In addition to its central role in food security, biomass is an important resource for the raw materials and energy transition. It forms the basis for a future bioeconomy and an elementary component for limiting global warming (e.g. substitution of climate-damaging building materials, provision of biogenic carbon for chemical processes, "gap closure" in the energy system, realisation of negative emissions to compensate for unavoidable emissions). The optimal and sustainable utilisation of biomass in the various economic sectors is not necessarily market-driven, so there is a need for political action. This need will foreseeably be accelerated by the defossilisation of the construction and chemical industries and the general substitution of finite resources with biogenic resources and the move away from fossil fuels. These processes are leading to an increasing demand for biomass, while at the same time more ambitious climate and nature conservation targets are limiting its availability.

The BIOSTRAT project forms the substantive basis for the National Biomass Strategy and thus for the future biomass-related policy of the Federal Government. This includes, in particular, the quantification of available areas for biomass production and national biomass potentials as well as the current and future utilisation of biomass potentials.

The UFZ has focussed primarily on the future optimal use of biomass potential in Germany's energy system for the period 2022 to 2050. This included updating and expanding the modelling of biomass use in the energy system, taking into account future material usage requirements using the BENOPT model. The UFZ's work was based on the scenarios developed and the BenOpt model status from the SoBio project. Based on this, scenarios were agreed with the BMEL and the project partners. This included updating the data on biomass feedstock availability in the model, integrating updated policy control measures and updating other scenario parameters.

The work included:
1. implementing the parameterised scenarios in the model,
2. calculation of the scenarios,
3. validation of the output and, if necessary, troubleshooting and correction of errors,
4. graphical or tabular presentation of the results.