Steady-state process simulation of a 90% post-combustion CO₂ capture system using 30 wt% MEA solvent, built in ASPEN Plus and validated against various literature studies.
| Metric | Simulated | Benchmark (Source) | Error |
|---|---|---|---|
| CO₂ capture rate | 90.14% | 90% (Knudsen et al., 2009) | 0.14% |
| Reboiler duty (GJ/tonne CO₂) | 4.147 | 3.7 (Knudsen et al., 2009) | 12.08% |
| Lean loading (mol CO₂/mol MEA) | 0.3 | 0.2-0.27 (Freguia & Rochelle, 2003) | 11% |
Post-combustion capture removes CO₂ from flue gas after combustion, making it retrofittable to existing power plants. The MEA loop used in this simulation consists of four main unit operations:
- Absorber — flue gas contacts lean MEA solvent; CO₂ is chemically absorbed
- Stripper — heat drives CO₂ off the rich solvent, regenerating it for reuse
- Condenser — separates the CO₂ and Water vapor by condensing the water to liquid and recycling this feed back to the stripper
- Mixer — combines the lean recycle stream with makeup streams of water and MEA to maintain material balance
The simulation uses ASPEN Plus with the ELECNRTL property method and rate-based RadFrac columns for both the absorber and stripper, which captures the ionic chemistry (carbamate, bicarbonate, protonated MEA) and mass-transfer kinetics that equilibrium-stage models miss.
co2-capture-simulation/
├── README.md
├── lab_notebook.md ← running project log
├── aspen/
│ └── co2_capture.bkp ← ASPEN Plus backup file
├── python/
│ ├── sensitivity_analysis.ipynb
│ ├── techno_economics.ipynb
│ └── aspen_com_interface.py
├── data/
│ ├── esbjerg_validation.csv
│ └── sensitivity_results.csv
├── figures/
│ └── *.png
├── report/
│ └── co2_capture_report.pdf
└── dashboard/
└── app.py ← Streamlit dashboard
ELECNRTL (electrolyte NRTL) — required for accurate modeling of the ionic CO₂–MEA–H₂O system. Properties were imported from an AspenTech example file ‘Rate-based model of the CO2 capture process by MEA using Aspen Plus’
Rate-based RadFrac for both absorber and stripper. Rate-based modeling accounts for mass-transfer resistance between vapor and liquid phases and uses reaction kinetics directly, rather than assuming equilibrium between phases at each stage. Column configuration was based on the simulation described in Arachchige et al., 2012.
Equilibrium reactions (liquid phase): CO₂ hydration, MEA protonation, carbamate formation, bicarbonate equilibrium. Kinetic reactions: CO₂–MEA second-order forward reaction. All reactions were pulled from AspenPlus example files.
Simulated outputs (reboiler duty, lean/rich loading, column temperature profiles, capture rate) are compared with results from comparable literature.
Three parametric studies were performed using ASPEN's built-in Sensitivity tool, post-processed in Python:
- Reboiler duty vs. lean loading
- Capture rate vs. liquid-to-gas (L/G) ratio / carbon-to-solvent ratio
- Reboiler duty vs. stripper pressure
Optimization: ASPEN Optimization block minimizing reboiler duty subject to ≥90% CO₂ capture. Decision variables: FLUEGAS mass flow, specified reboiler duty in STRIPPER block
Screening-level capital and operating cost estimate (±30%) using ASPEN economic analysis. Outputs: levelized cost of CO₂ capture ($/tonne CO₂) as a function of capture rate and reboiler duty.
Arachchige, U. S. P. R., Mohsin, M., Melaaen, M. C., & Tel-Tek, P. (2012). Optimization of post combustion carbon capture process-solvent selection. International Journal of Energy and Environment (Print), 3. https://www.osti.gov/etdeweb/biblio/22106515
Aspen Technology, Inc. (2014). Rate-based model of the CO2 capture process by MEA using Aspen Plus [Software documentation]. Aspen Technology, Inc. https://www.aspentech.com
Carbon Capture | MIT Climate Portal. (n.d.). Retrieved July 23, 2026, from https://climate.mit.edu/explainers/carbon-capture
Chou, V., Iyengar, A., Shah, V., & Woods, M. (2015, June 22). Cost and Performance Baseline for Fossil Energy Plants Supplement: Sensitivity to CO2 Capture Rate in Coal-Fired Power Plants. National Energy Technology Laboratory.
Freguia, S., & Rochelle, G. T. (2003). Modeling of CO2 capture by aqueous monoethanolamine. AIChE Journal, 49(7), 1676–1686. https://doi.org/10.1002/aic.690490708
Knudsen, J. N., Jensen, J. N., Vilhelmsen, P.-J., & Biede, O. (2009). Experience with CO2 capture from coal flue gas in pilot-scale: Testing of different amine solvents. Energy Procedia, 1(1), 783–790. https://doi.org/10.1016/j.egypro.2009.01.104
Rochelle, G. T. (2009). Amine Scrubbing for CO2 Capture. Science, 325(5948), 1652–1654. https://doi.org/10.1126/science.1176731
Built as a portfolio project by Dean, a rising junior in Chemical Engineering at Vanderbilt University. Summer 2026.