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KINETIC STUDIES ON CATALYST-AIDED ABSORPTION AND DESORPTION IN
A BENCH-SCALE POST-COMBUSTION CO2 CAPTURE PILOT PLANT USING A
NOVEL SOLVENT BLEND
A Thesis
Submitted to the Faculty of Graduate Studies and Research
In Partial Fulfillment of the Requirements
For the Degree of
Master of Applied Science
In
Process Systems Engineering
University of Regina
By
Daniel Boafo Afari
Regina, Saskatchewan
August 2018
Copyright 2018: D.B. Afari
UNIVERSITY OF REGINA
FACULTY OF GRADUATE STUDIES AND RESEARCH
SUPERVISORY AND EXAMINING COMMITTEE
Daniel Boafo Afari, candidate for the degree of Master of Applied Science in ProcessSystems Engineering, has presented a thesis titled, Kinetic Studies on Catalyst-Aided Absorption and Desorption in a Bench-Scale Post-Combustion CO2 Capture Pilot Plant Using A Novel Solvent Blend, in an oral examination held on August 22, 2018.The following committee members have found the thesis acceptable in form and content,and that the candidate demonstrated satisfactory knowledge of the subject material.
External Examiner:
Supervisor:
Committee Member:
Committee Member:
Chair of Defense:
Dr. Fanhua Zeng, Petroelum Systems Engineering
Dr. Raphael Idem, Process Systems Engineering
*Dr. Hussameldin Ibrahim, Process Systems Engineering
Dr. Teeradet Supap, Adjunct
Dr. Andrei Volodin, Department of Mathematics & Statistics
*Not present at defense
i
ABSTRACT
A total of seven solid base/alkaline catalysts comprising BaCO3, CaCO3, Ca(OH)2,
Cs2O/α-Al2O3, Cs2O/γ-Al2O3, K/MgO and Hydrotalcite were screened on a semi-batch
scale to select the most suitable for CO2 absorption into a novel aqueous solvent,
BEA/AMP. The selected catalyst was incorporated into the absorber section of a bench-
scale pilot plant and its kinetic performance was evaluated. Intrinsic kinetic data were
extracted and kinetic parameters were determined. Both cases of reversible and
irreversible reactions of CO2 with the aqueous BEA/AMP solvent were analysed. An
activation energy, Ea of 5.67E+04 J/mol and 3.40E+04 J/mol were obtained for the
reversible and irreversible cases respectively. A reaction order of 2 with respect to CO2
for the irreversible case shows a higher dependency of the reaction rate on CO2 with the
introduction of a heterogeneous catalyst and is a further indication of the complexity of
the reaction as a third phase (solid) is introduced. A parity plot showing the degree of
correlation between the experimental and predicted rate gave an AAD of 14.1%. Also, the
performance of the novel solvent was compared with conventional Monoethanolamine
(MEA) and blended Monoethanolamine (MEA)/n-Methyldiethanolamine (MDEA) in the
presence and absence of a solid acid catalyst (HZSM-5). The results showed that the novel
solvent (4M BEA-AMP) outperformed conventional 5M MEA and the 7M MEA-MDEA
blend despite its lower molarity. For the novel solvent, Parametric Sensitivity Analysis
(PSA) was conducted to investigate the impact of each independent process parameter on
the CO2 conversion. It was observed that the most influential parameter was the absorber
catalyst composition, followed by the gas flowrate and lean amine loading. The least
influential was seen to be the desorber catalyst composition. Preliminary economic
ii
analysis showed that the novel solvent, BEA-AMP recorded the least annual operating
cost when compared with conventional MEA and MEA-MDEA solvents. A separate
analysis on the BEA-AMP system revealed that the introduction of absorber catalyst
resulted in lowering the operating costs by about 40% using the base case of no absorber
catalyst as reference. Employing catalysts in Post-combustion capture helps in truncating
the associated operating costs and greatly contributes to making it a long term viable
technology.
iii
ACKNOWLEDGEMENTS
I would like to foremost thank God for the gift of life and His continual grace that
spurred me on during my studies.
I would also like to express my sincere gratitude to my Supervisor, Dr. Raphael
Idem for the wonderful opportunity granted me to work under Him. His invaluable
guidance and contributions throughout my research has seen me through the successful
completion of my program. I would also like to thank Dr. Teeradet Supap for his inputs
and advice during our research group meetings. I would also like to acknowledge Dr.
Ibrahim Hussameldin for his indispensable inputs in the Advanced Reaction Engineering
course. The knowledge base I acquired in His class was put to great use in my research.
I would also like to appreciate Mr. James Coker, my immediate research colleague
who was a shoulder to lean on during our challenging times during this research. Also,
many thanks to the research group members of Clean Energy Technologies Research
Institute (CETRI) for their constructive criticisms and suggestions during our research
group meetings. Special thanks go to Mr. Chikezie Nwaoha and Ms. Jessica Narku-Tetteh
in this regard. I would like to appreciate Mr. Benjamin Decardi-Nelson and his research
colleagues for providing training on the pilot plant and offering vital help whenever I
needed it.
