Multifactorial Screening for Fine‐Scale Selection of CCS Industrial Clusters and Hubs in Brazil

ABSTRACT As Brazil moves toward implementing its decarbonization commitments, carbon capture and storage (CCS) hubs are emerging as a key pathway for large‐scale CO 2 abatement in hard‐to‐abate sectors. This paper presents a multifactorial, data‐driven framework to screen and prioritize potential CCS industrial clusters and hubs across Brazilian regions, emphasizing Rio de Janeiro and São Paulo. The method integrates stratified emission density metrics, clustering algorithms (DBSCAN), and geospatial modeling to identify capture hubs, hypothetically eligible offshore storage wells, and transport corridors. Using emission data from the recognized SEEG database and the Campos and Santos basins as reference sinks, the framework mapped seven industrial capture clusters and nineteen storage clusters from a sample set of emitters from five sectors. The results show that São Paulo and Rio de Janeiro jointly account for over 63% of Brazil's emission reduction target for industry and energy, with 22% from Rio and 86% from São Paulo at hub level. The analysis provides a geospatial and quantitative foundation for identifying industrial capture clusters at multiple territorial scales using emission‐stratified metrics, selecting macro‐structural fields for the formation of offshore storage clusters and analyzing source‐to‐sink distance charts to assess transportation logistics. The findings contribute to a critical knowledge base to support the future deployment of CCS routes in Brazil and provide a foundation for subsequent feasibility assessments and economic validation.