Developing a preliminary site selection method for direct air capture and CO2 storage technology with a case study in the North Germany

• Novel method for selecting CO₂ storage sites for DACCS implementation. • Integrated AHP with multicriteria decision-making for site ranking. • Compiled and standardized geological data into a comprehensive database. • 92 Sites for direct air capture and CO 2 storage in Germany are identified. • 1.24–5.26 Gt of CO 2 can be stored in the identified reservoirs. Achieving global net-zero emission targets requires substantial CO 2 removal, with Direct Air Capture and Carbon Storage (DACCS) emerging as a pivotal technology. Addressing a knowledge gap in systematically selecting optimal geological sites for CO 2 storage for DACCS, this study introduces a novel and adaptable multicriteria site selection and ranking methodology. By coupling the Analytical Hierarchy Process (AHP) with multicriteria decision-making, we quantitatively evaluate and prioritize potential storage sites, providing a scalable framework applicable to sedimentary basins worldwide. As a case study, we compiled and standardized publicly available geological data to build a comprehensive underground storage database for the North German Basin (NGB), categorizing geological features into five key criteria: storage capacity, injectivity, trapping mechanism, containment, and cost. Representative parameters under each criterion were harmonized for data resolution and quality. Our findings not only highlight promising sites in the German North Sea and the state of Brandenburg but also demonstrate the methodology's effectiveness in systematically identifying optimal sites for DACCS implementation. The developed criteria-based ranking system incorporates weighting factors determined by experts, effectively quantifying the importance of each criterion while accounting for uncertainties in both parameters and weighting factors. This approach addresses the global site selection necessity for CO₂ storage by providing a transparent, reproducible, and adaptable framework.