I would also like to appreciate the financial support provided by the Natural
Science and Engineering Research Council of Canada (NSERC), Government of
Saskatchewan and the Faculty of Graduate Studies and Research (FGSR).
Finally, I would like to express my warmest gratitude to my family for their
unflinching support and continuous encouragement throughout my research.
iv
TABLE OF CONTENTS
ABSTRACT ................................................................................................................... i
ACKNOWLEDGEMENTS .......................................................................................... iii
TABLE OF CONTENTS .............................................................................................. iv
LIST OF TABLES ........................................................................................................ xi
LIST OF FIGURES .................................................................................................... xiii
NOMENCLATURE ..................................................................................................... xx
CHAPTER 1: INTRODUCTION ....................................................................................1
1.1 The drive for CO2 capture and Sequestration .......................................................1
1.2 Overview of Capture Technologies ......................................................................4
1.2.1 Post-Combustion Capture .................................................................................5
1.2.1.1 Absorption Processes .....................................................................................5
1.2.1.2 Adsorption Processes .....................................................................................6
1.2.1.3 Membrane Filtration ......................................................................................7
1.2.1.4 Cryogenic Separation .....................................................................................8
1.3 Drawbacks of Chemical Absorption based Post-Combustion Capture ..................8
1.4 Research Problem ................................................................................................9
1.5 Research Objectives and Scope of Work ............................................................ 14
1.6 Thesis Organization ........................................................................................... 15
v
CHAPTER 2: LITERATURE REVIEW ....................................................................... 16
2.1 Solvents ............................................................................................................. 16
2.2 CO2 Absorption Kinetics Data ........................................................................... 20
Table 2.1Rate constants for CO2 absorption into some blended aqueous AMP
systems .................................................................................................................. 24
2.3 Solvent Chemistry ............................................................................................... 25
2.3.1 Reaction of CO2 with aqueous primary and secondary amines ........................ 26
2.3.2 Reaction of CO2 with aqueous tertiary amines ................................................ 26
2.3.3 Reaction rate dependence on AMP ................................................................. 27
2.3.4 Reaction rate dependence on BEA .................................................................. 28
2.3.5 Reaction rate for uncatalyzed CO2 absorption into aqueous AMP+BEA system
.................................................................................................................................. 28
2.4 Catalysis in solvent-based CO2 Capture ............................................................. 29
Table 2.2 Activation energies and Frequency factors for catalyst-aided desorption of
CO2 from MEA and MEA-MDEA (Akachuku, 2016). ........................................... 32
2.4.1 Heterogeneous alkaline/base catalysts ............................................................. 33
2.4.2 Role of Catalyst in Absorption ........................................................................ 34
CHAPTER 3: EXPERIMENTAL SECTION ................................................................ 39
3.1 Laboratory Health and Safety Measures............................................................. 39
3.2 Materials and Equipment ................................................................................... 40
vi
3.3 Catalyst Preparation........................................................................................... 40
3.4 Catalyst Characterization ................................................................................... 42
3.5 Catalyst Screening ............................................................................................. 43
Table 3.1Operating conditions of the semi-batch catalyst screening experiments ... 45
3.6 Pilot plant .......................................................................................................... 46
Table 3.2 Typical operating conditions of bench-scale pilot plant system ............... 51
CHAPTER 4: RESULTS AND DISCUSSION ............................................................. 52
4.1 Catalyst Characterization ..................................................................................... 52
4.2 Catalyst Screening Results (Semi-batch runs) ...................................................... 61
Table 4.1. Initial rate of absorption for solid alkaline catalysts studied ................... 69
4.3 Pilot Plant Studies ............................................................................................... 73
4.3.1 Kinetic Performance of BEA-AMP, MEA-MDEA and MEA (Effect of solid acid
