Downscaling of agricultural market impacts under bioeconomy development to the regional and the farm level—An example of Baden‐Wuerttemberg

Abstract

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.

Processing Miscanthus to high‐value chemicals: A techno‐economic analysis based on process simulation

“…Given a continuous supply of miscanthus and by comparing the payback period, an optimal concept size with a capacity of roughly 31.500 tons per year can be determined. As investigated by Petig et al (2019), several regions in Baden‐Württemberg can provide the required miscanthus quantities for the addressed capacity ranges within a supply distance of only a few kilometers.…”

“…By assuming a miscanthus price of 90 EUR per ton (Petig et al, 2019), the provision of feedstock has a share of 14%, as seen in Figure 5. The labor and overhead costs account for 32% of total operational expenditures and consist of direct personnel costs of 27% and indirect personnel costs of 5%.…”

“…Regarding the feedstock prices, a study on the price‐driven feedstock potential of miscanthus in Baden‐Württemberg identifies regions, even at prices of 72 EUR/ton, that could provide enough feedstock for the biorefinery to produce HMF at a price per kilogram of 2.21 EUR/kg (Petig et al, 2019). These values can only be achieved by assuming a lignin price of 600 EUR/ton.…”

Implications of large‐scale miscanthus cultivation in water protection areas: A Life Cycle Assessment with model coupling for improved policy support

“…The EFEM is a comparative static linear optimization model that can be used at farm or regional level (bottomup approach; Petig et al, 2018Petig et al, , 2019. It analyses farm management decisions and optimizes the farm organization with the aim of maximizing the total gross margin (objective function) of the farm.…”

Integrating Regionalized Socioeconomic Considerations onto Life Cycle Assessment for Evaluating Bioeconomy Value Chains: A Case Study on Hybrid Wood–Concrete Ceiling Elements

“…One key issue for the future development of the bioeconomy is establishing a knowledge basis of the socioeconomic issues associated with the implementation of bio-based technologies on a regional level [34][35][36][37]. Siebert et al [38,39] proposed considering the relative social performance of the organizations involved in the value chains associated with a production system.…”