Projects per year
Abstract
As global efforts intensify to reduce CO2 emissions and combat climate change, this study explores the integration of Carbon Capture, Utilisation, and Storage (CCUS) and Carbon Tax (CT) for producing low-carbon Liquefied Natural Gas (LNG) in Qatar. The research develops a model employing Post Combustion Capture (PCC) to capture and strategically allocate CO2 from a single major source to various sinks. Utilising a Linear Programming (LP) approach, the model aims to balance profitability with emission reduction, considering factors such as operational costs, carbon tax implications, and the market price of CO2. The study examines three scenarios: maximising profit, minimising emissions, and a hybrid of both, to assess the impact of different CO2 allocation strategies on economic and environmental outcomes of the source. Results indicate that while specific CO2 allocation decisions subtly affect profitability and emissions, the overall economic and environmental performance remains consistent across scenarios. This research highlights the potential of CCUS and CT in enhancing sustainable energy production and advancing a circular economy in carbon management.
Original language | English |
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Title of host publication | Computer Aided Chemical Engineering |
Publisher | Elsevier B.V. |
Pages | 559-564 |
Number of pages | 6 |
DOIs | |
Publication status | Published - Jan 2024 |
Publication series
Name | Computer Aided Chemical Engineering |
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Volume | 53 |
ISSN (Print) | 1570-7946 |
Keywords
- CO allocation
- Carbon capture
- Liquified Natural Gas
- Sustainability
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Dive into the research topics of 'Advancing Low-Carbon LNG within Qatar: Integrating CCUS and Carbon Tax Strategies'. Together they form a unique fingerprint.Projects
- 1 Active
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EX-QNRF-GSRA-7: Optimising the capture and utilization of CO2 in Qatar through the development of a novel allocation methodology considering by multiple sources and sinks driven by environmental and economic policies
Sawaly, R. (Lead Principal Investigator)
31/07/22 → 31/05/26
Project: Applied Research