System dynamics models can simulate the behaviour of non-linear environmental, economic and social systems through time. In this paper we used the FeliX model.
This model was chosen for a number of reasons. It has previously been used in academic literature to test the feasibility of bioeconomy innovations through the lens of land footprints, such as the use of microalgae as a feedstock for protein production. The model is agile and provides near-instantaneous outputs, making it suitable as a tool to aid decision-making, as it is able to quickly provide analysis based on a number of scenarios designed by the user.
One limitation of the model in its current format is that it provides only an aggregated global analysis. This makes it unsuitable currently to identify, or consider, issues of trade, social or environmental local contexts, or infrastructure that influence bioeconomy decision-making. A focus on improving the local capabilities of this model would be a useful next step.
The modelling for each innovation was conducted in three stages.
Stage 1: Estimating demand
For each innovation – alternative proteins, bioplastics and cross-laminated timber – future demand was identified for materials and products in analogous traditional sectors.
For example, for alternative proteins, the future calorie and protein demands for the population were calculated based on the global population within the analysis. For cross-laminated timber, future urban expansion was calculated based on SSP2 predictions for urban populations and additional urban space required to accommodate them. SSP2 is the ‘middle of the road’ climate story where the world follows historical trends for social, economic and technical indicators. For bioplastics, future demand was estimated based on OECD projections of plastic consumption per capita.
Stage 2: Substituting with alternative products
For each innovation, we calculated the amounts of bio-based alternatives required to meet demand. A literature review was conducted to show the feedstocks required to produce the equivalent amount of alternative proteins, bioplastics and cross-laminated timber. The market uptake was based on the parameters shown in Annex B.
Stage 3: Simulating land footprint
The total land footprint of the feedstocks required to meet biomass demand were calculated based on current agricultural yields and incorporated existing trends in productivity.
In each scenario, population and GDP followed the SSP2 pathway, but the pathways for GDP were dynamically adjusted for damage based on global warming. Across each scenario, the role of other bio-based sectors remains relatively constant. The other largest source of biomass use – bioenergy – increases its market share from 5.6 per cent in 2023 to a maximum of 8.1 per cent in 2050 in the Far-reaching Scenario.
