Meeting global energy and environmental targets requires a new understanding of the science of large-scale injection and storage of CO₂.

Introduction: Liquid-solvent direct air capture (DAC) is a prominent approach for carbon dioxide removal but knowing where to site these systems is challenging because it requires considering a multitude of interrelated geospatial factors. Two of the most pressing factors are: (1) how should DAC be powered to provide the greatest net removal of CO₂ and (2) how does weather impact its performance?.Methods: To investigate these questions, this study develops a process-level model of a liquid-solvent DAC system and couples it to a 20-year dataset of temperature and humidity conditions at a ~9km resolution across the contiguous US.Results and discussion: We find that the amount of CO₂ sequestered could be 30% to 50% greater than the amount of CO₂ removed from the atmosphere if natural gas is burned on site to power DAC, but that the optimal way to power DAC is independent of capture rate (i.e., weather), depending solely on the upstream GHG intensity of electricity and natural gas. Regardless of how it is powered, air temperature and humidity conditions can change the performance of DAC by up to ~3x and can also vary substantially across weather years. Across the continuous US, we find that southern states (e.g., Gulf Coast) are preferrable locations for a variety of reasons, including higher and less variable air temperature and relative humidity. Lastly, we also find the performance of liquid-solvent DAC calculated with monthly means is within 2% of the estimated performance calculated with hourly data for more than a third of the country, including in the states with weather most favorable for liquid-solvent DAC.

Energy system planning tools suggest that the cost and feasibility of climate-stabilizing energy transitions are sensitive to the cost of CO₂ capture and storage processes (CCS), but the representation of CO₂ transportation and geologic storage in these tools is often simple or non-existent. We develop the capability of producing dynamic-reservoir-simulation-based geologic CO₂ storage supply curves with the Sequestration of CO₂ Tool (SCO₂T) and use it with the ReEDS electric sector planning model to investigate the effects of CO₂ transportation and geologic storage representation on energy system planning tool results. We use a locational case study of the Electric Reliability Council of Texas (ERCOT) region. Our results suggest that the cost of geologic CO₂ storage may be as low as $3/tCO₂ and that site-level assumptions may affect this cost by several dollars per tonne. At the grid level, the cost of geologic CO₂ storage has generally smaller effects compared to other assumptions (e.g., natural gas price), but small variations in this cost can change results (e.g., capacity deployment decisions) when policy renders CCS marginally competitive. The cost of CO₂ transportation generally affects the location of geologic CO₂ storage investment more than the quantity of CO₂ captured or the location of electricity generation investment. We conclude with a few recommendations for future energy system researchers when modeling CCS. For example, assuming a cost for geologic CO₂ storage (e.g., $5/tCO₂) may be less consequential compared to assuming free storage by excluding it from the model.