The oil industry needs to reduce CO₂ emissions across the entire lifecycle of fossil fuels to meet environmental regulations and societal requirements and to sustain its business. With this goal in mind, this study aims to evaluate the CO₂ mitigation potential of several bio-oil co-processing pathways in an oil refinery. Techno-economic analysis was conducted on different pathways and their greenhouse gas (GHG) mitigation potentials were compared. Thirteen pathways with different bio-oils, including vegetable oil (VO), fast pyrolysis oil (FPO), hydro-deoxygenated oil (HDO), catalytic pyrolysis oil (CPO), hydrothermal liquefaction oil (HTLO), and Fischer–Tropsch fuels, were analyzed. However, no single pathway could be presented as the best option. This would depend on the criteria used and the target of the co-processing route. The results obtained indicated that up to 15% of the fossil-fuel output in the refinery could be replaced by biofuel without major changes in the core activities of the refinery. The consequent reduction in CO₂ emissions varied from 33% to 84% when compared with pure equivalent fossil fuels replaced (i.e., gasoline and diesel). Meanwhile, the production costs varied from 17 to 31€/GJ (i.e., 118–213$/bbl_eq). Co-processing with VO resulted in the lowest overall performance among the options that were evaluated while co-processing HTLO in the hydrotreatment unit and FPO in the fluid catalytic cracking unit showed the highest potential for CO₂ avoidance (69% of refinery CO₂ emissions) and reduction in CO₂ emissions (84% compared to fossil fuel), respectively. The cost of CO₂ emissions avoided for all of the assessed routes was in the range of €99–651 per tCO₂.

The use of CO₂ for enhanced oil recovery (CO₂-EOR) is a promising alternative for reducing the cost of carbon capture and storage (CCS). In this study the techno-economic potential of integrated CCS-EOR projects for reducing greenhouse gas (GHG) emissions in the Colombian oil industry is estimated. For this purpose, a source-sink matching process is carried out, including CO₂ capture potentials in sources from the petroleum, cement, power generation, and bioethanol industries, as well as from the CO₂ storage in suitable oil fields for EOR. The results indicate that a total of 142 million tons of carbon dioxide (MtCO₂) could be stored, while delivering 465 MMbbl through five CCS-EOR projects in four clusters identified around the country. The levelised cost for capture ranged between 12–209 €/tCO₂, followed by the cost of CO₂ during EOR operations with a variation of 24–59 €/tCO₂, and finally the CO₂ transport, from 1 €/tCO₂ to 23 €/tCO₂. The CO₂ mitigation potential of CCS-EOR represents 25 % of the forecasted oil industry emissions in Colombia for the period of 2025–2040. As compared to the intended nationally determined contribution (INDC) target set by the Colombian government, CCS-EOR projects could contribute 7 % of the total accumulated emissions reductions by 2040.

The oil and gas sector represents 39% of the world's total industrial final energy consumption, and contributes to around 37% of total greenhouse gas (GHG) emissions. This study investigates the potential for improvements in energy efficiency, and their implications for CO₂ abatement, in the Colombian oil industry value chain. It also assesses the potential cost of conserved energy and mitigated CO_2-eq. A bottom-up approach was used to identify energy efficiency measures based on an assessment of specific operational data at the process unit level. In total, 20 measures and technologies were identified and applied in 48 cases throughout the chain, representing energy savings of 15.8 PJ and GHG savings of 0.75 Mt CO_2-eq per year. This accounts for 25% and 19% of the total energy consumption and GHG emissions, respectively. Ninety-six percent of the total energy savings come from measures that are already cost-effective and could be implemented in the short term. The results of this study offer a better understanding of the critical stages for energy and GHG savings potentials, as well as investment cost and revenue from a full value chain perspective, based on operational data processing.