catalyst)..................................................................................................................... 73
Table 4.2 Validation operating conditions for 5M MEA for comparison with
Decardi-Nelson (2016) .......................................................................................... 77
4.3.1.1 Absorber performance ................................................................................... 78
4.3.1.1 Desorber performance.................................................................................... 79
Table 4.3 Solvent lean loading of solvents studied ................................................. 87
4.3.2 Kinetic Performance of BEA-AMP (Effect of Solid alkaline and acid catalysts)
.................................................................................................................................. 88
vii
Table 4.4 Absorber and Desorber Configurations ................................................... 90
Table 4.5 Lean and Rich loadings for the different system configurations .............. 96
4.3.3 Catalytic Absorption Kinetic Studies ................................................................ 97
4.3.3.1 Evaluation of Heat Transfer Limitation .......................................................... 97
4.3.3.2 Evaluation of Mass Transfer Limitation ....................................................... 100
Table 4.6 Summary of Heat and Mass transfer limitations. .................................. 102
4.3.3.2 Determination of Reaction Rate ................................................................... 103
4.3.3.3 Parameter Estimation of Power law model ................................................... 105
Table 4.7 Experimental Kinetic Data ................................................................... 108
Table 4.8 Summary of Parameter Estimates for reversible and irreversible power
law models. ......................................................................................................... 109
4.3.3.4 Effect of Process Parameters on CO2 conversion........................................ 111
4.3.3.4.1 Effect of Catalyst weight (W/FA0) ............................................................. 111
4.3.3.4.2 Effect of lean loading .............................................................................. 114
Table 4.9 CO2 fractional conversion at solvent lean loadings of 0.2, 0.33 and 0.42
for various absorber catalyst weights (Absorber inlet temperature: 300C, Absorber
pressure: 1 atm, Gas flowrate: 15 slpm, Amine flowrate: 60 ml/min, Amine
concentration: 2M/2M BEA/AMP) ...................................................................... 116
4.3.3.4.3 Effect of Solvent flowrate ....................................................................... 118
4.3.3.4.4 Effect of Solvent concentration ratio ....................................................... 120
4.3.3.4.5 Effect of Gas flowrate ............................................................................. 128
viii
4.3.3.4.6 Effect of Absorber inlet temperature ....................................................... 131
4.3.3.4.7 Effect of Absorber Catalyst composition (K loading) .............................. 135
Table 4.10 Structural characterization of K-loaded MgO catalysts ....................... 138
4.3.3.4.7.1 Catalyst Deactivation ............................................................................. 140
4.3.3.4.8 Effect of Desorber catalyst (HZSM-5/ γ-Al2O3) ratio .............................. 143
CHAPTER 5: PARAMETRIC SENSITIVITY ANALYSIS, CONVERSION
CORRELATIONS AND PRELIMINARY ECONOMIC ANALYSIS ........................ 146
5.1 Parametric Sensitivity Analysis ......................................................................... 146
Table 5.1 Impact of various independent process parameters on CO2 conversion. 151
5.2 Conversion Correlation...................................................................................... 152
Table 5.2 Parameter range for developed conversion correlation .......................... 154
5.3 Statistical analysis for catalyst characteristics .................................................... 155
5.4 Preliminary Economic Analysis ......................................................................... 157
Table 5.3 Base case conditions used for Preliminary Economic Analysis ............. 161
CHAPTER 6: CONCLUSIONS AND RECOMMENDATIONS ................................ 162
6.1 Conclusions ....................................................................................................... 162
6.2 Recommendations ............................................................................................. 166
LIST OF REFERENCES ............................................................................................ 167
APPENDICES ............................................................................................................ 193
ix
APPENDIX A1: Standard Operating Procedure for running the CO2 capture plant for
kinetic data .............................................................................................................. 193
APPENDIX A2: Determination of Solvent Concentration and Loading ................... 198
APPENDIX B: Estimation of Heat and Mass Transfer Limitations .......................... 201
Appendix B1: Calculation of Diffusion coefficient of CO2 in BEA/AMP (DAB) and
effective diffusivity (Deff) ........................................................................................ 201
Appendix B2: Calculation of Mass transfer coefficient (kc) ..................................... 203
Appendix B3: Calculation of Effective thermal conductivity (λeff) ........................... 205
Appendix B4: Calculation of Heat transfer coefficient (h) ....................................... 206
Appendix B5: Determination of internal pore heat transfer resistance
