Locating the position of a scenario projection in solution space

Geosimulation models are used in various domains to make projections for a set of scenarios, characterizing different future story lines. An impact assessment is applied on the results hereof to compare scenario outcomes with respect to given indicators. The impact assessment, however, does not represent the complete solution space of indicator values, meaning that it is unclear how optimal the bestperforming scenario is. In this paper, we explain how the addition of an optimization approach to a scenario projection impact assessment can reduce solution-space uncertainty. This helps policy makers to place scenario results in context, by providing them with information about the relative performance and improvement potential in terms of impact indicator values. This idea is illustrated by a case study of land expansion for ethanol production in the state Goiás, Brazil, for 2030. Impact indicators production costs and greenhouse gas (GHG) emissions are first calculated for a Business as Usual scenario projection from a land use change model. Next, optimal values for these indicators are determined through optimization of the land use configuration. Projected production costs are 729 US$2014 / m ethanol, with GHG emissions of 40 kg CO2-eq / m ethanol. Locating the position of this point in solution space yields two findings. The scenario’s relative performance is particularly good in terms of emissions, given that the scenario assumes no added emission strategies. The improvement potential is 50 US$2014 / m ethanol, when keeping emissions fixed, or 250 kg CO2-eq / m ethanol, when keeping costs fixed.