Objective
In the field of CO2 transportation, safety is paramount to sustained and successful operations. This article provides a detailed overview of how advances in our understanding of flue gas impurities in CO2 are leveraged in a concise tool, we will also explore how to use and interpret the OLI CO2 Transport App. This cloud-based web application empowers engineers and operators to gain a deeper understanding of operational risks.
Disclaimer: The user interface, calculations, and results displayed in this article are from Version 1 of the OLI CO2 Transport App, which uses the Version 11.5 MSE thermodynamics databank. Other versions may appear different or present slightly distinct results due to continual developments to the software and thermodynamic databanks.
Chemistry Background
The CO2 Transport App leverages OLI’s Mixed Solvent Electrolyte (MSE) thermodynamic model and its associated species databank (V11.5). This databank includes key impurities commonly found in CO2-rich streams.
The model accurately predicts phase and chemical speciation behavior of these impurities in the CO2 phase. It also considers essential reduction-oxidation (redox) reactions between CO2 and these impurities, providing a robust foundation for the app’s calculations. OLI’s model was built in concert with experimental findings from a collaborating partner organization, the Institute for Energy Technology (IFE) in Norway.
CO2 Impurities Covered in MSE Databank (V11.5)
| H2O |
| CO |
| N2 |
| NOx |
| SOx |
| S0 |
| H2S |
| H2 |
| O2 |
| Alcohols (Methanol, MEG, DEG, TEG) |
| H2SO4 |
| HNO3 |
| Hg |
| Aldehydes (Formaldehyde, Acetaldehyde) |
| COS |
| Amines (MEA, DEA, DMEA, DMIPA, MDEA, DGA; alkyl amines, oxygenated amines) |
| NH3 and NH2CO2NH4 |
Redox Reactions Considered:
| Species Oxidation State | Redox Reaction |
| S(-2) | S-2 + O2 + H3O+ = S8 + OH- |
| S(+4) | SO3-2 + H3O+ = O2 + S8 + OH- |
| S(+6) | SO4-2 + H3O+ = O2 + S8 + OH- |
| N(+2) | NO + O2 = NO2 |
| N(+5) | NO3-1 + H3O+ = O2 + NO2 + OH- |
While pure CO2 is not corrosive, carbon capture processes often leave behind impurities that can react to form corrosive concentrated acids, posing significant risks.
The OLI CO2 Transport App provides critical insights into these impurities, offering quick and clear phase and speciation predictions. This information is crucial for determining the formation of acid phases, which puts the asset at risk of corrosion. Additionally, if elemental sulfur forms at levels that exceed its solubility in CO2, it may foul and obstruct transport equipment.
Using the OLI CO2 Transport App
Input Tab
In the Input tab, the user enters details about transport conditions (temperature and pressure) and the composition of the CO2 stream. Components are entered as moles; by entering CO2 at 1,000,000 moles, the remaining impurities can be added at their ppm(mol) levels. With this standardization, CO2 is taken to be the solvent in the system, and all other inflows will be relative to the 1 million parts (moles) of CO2. In the example below, the impurity loadings are as follows:
- H2O at 10 ppm(mol)
- O2 at 100 ppm(mol)
- H2S at 100 ppm(mol)
- SO2 at 150 ppm(mol)
- NO2 at 200 ppm(mol)
Output-Simplified Tab
After clicking the “Run” button in the Input tab, the Output-Simplified and Output-Detail tabs will populate with the calculation results.
The Output-Simplified tab presents a quick and intuitive way to interpret the calculation results with traffic light graphics. Each of the four traffic lights corresponds to one of the four phases:
- Vapor
- Liquid (Dense Phase CO2)
- Acid (ionic phase)
- Solid
A gray traffic light indicates the phase is not predicted to form. In the case below, the liquid and solid phases are not predicted to form.
A green traffic light indicates that a phase has formed, and it is not inherently concerning. However, a red traffic light indicates the presence of a concerning phase. In this example, both the vapor and acid phases are predicted, but the acid phase displays as red to signal risk. Also displayed are the volumetric or mass flowrates of each phase allowing the user to assess the relative amount of each phase forming, which is an indicator of risk, especially in acid formation.
Output-Detail Tab
This window provides granular detail on the four-phase separation, including the flow rates of each species in the vapor, liquid, and acid phases. It also identifies whether solid elemental sulfur (S8) or ice is predicted to form. Most importantly, it provides detail on the composition of each phase, allowing the user to make educated decisions on corrosion risk, in the case of acid formation, and potential decisions on impurity reduction to mitigate risks such as reducing sulfur components in the stream.
Conclusion
This article has outlined the functionalities of the OLI CO2 Transport App, demonstrating how to use it and interpret its outputs. This app enables users to quickly access critical chemistry insights to understand if their process conditions are safe for operations.