Abstract

The detrimental environmental impacts of climate change that are a result of high atmospheric CO 2 concentrations have prompted global efforts to limit the continuous increase in greenhouse gas (GHG) emissions. Many are now relying on the deployment of various carbon capture, utilization and storage (CCUS) methods which have been found reliable for reducing CO 2 levels in the atmosphere. Various industries are shifting towards the decarbonisation of their operations through the use of a combination of various CCUS activities. This could involve the conversion of CO 2 into value-added chemicals, the utilization of CO 2 for enhanced oil recovery (EOR), the injection of CO 2 into geological formations and/or oceans, the biological fixation of CO 2 , and other similar activities. Such operations are often referred to as CO 2 “sinks”. It is often crucial for industries to identify which CCUS operations to deploy, especially when faced with many choices, since factors such as the cost of implementation and the sink efficiency play a significant role in the sink selection process. In this work, a mathematical model that helps identify optimal CO 2 sink locations within industrial clusters is developed and utilized. Identifying optimal sink locations is an important factor that needs to be considered as part of a CCUS network planning problem. The proposed mathematical model was found to be very useful for identifying optimal CCUS sink selections, and their respective locations. A total of 22.7% of savings in transportation costs have been realized within the network, when compared to the case of having sink locations prescribed upfront.

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