(∆𝑻𝒎𝒂𝒙, 𝒑𝒂𝒓𝒕𝒊𝒄𝒍𝒆)............................................................................................... 207
Appendix B6: Determination of external film heat transfer resistance ...................... 208
Appendix B7: Determination of Mears Criteria for heat transport limitation ............ 209
Appendix B8: Determination of Weisz-Prater Criterion for internal mass diffusion . 210
Appendix B9: Determination of External film diffusion limitation .......................... 211
Appendix B10: Determination of Mears Criterion for External film diffusion limitation
................................................................................................................................ 212
APPENDIX C: Calculation of experimental rate of reaction .................................... 213
Appendix C1: Rate of reaction based on volume of reactor...................................... 213
Appendix C2: Rate of reaction based on weight of catalyst ..................................... 216
Appendix C3: Determination of exit flowrates......................................................... 216
x
APPENDIX D: Non-Linear Regression (NLREG) code for Power law model ......... 221
APPENDIX E1: Regression results for Conversion Correlation............................... 225
APPENDIX E2: Regression results for Catalyst properties statistical analysis ......... 226
APPENDIX F: Calculations for Preliminary Economic Analysis ............................. 227
xi
LIST OF TABLES
Table 2.1Rate constants for CO2 absorption into some blended aqueous AMP systems . 24
Table 2.2 Activation energies and Frequency factors for catalyst-aided desorption of CO2
from MEA and MEA-MDEA (Akachuku, 2016)........................................................... 32
Table 3.1Operating conditions of the semi-batch catalyst screening experiments .......... 45
Table 3.2 Typical operating conditions of bench-scale pilot plant system ...................... 51
Table 4.1. Initial rate of absorption for solid alkaline catalysts studied .......................... 69
Table 4.2 Validation operating conditions for 5M MEA for comparison with Decardi-
Nelson (2016) ............................................................................................................... 77
Table 4.3 Solvent lean loading of solvents studied ........................................................ 87
Table 4.4 Absorber and Desorber Configurations .......................................................... 90
Table 4.5 Lean and Rich loadings for the different system configurations ..................... 96
Table 4.6 Summary of Heat and Mass transfer limitations........................................... 102
Table 4.7 Experimental Kinetic Data .......................................................................... 108
Table 4.8 Summary of Parameter Estimates for reversible and irreversible power law
models. ....................................................................................................................... 109
Table 4.9 CO2 fractional conversion at solvent lean loadings of 0.2, 0.33 and 0.42 for
various absorber catalyst weights (Absorber inlet temperature: 300C, Absorber pressure:
1 atm, Gas flowrate: 15 slpm, Amine flowrate: 60 ml/min, Amine concentration: 2M/2M
BEA/AMP) ................................................................................................................. 116
Table 4.10 Structural characterization of K-loaded MgO catalysts .............................. 138
Table 5.1 Impact of various independent process parameters on CO2 conversion. ....... 151
Table 5.2 Parameter range for developed conversion correlation ................................. 154
xii
Table 5.3 Base case conditions used for Preliminary Economic Analysis .................... 161
xiii
LIST OF FIGURES
Figure 1.1 World Energy Consumption based on Energy Source. (U.S. Energy
Information Administration, International Energy Agency, 2017) ...................................3
Figure 1.2 Greenhouse gas emissions of reporting facilities in Canada (Environment and
Climate Change Canada, 2018). ......................................................................................3
Figure 2.1 Molecular Structure of amines studied in this work ...................................... 19
Figure 3.1 Experimental set-up of semi-batch run for catalyst screening ....................... 45
Figure 3.2 Schematic representation of bench-scale pilot plant experimental set-up ...... 49
Figure 3.3 Absorber and desorber columns packing and catalyst bed arrangement ........ 50
Figure 4.1 XRD pattern of BaCO3 catalyst .................................................................... 55
Figure 4.2 XRD pattern of CaCO3 catalyst .................................................................... 55
Figure 4.3 XRD pattern of Ca(OH)2 catalyst ................................................................. 56
Figure 4.4 XRD pattern of Hydrotalcite catalyst ........................................................... 56
Figure 4.5 XRD pattern of Cs2O/ γ-Al2O3 catalyst ........................................................ 57
Figure 4.6 XRD pattern of Cs2O /α-Al2O3 catalyst ........................................................ 57
Figure 4.7 XRD pattern of K/MgO catalyst ................................................................... 58
Figure 4.8 SEM images of catalysts studied (a) BaCO3 (b) CaCO3 (c) Ca(OH)2 (d)
Hydrotalcite (e) Cs2O/γ-Al2O3 (f) Cs2O/α-Al2O3 (g) K/MgO ........................................ 59
Figure 4.9 TPD profiles of catalysts studied .................................................................. 60
Figure 4.10 TPD profile of Cs2O/γ-Al2O3 ..................................................................... 60
Figure 4.11 CO2 absorption profiles of various catalysts understudied .......................... 62
