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Post-combustion CO2 capture with a commercial activated carbon: Comparison of different regeneration strategies

Open access
Plaza, M.G., García, S., Rubiera, F., Pis, J.J., Pevida, C.·2010·Chemical Engineering Journal

Abstract

Abstract A commercial activated carbon supplied by Norit, R2030CO2, was evaluated as CO 2 adsorbent under conditions relevant to post-combustion CO 2 capture (ambient pressure and diluted CO 2 ). It has been demonstrated that this carbon possesses sufficient CO 2 /N 2 selectivity in order to efficiently separate a binary mixture composed of 17% CO 2 in N 2 . Moreover, this carbon was easily completely regenerated and it did not show capacity decay after 10 consecutive cycles. Three different regeneration strategies were compared in a single-bed adsorption unit: temperature swing adsorption (TSA), vacuum swing adsorption (VSA) and a combination of them, vacuum and temperature swing adsorption (VTSA). Through a simple two step TSA cycle, CO 2 was concentrated from 17 to 43 vol%. For the single-bed cycle configurations, the productivity and CO 2 recovery followed the sequence: TSA −1 h −1 and a maximum CO 2 recovery of 97% were reached.

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Metadata

Authors
Plaza, M. G., García, S., Rubiera, F., Pis, J. J., & Pevida, C.
Venue
Chemical Engineering Journal
Publisher
Elsevier BV
Published
2010-09
Volume
163
Issue
1-2
Pages
41-47
ISSN
1385-8947 (ISSN-L)
OpenAlex
W2010718152
Cited by
365
References
2
FWCI
26.16
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Post-combustion CO2 capture with a commercial activated carbon: Comparison of different regeneration strategies. https://app.cochat.ai/papers/10.1016/j.cej.2010.07.030
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Plaza, M. G., García, S., Rubiera, F., Pis, J. J., & Pevida, C. (2010). Post-combustion CO2 capture with a commercial activated carbon: Comparison of different regeneration strategies. Chemical Engineering Journal. https://doi.org/10.1016/j.cej.2010.07.030

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.