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Cited by 462

The DOI matches its Crossref record; 112 of the 112 references it cites were found in a registry or an index.

Outlook of carbon capture technology and challenges

Open access
Wilberforce, Tabbi, Baroutaji, Ahmad, Soudan, Bassel, Al-Alami, Abdul Hai, Olabi, Abdul Ghani·2019·Science of The Total Environment

Abstract

The greenhouse gases emissions produced by industry and power plants are the cause of climate change. An effective approach for limiting the impact of such emissions is adopting modern Carbon Capture and Storage (CCS) technology that can capture more than 90% of carbon dioxide (CO2) generated from power plants. This paper presents an evaluation of state-of-the-art technologies used in the capturing CO2. The main capturing strategies including post-combustion, pre-combustion, and oxy - combustion are reviewed and compared. Various challenges associated with storing and transporting the CO2 from one location to the other are also presented. Furthermore, recent advancements of CCS technology are discussed to highlight the latest progress made by the research community in developing affordable carbon capture and storage systems. Finally, the future prospects and sustainability aspects of CCS technology as well as policies developed by different countries concerning such technology are presented.

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Crossref · 10.1016/j.scitotenv.2018.11.424

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Metadata

Authors
Wilberforce, T., Baroutaji, A., Soudan, B., Al-Alami, A. H., & Olabi, A. G.
Venue
Science of The Total Environment
Publisher
Elsevier BV
Published
2019-03
Volume
657
Pages
56-72
ISSN
0048-9697 (ISSN-L)
OpenAlex
W2902325525
Cited by
462
References
112
FWCI
23.02
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Outlook of carbon capture technology and challenges. https://app.cochat.ai/papers/10.1016/j.scitotenv.2018.11.424
The paper
Wilberforce, T., Baroutaji, A., Soudan, B., Al-Alami, A. H., & Olabi, A. G. (2019). Outlook of carbon capture technology and challenges. Science of The Total Environment. https://doi.org/10.1016/j.scitotenv.2018.11.424

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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.