Figure 4.12 Linear portion of CO2 absorption profiles ................................................... 63
Figure 4.13 Initial rate determination of blank run (solvent only) .................................. 64
xiv
Figure 4.14 Initial rate determination of CaCO3 ............................................................ 64
Figure 4.15 Initial rate determination of BaCO3 ............................................................ 65
Figure 4.16 Initial rate determination of Ca(OH)2 ......................................................... 65
Figure 4.17 Initial rate determination of Cs2O/γ-Al2O3 .................................................. 66
Figure 4.18 Initial rate determination of Cs2O/ α-Al2O3 ................................................ 66
Figure 4.19 Initial rate determination of Hydrotalcite .................................................... 67
Figure 4.20 Initial rate determination of K/MgO ........................................................... 67
Fig 4.21 Initial rate determination of K/MgO + Colloidal Silica binder ......................... 68
Fig. 4.22 Initial rate determination of K/MgO+γ-Al2O3 binder ...................................... 68
Figure 4.23 Validation of CO2 concentration profile along absorber for 5M MEA by
comparison with Decardi-Nelson (2016) ....................................................................... 76
Figure 4.24 Validation of temperature profile along absorber for 5M MEA by
comparison with Decardi-Nelson (2016) ....................................................................... 76
Figure 4.25 Validation of temperature profile along desorber for 5M MEA by
comparison with Decardi-Nelson (2016) ....................................................................... 77
Figure 4.26 CO2 absorption rates of MEA, MEA-MDEA and BEA-AMP with and
without HZSM-5 in desorber ........................................................................................ 82
Figure 4.27 CO2 desorption rates of MEA, MEA- MDEA and BEA-AMP with and
without HZSM-5 in desorber ........................................................................................ 82
Figure 4.28. CO2 absorption efficiency of MEA, MEA- MDEA and BEA-AMP with and
without HZSM-5 in desorber ........................................................................................ 83
Figure 4.29. CO2 cyclic capacity of MEA, MEA- MDEA and BEA-AMP with and
without HZSM-5 in desorber ........................................................................................ 84
xv
Figure 4.30 CO2 concentration profile along absorber ................................................... 85
Figure 4.31 Temperature profile along absorber ............................................................ 86
Figure 4.32 Amine Selection Chart ( Narku-Tetteh et al., 2017) .................................... 87
Figure 4.33 CO2 concentration profile along absorber for the different system
configurations ............................................................................................................... 93
Figure 4.34 Temperature profile along absorber for the different system configurations 94
Figure 4.35 CO2 absorption rates for the different system configurations ...................... 95
Figure 4.36 CO2 desorption rates for the different system configurations ...................... 95
Figure 4.37 XCO2 versus W/FCO20 at different temperatures and CO2/Amine molar
ratios........................................................................................................................... 104
Figure 4.38 Parity plot of predicted rate versus experimentally observed rate .............. 110
Figure 4.39 Effect of catalyst weight (W/FA0) on CO2 conversion (Absorber inlet
temperature: 300C, Absorber pressure: 1atm, Amine concentration: 2M/2M BEA/AMP,
Absorber inlet lean loading: 0.42, gas flowrate: 15 slpm, amine flowrate: 60 ml/min,
Desorber temperature: 75oC) ....................................................................................... 113
Figure 4.40 Cyclic capacity and Removal efficiency at different catalyst weights
(Absorber inlet temperature: 300C, Absorber pressure: 1atm, Amine concentration:
2M/2M BEA/AMP, Amine flowrate: 60 ml/min, gas flowrate: 15 slpm, Desorber
temperature: 85oC) ...................................................................................................... 113
Figure 4.41 Effect of lean loading on CO2 conversion. (Absorber inlet temperature:
300C, Absorber pressure: 1 atm, Gas flowrate: 15 slpm, Amine flowrate: 60 ml/min,
Amine concentration: 2M/2M BEA/AMP, Catalyst weight of 150g). .......................... 116
xvi
Figure 4.42 Absorber temperature profiles at lean loadings of 0.20, 0.33 and 0.42
(Absorber inlet temperature: 300C, Gas flowrate: 15 slpm, Amine flowrate: 60 ml/min.,
Amine concentration: 2M/2M BEA/AMP, Catalyst weight: 50g). ............................... 117
Figure 4.43 Cyclic capacity and Removal efficiency at different lean loadings (Absorber
inlet temperature: 300C, Absorber pressure: 1atm, Amine concentration: 2M/2M
BEA/AMP, Amine flowrate: 60 ml/min, gas flowrate: 15 slpm, Catalyst weight: 150g)
................................................................................................................................... 117
Figure 4.44 Effect of solvent flowrate on CO2 conversion (Absorber inlet temperature:
300C, Absorber pressure: 1atm, Amine concentration: 2M/2M BEA/AMP, Absorber inlet
lean loading: 0.33, gas flowrate: 15 slpm, amine flowrate: 60 ml/min, Desorber
temperature: 85oC) ...................................................................................................... 119
Figure 4.45 Cyclic capacity and Removal efficiency at different solvent flowrates
(Absorber inlet temperature: 300C, Absorber pressure: 1atm, Amine concentration:
