsulated systems were simulated across the two-dimensional space of pairs of key uncertain parameters identified above with other parameters fixed at their baseline values. For each uncertain parameter, grid samples were drawn from its defined range of uncertainty (i.e., 180 samples were evaluated for each pair of key uncertain parameters). For each sample, a bounded global optimization was performed to find the best values for decision variables (DVs) with a single objective to minimize the CI of COD removal (Eq. 2), given a very strong correlation between LC and CI had been observed for these encapsulated systems in the previous uncertainty and sensitivity analyses (Tables ).