In the SEEDS project, we used the energy system optimization framework Calliope to model 271 suboptimalconfigurations for Portugal's energy transition to 2050 with a Modelling for Generating Alternatives (MGA)perspective. The environmental impacts of these scenarios were then analyzed with the ENBIOS tool, whichintegrates Life Cycle Assessment and socio-ecosystem metabolism. In this paper, we assess the robustness ofour workflow through: (i) Spearman correlation values to address the influence of technologies in two impactcategories and (ii) Monte Carlo analysis to compare the uncertainty of Life Cycle Inventories to the optionspace given by MGA. This process highlighted uncertainty hotspots related to the modelling and indicatorchoices, as well as the accuracy and reliability of the technology data used. Our results highlight a range ofsensitivities among different energy pathways, with open-field solar electricity production, pumped hydro,and electrolysis showing high sensitivity, while wind onshore and biofuel to methane exhibit negativecorrelations. Monte Carlo simulations show significant uncertainty in the water consumption potential of asingle energy system configuration. Transparency and open communication of uncertainty is vital inpolicymaking to empower stakeholders with necessary information for informed decisions.