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The imperative to mitigate industrial CO2 emissions amidst global climate change has led to the development of innovative strategies that align economic growth with environmental sustainability. This study introduces a comprehensive CO2 allocation and utilisation framework, designed to reduce the environmental impact on the production of Liquefied Natural Gas (LNG). Demploying a multi-objective Linear Programming (LP) approach, the study introduces a system that dynamically allocates CO2 from a major source to several sinks, each with unique characteristics and requirements. Focusing on the State of Qatar, a major player in the global LNG market, advanced simulation tools, such as Aspen HYSYS and QASR Simulator are utilised to define the parameters of these sinks, ensuring precise and efficient CO2 allocation. An integral component of the model is the incorporation of a carbon tax, considered for both the source and the sinks. The results demonstrate that the profit maximisation objective generated a 23. 6 billion annual profit, although with high emissions of 23. 37 Mt/year. In contrast, the emission minimisation objective curbed emissions to 19. 01 Mt/year at a profit of 1. 4 billion. The multi-objective approach garnered 18. 6 billion annually with emissions at 22. 37 Mt/year. The CO2/LNG metric was used to gauge LNG's environmental footprint. Objective 1 yielded a ratio of 0. 3033, while objective 2 achieved the best score at 0. 2463. The multi-objective approach balanced both, with a ratio of 0. 2905. These findings illuminate the feasibility of optimising industrial practices for producing low-carbon LNG through deliberate CO2 allocation and within a circular economy framework.
Sawaly et al. (Wed,) studied this question.