FT-IR: a suitable process analytical technique for post combustion - PowerPoint PPT Presentation

FT-IR: a suitable process analytical technique for post combustion capture of CO 2 Eva Sanchez Fernandez, Annemiek van de Runstraat, Leon Geers, Earl Goetheer TNO Gas Treatment Delft, the Netherlands

1 23/5/11 TNO Gas Treatment Group Content Why PAT? Principles of FT-IR Model construction Demonstration Conclusions

2 23/5/11 TNO Gas Treatment Group Why PAT Compromising capturing efficiency: Thermal degradation of amine due to heating/cooling cycles Chemical degradation of amine due to formation heat stable salts Contamination of solution with other species in flue gas Evaporation of water from amine solution Temperature fluctuations  Optimal performance  Better process understanding necessary  But ... first step is monitoring concentrations Goal: Development of in-line monitoring system for concentrations of CO 2 , active amine, and heat stable salts

3 23/5/11 TNO Gas Treatment Group CO2 content Framework: post combustion capture of CO 2 Amine content HSS content

4 23/5/11 TNO Gas Treatment Group Measurement technique: Fourier Transform Infrared Spectroscopy Flexible  many different species In-line applicable  no “running to the lab” with samples Fast  order of a minute Non-contaminating  without addition of internal standards N Infrared Chemical bonds light absorption stretch or bend C H Model system: potassium b-alanine

5 23/5/11 TNO Gas Treatment Group Comparison potassium salt and - carbamate Potassium salt β -alanine Potassium salt β -alanine carbamate Carbonate Conclusion: No straight forward dependency species and FT-IR peaks

6 23/5/11 TNO Gas Treatment Group From IR spectra to concentrations? [Amine - ] 2- ] [CO 3 ? - ] [HCO 3 - ] [Amine-CO 2 [Heat Stable Salts] [ ... ? ... ] • Absorption is wavelength dependent  peaks of specific bonds may overlap • Water absorbs over broad band  might obscure peaks of other species • Chemical reactions  peak shifting or disappearance • Temperature fluctuations affect spectra

7 23/5/11 TNO Gas Treatment Group Partial Least Squares Model – Creation 1 2 3 ... n ... X T YY T X Spectra (X) Covariance matrix … … # # Y1 Y2 Yp 1 2 p … … 1 1 1.31 1.31 2.60 2.60 12.3 12.3 … … 2 2 2.33 2.33 6.20 6.20 23.5 23.5 Basis functions : : : : : : : : … … n n 0.01 0.01 9.99 9.99 16.9 16.9 Concentrations (Y)

8 23/5/11 TNO Gas Treatment Group Partial Least Squares Model – Regression + error = T 1 * + .. + T m * + T 2 * Coefficients T 1..m contain information to calculate species concentrations More basis functions  better fit BUT more rigid model Caveat: Non-informative correlations may be present in spectra  preprocessing necessary

9 23/5/11 TNO Gas Treatment Group Experiments Calibration + validation 28 Stock solutions were created of amine in 4 different concentrations CO 2 and SO 2 were added with a bubbler CO 2 concentration measured with phosphoric acid method IR Spectra collected with FTIR spectrometer and ATR flowcell Testing 7 samples from pilot plant capture installation of both lean and rich streams

10 23/5/11 TNO Gas Treatment Group C-O stretch Results – Basis functions Amine peaks (e.g.H-N-H bend) N-H stretch N-H, but also S-O

11 23/5/11 TNO Gas Treatment Group Calibration and validation matrices (37) (15)

12 23/5/11 TNO Gas Treatment Group Results – Validation 2.5 Reconstructed Amine conc. (M) Reconstructed CO2 conc. (M) 6 2 5 1.5 4 1 3 0.5 2 0 1 0 0.5 1 1.5 2 2.5 1 2 3 4 5 6 Measured Amine concentration (M) Measured CO2 concentration (M) Reconstructed SOx conc. (M) 1 0.8 0.6 0.4 0.2 0 0 0.2 0.4 0.6 0.8 1 Measured SOx concentration (M)

13 23/5/11 TNO Gas Treatment Group Results – Pilot plant RMS Error: ~0.04M

14 23/5/11 TNO Gas Treatment Group Results pilot tests

15 23/5/11 TNO Gas Treatment Group Microplant pilot equipped with on-line FT-IR

16 23/5/11 TNO Gas Treatment Group Test 1: 100 spectra recorded on-line show stable operation Colour intensity Time is measure of peak intensity

17 23/5/11 TNO Gas Treatment Group Test 2: process event identification CO 2 + SO 2 SO 2 Water replenishement

18 23/5/11 TNO Gas Treatment Group Test 3: Model robustness CO 2 CO 2 + SO 2 CO 2 + SO 2 + NO x

19 23/5/11 TNO Gas Treatment Group Test 3: Model robustness – SO 2 in rich stream CO 2 CO 2 + SO 2 CO 2 + SO 2 + NO x

20 23/5/11 TNO Gas Treatment Group Conclusions Methodology for reconstructing solvent concentration from FT-IR concentrations developed Accuracy of predictions on-line within 10% For calibrated species in calibrated range Model can be trained to discard noise from contaminations of other species Process event identification possible using this tool  extra input of information for process control FT-IR is a suitable process analytical tool

21 23/5/11 TNO Gas Treatment Group Acknowledgement: Ralph Joh and Rudiger Schneider (Siemens)