The scenario today
Several countries have pledged to achieve net zero by 2050. Industries that use fossil fuels such as power, iron and steel, cement, and transportation, are major contributors to carbon dioxide (CO2) emissions. While renewables are being pursued as an alternative source of energy, industries like steel still require carbon sources. Substituting them with chemicals like hydrogen will require major technological transformations.
Moreover, several large economies still depend on thermal power and this dependency is likely to continue until 2040. Additionally, CO2 is already in abundance in the atmosphere with a concentration level of about 415 parts per million (ppm) in 2020. In this context, carbon capture, utilization, and storage (CCUS) become unavoidable to reach the goal of limiting the global temperature rise to 1.5°C. In this blog, we outline a way forward using carbon capture.
Carbon capture technologies as a clean energy option
Point carbon capture is one of many clean energy transition options. It refers to the process of capturing carbon at the source from heavy industries like power, steel, cement, and chemicals. The exhaust gases are in a contained environment and CO2 concentration is also relatively high (10-30% by volume), making a case for carbon capture plants to be established as an extended arm closer to the site. However, this inflates the cost of operations.
Capturing CO2 from the atmosphere, or direct air capture, is relatively more challenging than point carbon capture as the volume of air is huge while concentration of CO2 is extremely low. However, the major advantage of this approach is that plants can be constructed anywhere on the planet. For instance, the plant can be constructed somewhere closer to an abandoned mine where CO2 can be sequestered.
Several factors need to be considered before selecting the carbon capture technology, such as volume of the gas to be treated, concentration of CO2, impurities present, power required, effluents and wastes, and cost. Well-established technologies such as absorption, adsorption, membrane separation, and cryogenic distillation that are used for gas separation and purification in industries are often recommended. New technologies like chemical looping and microbial or algal systems are also being explored for carbon capture. The appropriate technology can be adopted based on the requirements.
Each technology has its pros and cons. For instance, technologies like absorption and cryogenic distillation are mature and CO2 recovery is high (> 95%), but they are energy-intensive (4-10 MJ/kg CO2). On the other hand, adsorption and membrane separation are less energy-intensive (0.5-6 MJ/kg CO2), but recovery is lower (80-90%). Another crucial factor to be considered in the entire process is the cost of transportation and storage of CO2. The current practice is to store CO2 in saline formations and depleted oil and gas reservoirs. The need of the hour is to offset the cost of capture by utilizing CO2 for applications in enhanced oil recovery, fertilizers, polymers, food processing, industrial gases, and liquid fuels. Lastly, environmental sustainability of the process, including the materials used and their lifecycle, should be considered while selecting the technology.
Digital enablers for carbon capture
It is imperative to identify the best possible carbon capture technology and materials for each industry, with an efficient upscaling mechanism to meet industrial and environmental requirements.
For example, solvents such as mono-ethanolamine (MEA) and di-ethanolamine (DEA) are commonly used for CO2 absorption. There exist other alternatives that may work better depending on the nature of exhaust gases. Some may be good for carbon capture but are corrosive. Similarly, different materials are utilized as sorbents, membranes, and catalysts, in case of adsorption, membrane separation, and chemical looping, respectively.
Artificial intelligence (AI) along with technologies such as process modelling, simulation, optimization, and control can lead to enhanced efficiency. Molecular simulations and machine learning algorithms can be applied not only for identifying and selecting appropriate materials but also for data-driven discovery of novel materials. Similarly, physics-based models can be utilized for complete carbon capture process synthesis and design, as well as for selection and detailed design of individual equipment through process modelling and computational fluid dynamics, and so on. Digital twins deployed during the pilot-scale testing and scale-up stages will help predict potential challenges using real-time data.