Modelling of an integrated process for atmospheric carbon dioxide capture and methanation

Claudio Tregambi, Piero Bareschino, Dawid P. Hanak, Fabio Montagnaro, Francesco Pepe, Erasmo Mancusi

Research output: Contribution to journalArticlepeer-review

7 Citations (Scopus)

Abstract

Negative-emission technologies are largely investigated to better control atmospheric carbon dioxide concentration driving global warming. Calcium looping has been proposed in literature for direct air capture, but a comprehensive system analysis is still missing. Methanation of carbon dioxide can represent an alternative to geological storage, widely investigated within the power-to-gas framework. In this study, an integrated process considering the catalytic methanation of the concentrated carbon dioxide stream after capture from ambient air by a pure hydrogen stream from water electrolysis was proposed and numerically investigated. The system relies on packed bed reactors and uses calcium oxide as sorbent, and a nickel-based catalyst for methanation. A comprehensive study on the overall system performance was carried out, assuming a carbon dioxide capture target of 100 t y−1. Model computations suggest that roughly 50-in-parallel reactors, 0.5 m diameter each, are required for a continuous operation. The overall energy demand of the integrated process ranges within 344–370 GJ tCH4−1, or 215–293 GJ tCH4−1 if neglecting the humidifier. The methanation process requires 3-in-series reactors and can yield a continuous gas stream with a flow rate of 5 kg h−1 and a methane molar fraction of nearly 91%. If this stream is exploited for heat generation, a return of energy index of 16%, or 23% if neglecting the humidifier, is foreseen. The proposed process stems as viable solution towards a circular carbon economy.

Original languageEnglish
Article number131827
JournalJournal of Cleaner Production
Volume356
DOIs
Publication statusPublished - 1 Jul 2022
Externally publishedYes

Bibliographical note

Funding Information:
Claudio Tregambi wishes to thank the Italian Ministry of University and Research (MUR) , for funding his research position within the “PON Ricerca e Innovazione 2014–2020, Asse I Investimenti in Capitale Umano” – AIM 1823125-1, CUP: F84I19000010001.

Publisher Copyright:
© 2022 Elsevier Ltd

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