Near-optimal solutions for carbon capture, conversion, storage, and removal strategies

Abstract

Achieving climate neutrality in Europe requires rapid electrification alongside carbon management strategies for residual emissions. Existing analyses of the European energy system often focus on collocated carbon capture and geological sequestration, with limited attention to the interactions among carbon capture and utilization, transport, sequestration, and diverse carbon dioxide removal (CDR) options. Moreover, existing literature focuses on discussing the optimal, neglecting that near-optimal solutions might provide very different system configurations at a marginal higher cost. Here, we integrate afforestation, biochar, enhanced rock weathering, and perennialization into a sector-coupled European energy system model (PyPSA-Eur) clustered to 39 nodes with 750 aggregated time steps. We explore their contributions using a Modelling to Generate Alternatives (MGA) approach. The approach combines minimization, maximization, and random vectors to explore the near-optimal solution space for up to 5% increased total system costs. Our results show that, in a carbon-neutral system, multiple configurations of carbon management options can achieve net-zero emissions with only marginal cost increases. We find that a 5% total system cost increase is sufficient to accommodate the full spectrum from zero to full deployment of the individual CDR options, as well as a wide range of synthetic fuel use across different fuel types. Increased reliance on CDR options offers no clear cost advantage compared to greater utilization of synthetic fuels.

Figures (17)

• Figure 1: Optimal solution on which near-optimal solutions are based. Overview of the CO2 that is captured from point-source emissions or conversion processes and is available for underground sequestration or conversion to synthetic fuels and CO2 removal (left) and how carbon capture balances CO2 emissions in the atmosphere (right).
• Figure 2: Solution space for carbon management strategies (see Tab. \ref{['tab:CDR']}). Point-source CC is the sum of all capture technologies except for DAC. Solutions were obtained for a total system cost increase of 1%, 3%, and 5% based on the optimal solution.
• Figure 3: Solution space for point-source utilization with and without carbon capture. Solutions were obtained for a total system cost increase of 1%, 3%, and 5% based on the optimal solution. While biomass for industry demand is set exogenously, using it with carbon capture lowers the efficiency of the process, resulting in a 1.1% higher biomass demand. Single solutions are shown for technologies with and without carbon capture combined.
• Figure 4: Differences of carbon management strategies utilization for solutions with minimal CO2 sequestration underground use compared to the optimal solution. A reduction of capture technologies shown on the left figure (e.g. DAC) translates into an increase in CO2 emissions shown on the right figure. The grey boxes for the CO2 balance show the total amount of emissions being increased or reduced compared to the optimal solution.
• Figure 5: Solutions for minimizing a) afforestation, b) ERW, c) perennialization. Values indicate changes in capturing, removal, sequestration, and conversion compared to the optimal solution.