2M/2M BEA/AMP, Absorber inlet lean loading: 0.33, gas flowrate: 15 slpm, Desorber
temperature: 85oC, Catalyst weight: 150g) .................................................................. 119
Figure 4.46 Effect of solvent concentration ratio on CO2 conversion (Absorber inlet
temperature: 300C, Absorber pressure: 1atm, Gas flowrate: 15 slpm, Amine flowrate: 60
ml/min, Desorber temperature: 85oC, *Total amine concentration BEA/AMP: 4M) .... 122
Figure 4.47 Dynamic viscosities of unloaded solvent for different concentration ratios
(BEA:AMP) ............................................................................................................... 122
Figure 4.48 Densities of loaded 1.5M BEA/ 2.5M AMP solvent. ................................ 123
Figure 4.49 Dynamic viscosities of loaded 1.5M BEA/ 2.5M AMP solvent ................ 123
Figure 4.50 Densities of loaded 2M BEA/ 2M AMP solvent. ...................................... 124
xvii
Figure 4.51 Dynamic viscosities of loaded 2M BEA/ 2M AMP solvent ...................... 124
Figure 4.52 Densities of loaded 2.5M BEA/ 1.5M AMP solvent. ................................ 125
Figure 4.53 Dynamic viscosities of loaded 2.5M BEA/ 1.5M AMP solvent ................ 125
Figure 4.54 Densities of loaded 3M BEA/ 1M AMP solvent. ...................................... 126
Figure 4.55 Dynamic viscosities of loaded 3M BEA/ 1M AMP solvent ...................... 126
Figure 4.56 Cyclic capacity and Removal efficiency at different concentration ratios
(Absorber inlet temperature: 300C, Absorber pressure: 1atm, Absorber inlet lean loading:
0.33, gas flowrate: 15 slpm, Amine flowrate: 60 ml/min, Desorber temperature: 85oC,
Catalyst weight: 150g) ................................................................................................ 127
Figure 4.57 Effect of Gas flowrate on CO2 conversion (Absorber inlet temperature: 300C,
Absorber pressure: 1atm, Amine concentration: 2M/2M BEA/AMP, amine flowrate: 60
ml/min, Desorber temperature: 85oC, Catalyst weight: 50g) ........................................ 129
Figure 4.58 Temperature Profile for variation in gas flowrate (Absorber inlet
temperature: 300C, Absorber pressure: 1atm, Amine concentration: 2M/2M BEA/AMP,
amine flowrate: 60 ml/min, Desorber temperature: 85oC, Catalyst weight: 50g) .......... 129
Figure 4.59 Cyclic capacity and Removal efficiency at different gas flowrates (Absorber
inlet temperature: 300C, Absorber pressure: 1atm, Amine concentration: 2M/2M
BEA/AMP, Absorber inlet lean loading: 0.33, Amine flowrate: 60 ml/min, Desorber
temperature: 85oC, Catalyst weight: 50g) .................................................................... 130
Figure 4.60 Effect of Absorber inlet temperature on CO2 conversion (Absorber pressure:
1atm, Gas flowrate: 15 slpm, Amine concentration: 2M/2M BEA/AMP, amine flowrate:
60 ml/min, Desorber temperature: 85oC) ..................................................................... 133
xviii
Figure 4.61 Temperature Profile for variation in inlet temperature (Absorber pressure:
1atm, Amine concentration: 2M/2M BEA/AMP, Gas flowrate: 15 slpm, amine flowrate:
60 ml/min, Desorber temperature: 85oC, Catalyst weight: 150g) ................................. 133
Figure 4.62 Cyclic capacity and Removal efficiency at different absorber inlet
temperatures (Absorber pressure: 1atm, Amine concentration: 2M/2M BEA/AMP, Gas
flowrate: 15 slpm, Amine flowrate: 60 ml/min, Desorber temperature: 85oC, Catalyst
weight: 150g) .............................................................................................................. 134
Figure 4.63 Effect of Catalyst composition on CO2 conversion (Absorber inlet
temperature: 300C, Absorber pressure: 1atm, Gas flowrate: 15 slpm, Amine
concentration: 2M/2M BEA/AMP, amine flowrate: 60 ml/min, Desorber temperature:
85oC, Catalyst weight: 150g) ...................................................................................... 137
Figure 4.64 Cyclic capacity and Removal efficiency at different K loadings (Absorber
pressure: 1atm, Amine concentration: 2M/2M BEA/AMP, Gas flowrate: 15 slpm, Amine
flowrate: 60 ml/min, Desorber temperature: 85oC, Catalyst weight: 150g) .................. 137
Figure 4.65 XRD pattern for K/MgO catalysts with different K loadings on MgO ...... 138
Figure 4.66 SEM images of different K loadings on MgO (a) 0% (b) 0.5% (c) 1% (d) 3%
(e) 5% (f) 10% ............................................................................................................ 139
Figure. 4.67 XRD pattern of 1%K/MgO after run ....................................................... 142
Figure 4.68 Effect of varying desorber catalyst ratio (HZSM-5/γ-Al2O3) on CO2
conversion (Absorber inlet temperature: 30oC, Absorber pressure: 1atm, Amine
concentration: 2M/2M BEA/AMP, Gas flowrate: 15 slpm, Amine flowrate: 60 ml/min,
Desorber temperature: 85oC, Total catalyst weight: 150g) ........................................... 145
xix
Figure 4.69 Cyclic capacity and Removal efficiency for varying desorber catalyst
(HZSM-5/γ-Al2O3) ratio (Absorber inlet temperature: 30oC, Absorber pressure: 1atm,
Amine concentration: 2M/2M BEA/AMP, Gas flowrate: 15 slpm, Amine flowrate: 60
ml/min, Desorber temperature: 85oC, Total catalyst weight: 150g) .............................. 145
Figure 5.1 Parity plot of Predicted and experimental conversion for the conversion
correlation. ................................................................................................................. 156
Figure 5.2 Parity plot of Predicted conversion and experimental conversion for catalyst
properties statistical analysis. ...................................................................................... 156
Fig 5.3 Annual cost incurred for the different solvent systems .................................... 160
