(11g) Optimisation Under Uncertainty of Direct Air Capture Chains in Europe

Direct Air Capture (DAC) is a critical technology for achieving net-zero targets and enabling negative emissions by removing CO₂ from the atmosphere. This study develops a multi-period mixed-integer linear programming (MILP) model for the strategic planning of DAC supply chains across Europe, with a focus on minimising overall costs under uncertainty. The optimisation framework integrates uncertainty in key parameters to enhance the resilience of decision-making and incorporates the influence of ambient air conditions on DAC performance. Factors such as temperature, humidity, country-specific energy costs, and greenhouse gas (GHG) emission factors are considered, impacting productivity, energy consumption, and net CO₂ removal costs.

Novelty and methodology

This study introduces several innovative elements compared to previous methodologies for DAC deployment and optimisation in Europe (Terlow et al., 2024). Firstly, it employs a multi-period framework spanning from 2025 to 2050, enabling dynamic and strategic planning over an extended timeframe. Secondly, the MILP approach integrates uncertainty in key parameters such as contactor cost, energy consumption, and energy prices, ensuring robustness across diverse future scenarios. Uncertainty is captured by generating 10,000 realisations of uncertain parameters using normal and triangular distributions, enhancing model reliability. Additionally, this study provides a detailed breakdown of total costs into capture, transport, and sequestration components, with capture costs further subdivided into capital and operational expenses dependent on ambient conditions and energy prices. A spatial resolution of 250 km is adopted to balance geographic detail and computational feasibility, while transport options - including multiple pipeline and ship sizes - enhance logistical flexibility. Moreover, climatic data is incorporated to ensure a comprehensive year-round operational assessment, while country-specific GHG emission factors are factored in to refine cost evaluations.

Results

The economic analysis confirms that ambient air conditions significantly impact sorbent performance, with temperature and humidity affecting productivity and energy consumption (Sabatino et al., 2021). By leveraging seasonal temperature data and literature-based interpolations for European locations (Wiegner et al., 2022), this study evaluates cost-optimal DAC supply chains under different policy and market conditions. Two deployment scenarios - LowDAC and HighDAC - were established to simulate varying DAC growth rates across Europe (Mcquillen et al., 2022). Under the most pessimistic "business as usual" scenario within the HighDAC case, the total chain cost ranged from 545-748 €/t CO₂. In contrast, under the most favourable conditions, which assumed a 12% learning curve (Sievert et al., 2024) and fully electrified DAC, costs could potentially fall to 407-121 €/t CO₂ within the 2025-2050 timeframe. CO₂ transport and sequestration collectively contributed up to 10% of total DAC costs by 2050, with offshore sequestration and ship transport presenting viable options despite higher costs compared to onshore storage and pipeline transport. These options provide strategic advantages for locations distant from sequestration sites, enhancing flexibility without significantly increasing infrastructure costs.

Conclusions

The results suggest that with ambitious deployment targets, technological learning curves, and a transition to renewable electricity, DAC costs could decrease to approximately 121 €/t CO₂ by 2050, with capture costs contributing 108 €/t. While proximity to sequestration sites remains beneficial, local energy mix and costs exert a greater influence on the selection of optimal DAC locations. Countries with a high share of renewable energy and lower energy costs emerge as preferred sites for DAC installations, reinforcing the importance of renewable energy transition in improving DAC cost-effectiveness. This study offers a robust, adaptable model for the strategic planning of DAC supply chains, which can be continuously refined with new data as technology advances and market conditions evolve. These insights provide a systematic framework for policymakers to design resilient and cost-effective supply chains, positioning DAC as a competitive solution for hard-to-abate emissions.

References

Mcquillen, J.; Leishman, R.; Williams, C. European CO₂ availability from point-sources and direct air capture. Report for: Transport & Environment. 2022. https://www.transportenvironment.org/wp-content/uploads/2022/07/DAC-fin… (accessed 8.5.24)

Sabatino, F.; Grimm, A.; Gallucci, F.; van Sint Annaland, M.; Kramer, G.J.; Gazzani, M. A comparative energy and costs assessment and optimization for direct air capture technologies. Joule 2021, 5, 2047-2076. https://doi.org/10.1016/j.joule.2021.05.023

Sievert, K.; Schmidt, T.S.; Steffen, B. Considering technology characteristics to project future costs of direct air capture. Joule 2024, 8, 979-999. https://doi.org/10.1016/j.joule.2024.02.005

Terlouw, T.; Pokras, D.; Becattini, V.; Mazzotti, M. Assessment of Potential and Techno-Economic Performance of Solid Sorbent Direct Air Capture with CO₂ Storage in Europe. Environ. Sci. Technol. 2024, 58, 10567-10581. https://doi.org/10.1021/acs.est.3c10041

Wiegner, J.F.; Grimm, A.; Weimann, L.; Gazzani, M. Optimal Design and Operation of Solid Sorbent Direct Air Capture Processes at Varying Ambient Conditions. Ind. Eng. Chem. Res. 2022, 61, 12649-12667. https://doi.org/10.1021/acs.iecr.2c00681