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Biogas is in many respects a serious alternative to other fossil resources and complements other renewable energy sources from wind and sun. Biogas can be produced in many places decentrally. Its energy potential is high, and it is widely used in the EU and all over the world. With more than 16,000 ktoe of oil equivalent in the EU in 2016, it corresponds to approximately 8% of the total primary energy produced by renewable energies in the EU, produced with nearly 17,000 biogas plants. Nevertheless, the production costs of biogas and its products like energy, heat, and fuel are still too high. Kost et al. (2018) show a comparison of electricity generation costs of different renewable energies and their future potentials. While electricity from huge biogas plants offers generation costs from 10 to 15 ct/kWh, electricity from onshore wind and huge solar systems offers generation costs from 4 to 8 ct/kWh. Although substantial progress has been made with regard to substrate use, production techniques and market designs, many more innovations are needed throughout the biogas value chain for it to be competitive in energy markets without high subsidies. As several papers in the special issue on biogas show, there are numerous innovations and product designs with regard to energy and material uses that could maintain or even increase the importance of biogas production both within and outside of the EU. There are many potential benefits of biogas, as it offers high shares of produced renewable energies as well as large amounts of material products like digestates and in future maybe products of higher value such as proteins or lactic acids.

Diminishing fossil carbon resources, global warming, and increasing material and energy needs urge for the rapid development of a bioeconomy. Biomass feedstock from agro‐industrial value chains provides opportunities for energy and material production, potentially leading to competition with traditional food and feed production. Simulation and optimization models can support the evaluation of biomass value chains and identify bioeconomy development paths, potentials, opportunities, and risks. This study presents the linkage of a farm model (EFEM) and a techno‐economic location optimization model (BIOLOCATE) for evaluating the straw‐to‐energy and the innovative straw‐to‐chemical value chains in the German federal state of Baden‐Wuerttemberg taking into account the spatially distributed and price‐sensitive nature of straw supply. The general results reveal the basic trade‐off between economies of scale of the energy production plants and the biorefineries on the one hand and the feedstock supply costs on the other hand. The results of the farm model highlight the competition for land between traditional agricultural biomass utilization such as food and feed and innovative biomass‐to‐energy and biomass‐to‐chemical value chains. Additionally, farm‐modeling scenarios illustrate the effect of farm specialization and regional differences on straw supply for biomass value chains as well as the effect of high straw prices on crop choices. The technological modeling results show that straw combustion could cover approximately 2% of Baden‐Wuerttemberg's gross electricity consumption and approximately 35% of the district heating consumption. The lignocellulose biorefinery location and size are affected by the price sensitivity of the straw supply and are only profitable for high output prices of organosolv lignin. The location optimization results illustrate that economic and political framework conditions affect the regional distribution of biomass straw conversion plants, thus favoring decentralized value chain structures in contrast to technological economies of scale.

The strategy of using biogenic resources in a bioeconomy could be seen as one answer to the geopolitical challenges the world is facing in the twenty-first century. One of those challenges is the closing of the prosperity gap between rich and poor countries. However, considering the current global population growth and anthropogenically induced climate change, it is expected that efforts to achieve this goal will be accompanied by an increasing demand for food, feed, products, and energy, which cannot be satisfied by the expected supply of non-biogenic raw materials and resources.Transforming an economy is extremely complex: domestic and international obligations, traditional practices, and divergent interests and wishes need to be taken into consideration. This requires the development of an appropriate strategy and adequate instruments and tools to support it.This chapter discusses a range of possible knowledge-based instruments and tools that take a systemic view of the challenges in such transformation processes. Keywords Scenarios • Scenario building • Economic models • Ecological and biophysical models • Life cycle assessment • Integrated assessment models Learning ObjectivesAfter studying this chapter, you should:• Understand how transformation theory can support transition processes.• Have an overview of main instruments and tools to quantify and assess transition developments.• Be acquainted with the main challenges, strategies and drivers to facilitate the transition to a bioeconomy.

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The expansion of the bioeconomy sector will increase the competition for agricultural land regarding biomass production. Furthermore, the particular path of the expansion of the bioeconomy is associated with great uncertainty due to the early stage of technology development and its dependency on political framework conditions. Economic models are suitable tools to identify trade‐offs in agricultural production and address the high uncertainty of the bioeconomy expansion. We present results from the farm model Economic Farm Emission Model of four bioeconomy scenarios in order to evaluate impacts and trade‐offs of different potential bioeconomy developments and the corresponding uncertainty at regional and farm level in Baden‐Wuerttemberg, Germany. The demand‐side effects of the bioeconomy scenarios are based on downscaling European Union level results of a separate model linkage between an agricultural sector and an energy sector model. The general model results show that the expanded use of agricultural land for the bioeconomy sector, especially for the cultivation of perennial biomass crops (PBC), reduces biomass production for established value chains, especially for food and feed. The results also show differences between regions and farm types in Baden‐Wuerttemberg. Fertile arable regions and arable farms profit more from the expanded use of biomass in the bioeconomy than farms that focus on cattle farming. Latter farms use the arable land to produce feed for the cattle, whereas arable farms can expand feedstock production for new value chains. Additionally, less intensive production systems like extensive grassland suffer from economic losses, whereas the competition in fertile regions further increases. Hence, if the extensive production systems are to be preserved, appropriate subsidies must be provided. This emphasizes the relevance of downscaling aggregated model results to higher spatial resolution, even as far as to the decision maker (farm), to identify possible contradicting effects of the bioeconomy as well as policy implications.