Assessing uncertainty cascades in energy and environmental modelling: a case for Portugal

In the SEEDS project, we used the energy system optimization framework Calliope to model 271 suboptimal
configurations 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, which
integrates Life Cycle Assessment and socio-ecosystem metabolism. In this paper, we assess the robustness of
our workflow through: (i) Spearman correlation values to address the influence of technologies in two impact
categories and (ii) Monte Carlo analysis to compare the uncertainty of Life Cycle Inventories to the option
space given by MGA. This process highlighted uncertainty hotspots related to the modelling and indicator
choices, as well as the accuracy and reliability of the technology data used. Our results highlight a range of
sensitivities 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 negative
correlations. Monte Carlo simulations show significant uncertainty in the water consumption potential of a
single energy system configuration. Transparency and open communication of uncertainty is vital in
policymaking to empower stakeholders with necessary information for informed decisions.