This study aims at identifying underutilized land potentially suitable for bioenergy production in Europe by means of remote sensing time series analysis. The background is the Revised Renewable Energy Directive (REDII) requesting that 32% of Europe’s energy production shall come from renewable energy sources until 2030. In order to avoid the food versus fuel debate, we only considered land that has not been used in the previous five years. Satellite remote sensing is the only technique that allows for the assessment of the usage of land for such a long time span at the pan-European scale with reasonable efforts. We used Landsat 8 (L8) data for the full five year time period 2015–2019 and included additional Sentinel-2 (S2) data for 2018 and 2019. The analysis was based on a stratified approach for biogeographical regions and countries using Google Earth Engine. To our knowledge, this is the first work that employs high resolution time series data for pan-European mapping of underutilized land. The average patch size of underutilized land was found to be between 23.2 ha and 49.6 ha, depending on the biogeographical region. The results show an overall accuracy of more than 85% with a confidence interval (CI) of 1.55% at the 95% confidence level (CL). The classification suggests that at total of 5.3 million ha of underutilized land in Europe is potentially available for agricultural bioenergy production.

Extensive surfaces of land are currently under-utilized, marginal and/or contaminated (MUC) in many EU and neighbouring countries. In the past few years, scientific research has demonstrated that bioenergy crops can potentially render this land profitable, generating income for the local populations and, at the same time, reaching the goals of the new Renewable Energy Directive (REDII) without interfering with food production. The main purpose of this paper is to measure net economic returns by computing benefits and costs of low indirect Land Use Change (iLUC) biofuel production on MUC land from the perspective of both the private investors and social welfare. A standard cost-benefit technique was applied to analyse and compare net returns of different advanced bioenergy value-chains in monetary terms. Productivity, economic feasibility and green-house gas (GHG) emissions impact were assessed and considered for the economic analysis. The considered pathways were cellulosic or second generation (2G) ethanol from Giant reed (Arundo donax) in Italy, electricity from miscanthus, biochemicals from spontaneous grass and cultivated Lucerne (Alpha-alfae) with sorghum for biomethane in Germany, and 2G ethanol from Willow (Salix viminalis) in Ukraine. For the risk assessment, Monte Carlo simulation was applied. The results indicated that in Italy and Ukraine, although the production of 2G ethanol would allow positive net yearly margins, the investments will not be profitable compared to the baseline scenarios. In Germany, the work showed good profitability for combined heat and power (CHP) and biochemicals. On the other hand, investments in biomethane showed negative results compared with the baseline scenarios. Finally, the Monte Carlo simulation enabled us to identify the range of possible economic results that could be attained once volatility is factored in. While for Italy the likelihood of yielding positive results remains lower than 20 percent, case studies in Ukraine and Germany showed higher certainty levels, ranging from 49 to 91 percent.