The investigation of treatment design parameters on carbon integration networks

Carbon Integration methods help identify the appropriate allocation of captured carbon dioxide (CO 2 ) streams into CO 2 -using sinks, and are especially useful when a number of CO 2 sink options are present simultaneously. The method helps identify CO 2 allocation scenarios when subjected to an emission target on the CO 2 overall network. Many carbon dioxide sink options are costly, and more often than not, require a high purity carbon dioxide source to satisfy the sink demand. Hence, it is imperative to effectively incorporate treatment units in such networks, to obtain high-purity CO 2 streams. In fact, it has been previously reported in many studies that the most expensive step in Carbon Capture, Utilization and Sequestration (CCUS) is the treatment system. As a result, this paper focuses on reassessing the performance of carbon integration networks using a more rigorous cost model for the treatment design stage. The effect of utilizing different treatment operating conditions on the overall cost of the treatment stage of CO 2 (before allocation) is first captured using a detailed cost model. Subsequently, this information is then fed into a network design problem that involves a CO 2 source-sink allocation network problem, and different CO 2 net capture targets within the network. For this, an enhanced treatment model that captures all necessary treatment design parameters has been utilized alongside the original model. The original carbon integration formulation has been adopted from previous work. Many of the cost items have been lumped into single parameters in the original formulation, and lack the necessary depth required to carry out the necessary investigations for this work. Hence, the treatment model introduced in this paper is more rigorous, as it accounts for important technical performance constraints on the system to be assessed. Utilizing a more detailed cost model was found to be very helpful in understanding several effects of varying parameters on the overall source-sink allocations, when subjected to different CO 2 net emission reduction targets. The cost of the carbon network increases when the solvent temperatures are increased. However, there was a noticeable linear trend at lower temperatures compared to higher temperatures, where the increase became non-linear. Furthermore, it was discovered that for net capture targets of 20% and 25%, no revenue from carbon storage could be generated beyond a solvent temperature of 25 °C. Additionally, the optimal diameter of the treatment column was more responsive to changes in solvent temperature for cases with low net capture targets (below 10%), while its sensitivity decreased for higher capture targets (above 10%). Graphical Abstract