A novel socio-techno-environmental GIS approach to assess the contribution of ground-mounted photovoltaics to achieve climate neutrality in Germany

The German government’s goal of achieving climate neutrality by 2045 and increasing the use of renewable energy, particularly wind and solar power, has public support. However, the local siting of wind and solar farms is highly controversial due to land-use conflicts. We have developed a comprehensive Geographic Information System (GIS) model that integrates criteria from the literature to identify optimal locations for ground-mounted photovoltaic (GM-PV). The model is based on a holistic approach considering energy-related factors and broader environmental and climate aspects. The unique feature of the model is its integration of socio-technical and environmental criteria, including a novel approach to achieving a dual land-use climate benefit by protecting erosion-prone soils and conserving soil carbon in areas prone to organic matter decomposition and associated CO2 release. Our multi-criteria GM-PV model includes 12 restrictions and five suitability criteria representing key socio-technical, economic and environmental aspects. Scenario analysis highlights the sensitivity of Germany’s GM-PV potential to defined criteria. In Scenario 1, with minimal constraint, 14.2 % of Germany’s land is available for GM-PV, decreasing to 1.9 % in the highly constrained Scenario 12. Suitable areas (>10 ha) account for 0.4 % of Germany’s land area, which could cover 8.1 % of Germany’s electricity consumption in 2045 in the highly restricted scenario. The spatial distribution results show that the innovative approach of the model changes the preference of GM-PV locations based on factors such as solar radiation in the south and soil carbon storage in the north of Germany. The application of restriction and suitability criteria significantly reduces the potential for GM-PV in Germany but also potential pitfalls for decision-makers. The GIS model can be applied in regional context to integrate stakeholder values and generate region-specific scenarios, as criteria and thresholds can be easily adapted to regional characteristics, preferences, and concerns, including those related to agriculture, biodiversity, and social acceptance.