(327f) Life Cycle Assessment of CO2 Capture and Utilization Technologies

CCU technology can reduce greenhouse gas (GHG) emissions by capturing CO₂ generated from various industrial processes and contribute to the reduction of fossil fuel consumption by converting it into a carbon source to produce high value-added products. However, CO₂ is chemically very stable under standard conditions, so the entire process of capturing CO₂ from flue gas and converting it into useful products is energy-intensive, and thus has the potential to cause a significant amount of additional GHG emissions. Therefore, life cycle assessment (LCA) is essential to evaluate whether CCU technology can actually have a positive impact on the environment.

ISO 14040 and 14044 provide standardized guidelines for performing LCA. However, there are several methodological issues when performing LCA in CCU technology. The main issues include whether utilized CO₂ should be regarded as avoided environmental impact or as a process input, how to distribute the environmental burden in a multifunctional system, and whether to apply an attributional approach, focusing on the product itself, or a consequential approach, considering broader social and indirect effects. The general LCA guidelines recommend analyzing these multiple methodologies simultaneously. Therefore, this study aims to establish a comparable LCA database and evaluation framework for CCU technology by performing analysis applying multiple LCA methodologies to various CCU products and technologies.

In this study, LCA was conducted focusing on the following aspects. First, a consequential LCA (CLCA) analysis was performed based on the results of the attributional LCA (ALCA) analysis to evaluate the GHG emission reduction when CCU products successfully enter the market and replace conventional products, integrating market penetration scenarios and indirect social effects. In addition, scenario analyses were conducted to assess differences in LCA results by region, electricity sources, and CO₂ feedstock accounting methods. Finally, a learning curve analysis based on technological maturity was applied to predict how the development of CCU technologies over time would affect GWP of each product.

The major CCU products selected in this study include syngas, methanol, fuel (gasoline, diesel, and aviation fuel), dimethyl ether, organic carbonate (dimethyl carbonate, ethylene carbonate, and propylene carbonate), formic acid, biodegradable plastic (polyhydroxybutyrate, polylactic acid, and polypropylene carbonate), and mineral carbonate (cement alternative, precipitated calcium carbonate, and sodium bicarbonate). Each product can be produced through various CCU technological pathways such as catalytic conversion, biological fixation, electrochemical reduction, and mineral carbonation.

The ALCA of this study was conducted using a cradle-to-gate system boundary. CO₂ feedstock was assumed as consumed emissions in the process. For the multifunctionality problem, the system expansion method was applied as recommended by ISO 14040, and physical allocation was applied in cases where the main product and the co-product could not be clearly distinguished. Dataset for the environmental assessment was sourced from the Ecoinvent 3.11 database. In this study, the electricity database was developed to reflect the energy mix policies of each country. The H₂ dataset was based on the average of four wind-powered electrolysis technologies: alkaline water electrolysis, proton-exchange membrane electrolysis, anion-exchange membrane electrolysis, and solid oxide fuel cell electrolysis. The life cycle impact assessment was conducted using Simapro V9.6 and the ReCiPe 2016(H) midpoint methodology.

Through the conventional ALCA approach, the GWP of individual CCU products and technological pathways was calculated. Syngas produced via biomass gasification presented the lowest GWP at -1.77 kg CO₂ eq./kg of syngas, and it is already commercialized in some regions. In contrast, PPC showed the highest GWP, at 3.91 kg CO₂ eq./kg PPC, mainly due to the high GWP of co-feedstock, propylene oxide.

Traditional ALCA evaluates products based on material and energy flows across the system boundaries. On the other hand, CLCA considers social and indirect effects that occur when CCU products replace conventional products. The total GHG emission reduction depends not only on the GWP of individual CCU products but also on market size and replacement rates. Even if a specific CCU product has a low GWP, its actual GHG reduction may be limited if the market size is small or if it cannot sufficiently replace the conventional product. Therefore, integrating market size and replacement rate into the assessment provides a more realistic evaluation of GHG reduction potential of CCU technology. According to the CLCA results, gasoline demonstrated the greatest potential for GHG emission reduction by avoiding 988.36 billion kg CO₂ eq. based on 2023 market size. This result indicates that the environmental benefits of CCU products are influenced not only by their GWP but also by market demand.

