Abstract Carbon capture and geological storage (CCS) is a key technology for the World deep decarbonization. However, several challenges remain, such as the optimization of the carbon transportation infrastructures. This study proposes a methodology that applies the Kernel Density function in a geographic information system software and uses as input, CO2 emission sources data to identify emission clusters and emission high-density hotspots. The main goal of the proposed methodology is to perform a preliminary screening to identify areas of interest to install hubs when designing an optimized CO2 pipeline network. The methodology includes an estimation of capturable CO2 emissions and a density analysis that was based on Kernel Density function from the ArcGIS Desktop 10. The methodology was applied to the Iberian Peninsula CO2 industrial emission sources such as refineries, coal and natural gas power plants and cement factories (case study) and the results showed that in Portugal, CO2 industrial emissions reduction can reach up to 68% and, in Spain, up to 74% of CO2 industrial emissions, could be avoided. These are called capturable CO2 emissions which means that they are the portion of the total emissions that can be captured from industrial processes before they reach the atmosphere. Moreover, hubs were shown to be more viable when Portugal and Spain are considered together, therefore, carbon routes (pipeline network) in the future may consider an integrated route for the Iberian Peninsula.