Estimation of CO₂ emissions from petroleum refineries based on the total operable capacity for carbon capture applications

Abstract

Carbon capture and storage processes are sought to play a major role in reducing carbon emissions from large point sources. Petroleum refineries, in particular, produce several streams that are CO2-rich, including fluidized catalytic cracking, steam methane reforming, and natural gas combustion processes that generate heat for refinery operations. Of these, stationary combustion processes account for nearly two-thirds of all CO2 generated within a refinery. In this work, a regression analysis was performed to correlate the size and power requirements for the combined capture, compression, and dehydration process dependent upon a refinery's operating capacity. Refinery capacity and CO2 generation data from 128 U.S. refineries were normalized, and a linear regression model was developed. A capture, compression, and dehydration process model was developed using Aspen HYSYS for delivery of CO2 (10–15 wt. % in steam) to pipeline specifications (500 ppm H2O, 15.2 MPa). Predicted CO2 emissions were 0.1 to 7.7 % of actual emissions, depending on whether a refinery had a low, medium, or high carbon emission/capacity ratio.

Keywords

• Carbon
• Capture
• Compression
• Dehydration
• Regression
• Refinery