A million scenarios to identify conditions for robust bioenergy carbon capture in Sweden
Artikel i vetenskaplig tidskrift, 2025

Large-scale bioenergy carbon capture and storage (BECCS) could be realized without escalating biomass use - under the right conditions. We apply robust decision-making theory to frame carbon capture as a decision problem. We then search for conditions of low costs and energy penalties by modelling the capture decision across a million scenarios of already-existing plants in Sweden. Mining the scenario data reveals that annual plant utilization, heat recovery via heat pumps and electricity prices constitute key conditions for combined heat and power plants. For pulp mills, key conditions are site-specific, but the availability of low-pressure steam and electricity prices are generally important. A sensitivity analysis supports these findings, but also identifies capture rates as key. About 19 MtCO2 could be captured annually from the 113 plants studied while combusting zero additional biomass. Under the identified conditions, this would entail reduced power and district heating generation of 5.1-7.9 TWh per year – a modest penalty relative to the 220 TWh generated annually in Sweden.

Robust decision making

RDM

Scenario discovery

Exploratory modelling

Data mining

CCS

Combined heat and power

Carbon capture and storage

Bioenergy

Heat integration

Pulp

BECCS

Machine learning

Carbon dioxide removal

Författare

Oscar Stenström

Chalmers, Rymd-, geo- och miljövetenskap, Energiteknik

Tharun Roshan Kumar

Chalmers, Rymd-, geo- och miljövetenskap, Energiteknik

Magnus Rydén

Chalmers, Rymd-, geo- och miljövetenskap, Energiteknik

International Journal of Greenhouse Gas Control

1750-5836 (ISSN)

Vol. 145 104411

Under nollpunkten- Ansvarsfull och anpassningsbar realisering av sociotekniska bioenergisystem med avskiljning och lagring avkoldioxid

Energimyndigheten (P2022-00172), 2022-12-01 -- 2027-12-01.

Ämneskategorier (SSIF 2025)

Energiteknik

Energisystem

DOI

10.1016/j.ijggc.2025.104411

Relaterade dataset

ostenst/BECCS-Sweden: Review release [dataset]

DOI: https://doi.org/10.5281/zenodo.14236300

Mer information

Senast uppdaterat

2025-06-10