Fig 5.4 Annual cost incurred for the different parameter variations for BEA/AMP system
................................................................................................................................... 160
xx
NOMENCLATURE
AAD – average absolute deviation
AMP – 2-Amino-2-methyl-1-propanol
[𝐴] – Concentration of species, mol/dm3
BEA – Butyl ethanolamine
CO2 in – CO2 composition in the inlet gas
CO2 out – CO2 composition in outlet gas
𝐶𝑤𝑝,𝑖𝑝𝑑 – Weisz–Prater criterion for internal pore diffusion
d – internal diameter of reactor, m
dp – diameter of particle, mm
D – diffusivity coefficient, m2 s−1
Ea – activation energy, J mol−1
𝐹i – Molar flow rate of species i mol min−1
Δ𝐻𝑟𝑥𝑛 – Heat of reaction, J mol-1
k – rate constant
kc – mass transfer coefficient, m2 s−1
k0 – pre-exponential or frequency factor
L - length of catalyst bed, m
MEA – monoethanolamine
MDEA – Methyldiethanolamine
P – pressure, atm
R – radius of the catalyst bed, m
ri – rate of reaction based on a particular species, mol gcat−1 min−1
xxi
R – universal gas constant, kJ kmol−1 K−1
Rc – radius of catalyst particle, m
T – temperature, K
V – volume of reactor, m3
W – weight of catalyst, g
(𝑊/𝐹io) – Contact time, min
Xi – conversion of component i
Greek Letters
∆ - gradient
𝜀 – Porosity
𝜆 – Thermal conductivity KJ m−1𝑠−1𝐾−1
𝜇 – Viscosity
𝜌𝑏 – bulk density kg m−3
𝜌𝑐 – particle density, kg m−3
𝜏 – Tortuosity factor
Superscripts
Am – amine
Lean – solution lean in CO2
n – reaction order with respect to CO2
rich – solution rich in CO2
In – entering the reactor
xxii
Out – exiting the reactor
Subscripts
𝑏 – Bulk
𝑐 – Catalyst
𝑝 – Pellet or particle
𝑒𝑓𝑓 – Effective
𝑖𝑝𝑑 – Internal pore diffusion
𝑜𝑏𝑠 – Observed
1
CHAPTER 1: INTRODUCTION
1.1 The drive for CO2 capture and Sequestration
The escalating energy demand across the globe cannot only be attributed to the
world’s fast-growing population but also to industrialization as well as the sustenance of
booming economies and their increased liberty to obtain marketed energy. Majority of the
world’s energy needs is projected to be met by fossil fuels, despite the accelerated growth
in both renewable and nuclear energy (International Energy Outlook, 2017). Figure 1.1
shows the world’s energy consumption by energy source. The figure shows that petroleum,
natural gas and coal are consumed in the largest quantities.
Despite its huge contribution as a major source of energy, the use of fossil fuels
could be limited by fact that large quantities of greenhouse gases (GHGs), with CO2 being
a major contributor, are emitted. This is blamed for global warming. The predicted
transition in climate, owing to the world’s reliance on fossil fuels for energy generation, is
a key impetus for Carbon Capture and Sequestration (CCS). A major challenge to
mitigating global warming is how to reduce CO2 emissions. A global growth rate of
0.6%/year in CO2 emissions from energy-related sources is projected between 2015 and
2040 with natural gas and renewables leading the energy generation sources. Energy
generation from coal is stipulated to be fairly constant within this period. With all these
being large point sources of CO2 emissions, there is the need to employ available
technologies to aid in drastic truncation of emissions.
Several technologies to aid in Carbon capture exist, and they can be broadly
classified under Oxyfuel combustion, Pre-Combustion capture and Post-Combustion
2
capture. Apart from minimizing global warming, CO2 capture has gained wide use in the
petroleum and beverage industries for enhanced oil recovery (EOR) and the manufacture
of carbonated drinks, respectively. (Wilcox, 2012).
3
Figure 1.1 World Energy Consumption based on Energy Source. (U.S. Energy Information
Administration, International Energy Agency, 2017)
Figure 1.2 Greenhouse gas emissions of reporting facilities in Canada (Environment and
Climate Change Canada, 2018).
4
1.2 Overview of Capture Technologies
The major existing technologies for the capture of CO2 as aforementioned are
Oxyfuel Combustion, Pre-Combustion and Post-Combustion Capture. Oxyfuel
Combustion employs very high oxygen purity (>95%) for the combustion of the fossil
fuel, resulting in the exhaust gas consisting essentially of a high concentration of CO2
which can be separated easily. The most common operation of this technology involves
the use of an Air Separation Unit (ASU) in providing nearly pure oxygen to a PC-fired
boiler. Usually, owing to the limitation of construction materials in withstanding harsh
operating conditions for combustion of coal, a recycle CO2 product gas stream is blended
with pure oxygen. The anticipated merit of this technology is that the flue gas stream
produced consists essentially of CO2 and H2O. Thus, when the water is condensed, it
leaves only the CO2 to be further treated at a relatively cheap cost which is an advantage
of this technology over the other two. However, when a large unit for separation of O2 is
involved, this technology poses a disadvantage due to the expensive nature of this process.
Pre-Combustion, as the name suggests, involves the removal of the carbon content
of the fuel prior to being burned to release energy. A strong merit of this technology is the
use of relatively inexpensive physical solvents and lower regeneration energy. The use of
inexpensive physical solvents is due to the use of high total pressure and partial pressure
of CO2. This provides a large driving force for easy absorption into the solvent. Some
methods of CO2 separation under this technology are Integrated Gasification Combined
Cycle (IGCC), Membranes, Chemical looping combustion and gasification and others.
Nonetheless, the use of a solid feed (usually coal-based) presents a drawback to the use of
this technology. Also, the inability to be retrofitted to existing plants is greatly undesirable.