This study conducted three scenario analyses to comprehensively evaluate CCU technology's environmental impacts under various conditions. The first was a regional scenario analysis, assessing the impact of differing energy mixes and policy environments across selected regions. The selected regions—Korea, Brazil, China, the European Union, and the United States—were chosen based on their roles in CCU technology development, the extent of renewable energy deployment, and the policy characteristics of their carbon reduction strategies. As a result, Brazil was generally found to be the most environmentally favorable region for the deployment of CCU technologies due to its high share of renewable energy. This analysis quantitatively evaluated how regional differences in energy mix and infrastructure affect CCU technology's environmental performance, identifying optimal deployment regions based on environmental outcomes.

In the second scenario analysis, the electricity mix in South Korea was varied to evaluate the impact of different electricity sources on the environmental performance of CCU pathways. In particular, since electricity has a critical impact on energy-intensive CCU processes such as electrochemical CO₂ reduction and CO₂ hydrogenation, it is essential to understand the environmental contributions of different power sources. This analysis compared the environmental performance of CCU pathways under different electricity sources, including the current (2023) and projected (2030) mixed energy grid, renewable energy (solar, wind, biogas, fuel cells, hydro, nuclear), fossil energy (natural gas, hard coal, petroleum), and mixed energy grid-based (reflecting both 2023 and projected 2030 energy mixes). As a result, when renewable energy sources such as solar, wind, biogas, and nuclear power were used as energy sources, the e-SAF pathway showed the lowest GWP of -2.33 to -2.04 kg CO₂/kg of SAF, unlike the base case where bio-syngas had the lowest GWP. Through this analysis, the relative impact of each electricity source on the environmental performance of CCU technology could be identified.

In the third scenario analysis, different CO₂ accounting method were applied by comparing a base case in which CO₂ was treated as a consumed emission with a case where CO₂ was considered a process input. When CO₂ is treated as a process input, fuel products tend to exhibit high GWP values due to the large amount of CO₂ used per kilogram of product. In contrast, mineral carbonates show relatively low GWP. In particular, unlike polymers or carbonates that can sequester CO₂ stably over the long term, fuel products re-release CO₂ during combustion, making it crucial to determine whether the utilized CO₂ is considered as avoided emissions or as a process input. Therefore, it is essential for CCU-LCA conductors to ensure the reliability and transparency of the results through scenario analysis based on LCA methodology.

Finally, this study applied a learning curve to model GWP changes resulting from technological advancements and experience accumulation in CCU technologies. The analysis quantitatively demonstrated that CCU pathways with high technological maturity, such as bio-syngas, showed minimal potential for further GWP reduction because these processes have already reached a high level of optimization with limited room for additional improvements. In contrast, pathways with lower technological maturity, including bio-diesel, PHB, and ECR-syngas, demonstrated significant potential for GWP reduction as technology develops.

In conclusion, according to the ALCA results, among the 31 CCU products and technological pathways evaluated in this study, the bio-syngas pathway showed the lowest GWP. The CLCA results indicated that gasoline achieved the highest GHG emission reduction when CCU products were introduced to the market. Through these assessments, the environmental impact of a CCU product depends not only on its inherent GWP but also on market demand. Scenario analyses were conducted to examine how the LCA results of CCU products vary depending on region, electricity source, and CO₂ accounting method. This approach helps reduce uncertainty in the LCA results of CCU technologies and supports the development of strategies to maximize their environmental benefits. Furthermore, the learning curve analysis enabled a quantitative prediction of how much the GWP of products could decrease in the future as the technological maturity of CCU pathways improves. The evaluation framework and database proposed in this study can serve as practical academic and decision-making tools supporting the sustainable development and policy-making of CCU technologies.