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Bioenergy is the EU's leading renewable energy source at present. Understanding bioenergy's contribution to the future EU energy mix is strategically relevant for mid to long term climate targets. This review consolidates recent projections of both supply and demand dynamics for EU bioenergy to 2050, drawing from resource-focused, demand-driven and integrated assessment approaches. Projections are synthesised to identify absolute ranges, determine cohesion with policy and draw insights on the implications for the scale of development, trade and energy security. Supply side studies have undergone methodological harmonisation efforts in recent years. Despite this, due to assumptions on key uncertainties such as feedstock yields, technical potential estimates range from 9 to 25 EJyr-1 of EU domestically available biomass for energy in 2050. Demand side projections range between 5 and 19 EJyr-1 by 2050. This range is primarily due to variations in study assumptions on key influential developments such as economic competitivity of bioenergy, EU energy efficiency gains within the power sector, flexibility for meeting mitigation targets and technological portfolios. Upper bound technical supply estimates are able meet future demand wholly from the domestic resource base, holding the potential to reduce total EU primary energy import dependency 22% points from the current EU roadmap trajectory. However, due to part of this domestic resource base being deemed economically inaccessible or of insufficient quality, interregional imports are projected to increase from current 4% to 13–76%. Emergence of non-energy applications are projected to compete for at least 10% of the biomass needed to fulfil bioenergy demand in 2050.

Acknowledgements The work of CDJ, JAL, AW was supported by the Joint UK DECC/Defra Met Office Hadley Centre Climate Programme (GA01101). CDJ, JAL, AW, PF, EK, DvV are supported by the European Union's Horizon 2020 research and innovation programme under grant agreement No 641816 (CRESCENDO). GPP was supported by the Norwegian Research Council (project 209701). PC acknowledges support from the European Research Council Synergy grant ERC-2013-SyG-610028 IMBALANCE-P. We acknowledge the World Climate Research Programme's Working Group on Coupled Modelling, which is responsible for CMIP, and we thank the climate modeling groups (listed in Table 1 of this paper) for producing and making available their model output. For CMIP the U.S. Department of Energy's Program for Climate Model Diagnosis and Intercomparison provides coordinating support and led development of software infrastructure in artnership with the Global Organization for Earth system Science Portals. ; Peer reviewed ; Publisher PDF