Diversity of biomass usage pathways to achieve emissions targets in the European energy systemShow others and affiliations
2025 (English)In: Nature Energy, E-ISSN 2058-7546, Vol. 10, no 2, p. 226-242Article in journal (Refereed) Published
Abstract [en]
Biomass is a versatile renewable energy source with applications across the energy system, but it is a limited resource and its usage needs prioritization. We use a sector-coupled European energy system model to explore near-optimal solutions for achieving emissions targets. We find that provision of biogenic carbon has higher value than bioenergy provision. Energy system costs increase by 20% if biomass is excluded at a net-negative (−110%) emissions target and by 14% at a net-zero target. Dispatchable bioelectricity covering 1% of total electricity generation strengthens supply reliability. Otherwise, it is not crucial in which sector biomass is used, if combined with carbon capture to enable negative emissions and feedstock for e-fuel production. A shortage of renewable electricity or hydrogen supply primarily increases the value of using biomass for fuel production. Results are sensitive to upstream emissions of biomass, carbon sequestration capacity and costs of direct air capture.
Place, publisher, year, edition, pages
Nature Research , 2025. Vol. 10, no 2, p. 226-242
Keywords [en]
Carbon capture and utilization; Direct air capture; Low emission; Bio-energy; Biogenics; Emission targets; Energy systems; Energy-system models; Fuel production; Near-optimal solutions; Prioritization; Renewable energy source; System costs; Carbon sequestration
National Category
Environmental Engineering
Identifiers
URN: urn:nbn:se:ri:diva-78037DOI: 10.1038/s41560-024-01693-6Scopus ID: 2-s2.0-85217252118OAI: oai:DiVA.org:ri-78037DiVA, id: diva2:1950444
Note
We acknowledge funding from the Swedish Energy Agency, project numbers 2021-00067 (M.M., F.H., L.R.), 2023-00888 (RESILIENT, M.M.) and 2020-004542 (M.M., F.H., L.R.). This research was partially funded by CETPartnership, the Clean Energy Transition Partnership under the 2022 joint call for research proposals, co-funded by the European Commission (grant agreement number 101069750). This research was partially funded by the European Union’s Horizon Europe esearch and innovation programme under the UPTAKE project (g.a. no. 101081521). The views and opinions expressed are, however, those of the author(s) only and do not necessarily reflect those of the European Union or CINEA. The computations and data handling were enabled by resources provided by the National Academic Infrastructure for Supercomputing in Sweden (NAISS) and the Swedish National Infrastructure for Computing (SNIC) at Chalmers Centre for Computational Science and Engineering (C3SE), partially funded by the Swedish Research Council through grant agreement numbers 2022-06725 and 2018-05973.
2025-04-072025-04-072025-09-23Bibliographically approved