With the proliferation of initiatives and commitments to dramatically reduce greenhouse gas emissions, several common industrial processes have been identified as potential opportunities for decarbonization, due to their relatively high CO2 effluent concentrations and inability to avoid the emissions through process change. The National Energy Technology Laboratory’s study titled Cost of Capturing CO₂ from Industrial Sources evaluates nine representative industrial facilities (ammonia, ethanol, ethylene oxide, natural gas processing, coal-to-liquids, gas-to-liquids, refinery hydrogen, cement, and iron/steel) —each with CO₂ emission concentrations above that found in the flue gas streams of coal-fueled power plants (~11-16 percent) —to estimate the levelized cost of CO₂ capture. The cost of capture in each case considers the equipment required for state-of-the-art solvent-based CO₂ capture, where applicable, along with compression, dehydration, and balance of plant equipment, such as that required for heating, cooling, and power supply. For industrial sources with very high CO₂ concentrations (nearly 100 percent CO₂), CO₂ capture may only require compression and dehydration. Sensitivity analyses consider the cost implications associated with changes to financial assumptions and plant size (i.e., the amount of CO₂ available for capture) for each case. For most cases, greenfield costs (i.e., the additional cost that would be associated with including capture in a greenfield plant build) and retrofit cost implications are both considered.

The cost and performance estimate methodologies and data from the study were used to create a public Microsoft Excel tool—the Industrial Carbon Capture Retrofit Database—that allows users to estimate the cost of CO₂ capture at existing ammonia, ethanol, cement, natural gas processing, and hydrogen production facilities. The tool provides screening level estimates—additional study (e.g., a FEED study) considering the unique circumstances and requirements present at a specific facility is necessary to reduce uncertainty in support of prudent investment decisions.