15:45 - 16:15
Environmental impact of the CCS value chain
Large-scale carbon capture and storage can significantly reduce the CO2 emission of Europe but comes with expensive infrastructures, high energy demand, and its own CO2 footprint. We assess the energy demand and CO2 emission of a transport network that collects CO2 from industrial emitters across Europe and stores it in selected offshore locations.
We specifically address the variability of CO2-rich exhaust gas compositions that introduces impurities into the captured CO2 streams and impacts the efficiency and energy demand of capture, transport, and storage processes. To automate the analysis, we develop computer models for the optimum design of the transport network and the subsurface storage by minimizing the resource requirement (material and exergy). The Python-based web application utilizes graph theory and geospatial tools and data to optimize the transport path from emitters to storage locations. It also has functionalities for designing and estimating the cost of process equipment. We present the exergy demand and CO2 penalty of an optimized CCS network that can reduce the point source CO2 emission of Europe by 70%. We also demonstrate open-source Python software for the design and optimization of a CCS network for given locations with known point sources and storage locations.
