Minimize Energy Consumption of CO2 Release in a Flow Electrolyzer By Optimizing Direct Air Capture Solvents

Abstract

Under the 2015 Paris Agreement, almost 200 nations have committed to the global goal of limiting the rise in average temperatures to 2.0 °C above preindustrial levels, with an even more ambitious aim of striving for 1.5 °C. Achieving the 1.5 °C objective requires a 45% reduction in global greenhouse gas emissions by 2030, ultimately reaching net-zero emissions by 2050. Numerous industries are increasingly making commitments to combat climate change by minimizing their CO2 emissions. However, certain sectors face challenges due to the current high costs associated with emissions reduction through available technologies, though these costs are expected to decrease over time. Moreover, in specific industries like cement production, there are emissions sources that cannot be entirely eliminated, such as those arising from the inherent calcination process. Given these constraints, realizing the emissions reduction pathway to the 1.5 °C target requires the adoption of negative emissions processes, including technologies like direct air capture (DAC), to actively remove CO2 from the atmosphere.The operational concept of the DAC process explored in this study is based on the utilization of both the solvent-based method and alkaline water electrolysis. This involves regenerating the solvent through pH fluctuations generated by a carbonate electrolyzer. As depicted in Figure 1, the consumption of OH- ions during O2 evolution leads to a decrease in pH at the anolyte loop, while the production of OH- ions through water splitting causes an increase in pH at the catholyte loop. Consequently, the lowered pH environment facilitates the release of CO2 gas from dissolved carbon species such as CO32-, while the heightened pH environment promotes the formation of alkaline hydroxides for carbon capture in an air absorber.In this work, we will aim to analyze the energy consumption per mole of CO2 released from the anolyte loop of a flow electrolyzer. Utilizing a combination of theoretical predictions and experimental validations, significant insights were obtained for optimizing the DAC solvent. This optimization involves minimizing energy consumption by adjusting alkalinity levels and incorporating supporting electrolytes. Figure 1