Modelagem multifatorial para triagem e seleção de clusters e hubs industriais de CCS no contexto brasileiro

Abstract

Carbon Capture and Storage (CCS) technologies constitute a relevant strategy for mitigating emissions from hard-to-abate sectors. When combined with the hub-and-clusters model, these technologies enable the integration of emission sources, CO2 transport systems, and underground geological reservoirs, optimizing the operational efficiency and economic viability of decarbonization chains. This dissertation aims to develop a multifactor model for screening and selecting CCS industrial clusters and hubs in the Brazilian context, integrating the identification of emission sources, offshore sinks, and the analysis of CO2 transport logistics. The methodology integrated geospatial analysis, mathematical modeling, and a heuristic approach to map and prioritize CCS hubs and clusters in the states of Rio de Janeiro and São Paulo. As a result, 59 industrial plants in hard-to-abate sectors were identified, concentrated primarily in São Paulo (81%) and Rio de Janeiro (19%). A total of 387 offshore wells eligible for CO2 storage were also mapped, distributed across the Campos and Santos basins. These wells were grouped into macrofields strategically positioned near areas of high emissive density, reducing logistical distances between sources and sinks taking into account the existing infrastructure. The results indicate priority regions in the Southeast with infrastructure and potential for initial deployment of CCS hubs and clusters in Brazil.