A CO2 valorization plant to produce light hydrocarbons: Kinetic model, process design and life cycle assessment

Tomás Cordero-Lanzac, Adrian Galilea, Marta Cruz-Fernandez, Hans-Jorg Zander, Finn Joensen, Steven Woolass, Andreas Meiswinkel, Peter Styring, Jorge Gascon, Unni Olsbye

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

Reliable Life Cycle Assessment (LCA) of processes for valorization of CO2-rich off-gas streams requires multidisciplinary contributions that span the development of active and selective catalysts, reactor design, plant modeling and optimization, as well as environmental impact analysis. Herein, we present the design and study of a CO2 valorization plant through methanol-mediated (tandem) hydrogenation to light hydrocarbons, with propane as the most abundant product. A state-of-the-art PdZn/ZrO2 + SAPO-34 catalyst combination was screened for catalytic activity and selectivity in a wide operation range. Optimal process conditions were found at 350 °C, 30–40 bar and co-feeding of CO2/CO. Kinetic parameters for the tandem reaction were extracted and used for the design of a multi-layer reactor, where the two catalysts are distributed according to: (i) CO2-to-methanol catalyst; (ii) mixed catalyst bed, and; (iii) methanol-to-hydrocarbons catalyst. This configuration outperformed the conventional dual bed and mixed bed reactor configurations in terms of process design. A Life Cycle Assessment of the plant suggested that a substantial decrease in the global warming impact of propane production will be highly driven by using green hydrogen from either solar or wind sources, although the comparison with fossil-derived propane indicated already a reasonable improvement even when using grey hydrogen from natural gas.
Original languageEnglish (US)
Pages (from-to)102337
JournalJOURNAL OF CO2 UTILIZATION
Volume67
DOIs
StatePublished - Nov 25 2022

Bibliographical note

KAUST Repository Item: Exported on 2022-12-27
Acknowledgements: This work has been carried out with the financial support of the European Union through the Horizon 2020 research and innovation program under the grant agreement 837733 (COZMOS).

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