Carbon Capture and Storage (CCS) is an essential technology for CO₂ emissions reductions, which will allow us to continue consuming fossil fuels in the short to medium term. In this work, we developed a multiscale modeling and optimization approach that links detailed models of the capture plant, compression train and pipelines with the CO₂ supply-chain network model. This was used to find the cost-optimal CO₂ network considering a case-study of meeting a national reduction target in the United Arab Emirates that supplies CO₂ for EOR activities. The main decision variables were the optimal location and operating conditions of each CO₂ capture and compression plant in addition to the topology and sizing of the pipelines while considering the whole-system behaviour. A key result of our study was that the cost-optimal degree of capture should be included as a degree of freedom in the design of CO₂ networks and it is a function of several site-specific factors, including exhaust gas characteristics, proximity to transportation networks and adequate geological storage capacity. This conclusion serves to underscore the need to comprehend the science governing the physical behaviour at different scales and the importance of a whole-system analysis of potential CO₂ networks.

碳捕集与封存（CCS）是减少CO ₂排放的一项必不可少的技术，这将使我们在中短期内能够继续消耗化石燃料。在这项工作中，我们开发了一种多尺度建模和优化方法，该方法将捕获装置，压缩链和管道的详细模型与CO ₂供应链网络模型相链接。考虑到要实现为EOR活动提供CO _2的阿拉伯联合酋长国的国家减排目标的案例研究，这是用来找到成本最佳的CO ₂网络。主要决策变量是每种CO ₂的最佳位置和运行条件在考虑整个系统行为的同时，还对管道的拓扑结构和大小进行了捕获和压缩，同时还对设备进行了捕获和压缩。我们研究的关键结果是，CO ₂网络设计中应将捕获成本的最佳程度作为自由度纳入考虑范围，并且它是几个特定地点因素的函数，包括废气特性，交通便利性网络和足够的地质存储容量。该结论旨在强调需要理解管理不同规模物理行为的科学，以及对潜在CO ₂网络进行全系统分析的重要性。