Energy generation potentials from agricultural residues: The influence of techno-spatial restrictions on biomethane, electricity, and heat production

Agricultural biogas production is subject to various spatial restrictions including legislation, biomass availability, transport, and the distribution of final energy products. This study introduces a geographic information system (GIS)-based approach for a comprehensive techno-spatial assessment of the above-mentioned factors, which was tested for Switzerland. First, spatial criteria were identified based on an extensive literature review that was complemented by expert knowledge. Then, quantitative GIS-based methods were developed to identify suitable areas for biogas production. Finally, a location- allocation algorithm was used to estimate national production potentials of biogas, electricity, heat, and biomethane and to assess the relevance of greenhouse gas (GHG) emissions from biomass transport. Maximum production potentials for electricity, heat, and biomethane were found to be in the order of 6.3, 8.5, and 13.8 PJ per year, respectively. Heat utilization and biomethane injection are often limited to areas in proximity of settlements. Furthermore, biogas production potentials varied depending on legal, economic, and technological factors. Particularly the utilization of excess heat from combined heat and power (CHP) plants was found to react very sensitive to altering spatial constraints due to its dependency on local demand. Resulting emissions from biomass transport were in the order of 0.5-0.8 kgCO2-eq per gigajoule of produced biogas, which is negligible compared to benefits from agricultural biogas production. The modeling results therefore suggest that attention should rather be concentrated on biomass utilization, plant efficiency, and optimal energy utilization when aiming to optimize GHG efficiency. Overall, the findings support the strategic planning of practitioners and authorities for the future development of agricultural biogas pro-duction. Moreover, the presented methodology can be transferred to different spatial and technological contexts.