Process-level uncertainties challenge system-level direct air capture assessments

Abstract System-level assessments of direct air capture (DAC) commonly rely on individual process models, overlooking the influence of model choice on system-level conclusions. Here, we quantify this impact by integrating weather-dependent performance data from seven solid-sorbent DAC models into an otherwise consistent energy system framework. DAC representation is the largest source of variation in levelized CO2 capture cost, accounting for 43% of the observed variation across the climate-renewable archetypes considered compared with 16% for climate and 6% for renewable-resource configuration. Model-dependent cost differences exceed 1000 € tCO2-1 at individual locations. Different model representations can also reverse siting preferences, substantially alter cost-optimal system design, and determine whether future CO2 capture-cost targets are achieved. Our results further demonstrate how individual process-level assumptions can propagate through the assessment, resulting in a major source of system-level uncertainty. The harmonized DAC performance data developed here enable systematic comparison of alternative DAC representation in future system assessments.

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Publication Details

Journal
Research Square
Published
2026-11-02
DOI
https://doi.org/10.21203/rs.3.rs-11387567/v1
Primary Topic
Carbon Dioxide Capture Technologies
Type
preprint

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Process-level uncertainties challenge system-level direct air capture assessments

Sean McCoy, Marwan Sendi, Carsten Wedler, Tom Terlouw et al.
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Research Square
Carbon Dioxide Capture Technologies
preprint

Process-level uncertainties challenge system-level direct air capture assessments

Sean McCoy, Marwan Sendi, Carsten Wedler, Tom Terlouw, Russell McKenna, Ralf Peters, Niklas V. von der Assen, Jochen Linßen, Thomas Schöb, Jann Michael Weinand, Vittoria Bolongaro, Daniel Rezo, Niall Mac Dowell, Henrik Wenzel, Mattia Galanti, Malte Glaser, Christoph Winkler, Martin van Sint Annaland, Aaron Jajjawi, Mak Dukan
preprint en

Abstract

Abstract System-level assessments of direct air capture (DAC) commonly rely on individual process models, overlooking the influence of model choice on system-level conclusions. Here, we quantify this impact by integrating weather-dependent performance data from seven solid-sorbent DAC models into an otherwise consistent energy system framework. DAC representation is the largest source of variation in levelized CO2 capture cost, accounting for 43% of the observed variation across the climate-renewable archetypes considered compared with 16% for climate and 6% for renewable-resource configuration. Model-dependent cost differences exceed 1000 € tCO2-1 at individual locations. Different model representations can also reverse siting preferences, substantially alter cost-optimal system design, and determine whether future CO2 capture-cost targets are achieved. Our results further demonstrate how individual process-level assumptions can propagate through the assessment, resulting in a major source of system-level uncertainty. The harmonized DAC performance data developed here enable systematic comparison of alternative DAC representation in future system assessments.

Research Square
University of Calgary (CA), Forschungszentrum Jülich (DE), Paul Scherrer Institute (CH), ETH Zurich (CH), Saudi Aramco (Saudi Arabia) (SA), Institute of Energy and Process Engineering (CH), Imperial College London (GB), Saudi Aramco (United States) (US), Eindhoven University of Technology (NL), RWTH Aachen University (DE)
HORIZON EUROPE Framework Programme, Staatssekretariat für Bildung, Forschung und Innovation
Climate action, Affordable and clean energy
Carbon Dioxide Capture Technologies
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