5
The subsequent capture of CO2 after combustion of the fuel for energy extraction
is termed as Post-Combustion capture. It is the most widely used technology currently. Its
ability to be retrofitted to existing power plants comes as a major advantage over the
others. Also, a higher thermal efficiency is observed for Post-Combustion capture as
compared to Pre-Combustion capture. However, the use of expensive reactive solvents
and subsequently higher circulation rates, due to the rather small CO2 concentrations in
flue gases as well as operation at atmospheric conditions, renders it a disadvantage. Also,
relatively larger amount of energy is required for the regeneration of these reactive
solvents. These and other challenges have triggered intensive research to improve upon
the overall Post-Combustion Capture process.
1.2.1 Post-Combustion Capture
Various options exist under this technology for CO2 capture. They include
Absorption processes, Adsorption processes, Membrane filtration and Cryogenic
Separation. It is important to note that the most common option is the use of Absorption
processes.
1.2.1.1 Absorption Processes
Absorption is broadly classified as either physical or chemical. Physical absorption
involves CO2 absorption at elevated pressures and considerably lower temperatures;
regeneration of the solvent is done by reducing pressure and raising the temperature for
CO2 evolution. It is commonly applied in synthesis gas, hydrogen production and natural
6
gas processing industries (Yu et al., 2012). Commercial processes are usually named after
the solvent employed and they include Rectisol, Selexol, Purisol, Fluor, and Morphysorb
processes. The Rectisol process makes use of methanol, while that of Selexol is either
propylene glycol or dimethylether. Morphysorb, Purisol and Fluor processes utilize
morpholine, N-methylpyrrolidone and Propylene carbonate respectively. General
advantages include low solvent corrosion, low energy consumption, low toxicity, low
vapour pressures and high solvent stability. On the other hand, Chemical absorption
employs reactive solvents in the CO2 removal. The Chemical absorption process begins
with flowing a CO2-containing flue gas upwards into a packed bed column where it is met
by a counter-current flow of a CO2-lean solvent. The CO2 is absorbed and the rich solvent
is sent to a desorption column for solvent regeneration at a high temperature. The lean
solvent flows back to the absorber after regeneration to make a complete cycle. Examples
of reactive solvents used include amine-based solvents and ionic liquids. Alkanolamines
are widely used and many researchers have formulated novel solvents to improve the
chemical absorption process (Sada et al., 1976; Hikita et al., 1977).
1.2.1.2 Adsorption Processes
Various solid adsorbents are in existence to aid in CO2 capture. They are usually
classified as physical or chemical adsorbents. Adsorbents used include activated carbon,
ordered mesoporous carbon, ordered mesoporous silica, zeolites, metal-organic
framework (MOFs), single and multi-walled carbon nanotubes (CNTs) and graphene
(Cinke et al., 2003; Plaza et al., 2010; Saha and Deng., 2010; Su et al., 2009; Hsu et al.,
2010; Ghosh et al., 2008; Liu et al., 2005, Sun et al., 2007; Wang et al., 2011b; Millward
7
and Yaghi., 2005). The chemical adsorbents are mostly amine-based which are either
grafted or impregnated on the solid support (Sayari et al., 2011). The techniques available
for regeneration of these adsorbents after they have been loaded with CO2 can either be
accomplished by using steam, hot air (TSA-Temperature Swing Adsorption), or switching
between high pressure (above atmospheric) for adsorption and low pressure (at
atmospheric) for desorption (PSA – Pressure Swing Adsorption). When adsorption is done
at atmospheric pressure, and a vacuum is pulled for CO2 desorption to occur, the process
is termed as Vacuum Swing Adsorption (VSA). A combination of these techniques is also
employed to improve upon the process (Olajire, 2010).
1.2.1.3 Membrane Filtration
Membrane filtration employs a semi-permeable medium to selectively remove
species from one phase to the other. The application of a driving force is the main
characteristic of membranes. The driving force for the permeation of CO2 is either
concentration gradient, temperature gradient, pressure gradient and electric potential of
two differing gases at either side of the membrane. Different types of membrane materials
are in use. The types are polymeric membranes, inorganic membranes, hybrid organic-
inorganic membranes and facilitated transport membranes (Lv et al., 2013). Owing to their
low cost, high separation performance and mechanical strength, Polymeric membranes
have drawn the most attention for CO2 capture. Two main properties affecting the selection
of membrane materials for gas separation are permeability and selectivity. The extent of
separation is dictated by the permeability while selectivity influences the permeate gas
CO2 concentration (Makertihartha et al., 2016).
8
1.2.1.4 Cryogenic Separation
Cryogenic separation of CO2 from flue gases involves cooling the gas to very low
temperatures for the liquefaction and separation of CO2. An advantage is that no chemical
solvents are required. However, a huge demerit of this process is the large energy
requirement for cooling the gas. Also, in post combustion capture, flue gas streams contain
water and other waste products such as NOx and SOx; the removal of these components is
necessary prior to the gas being introduced to the low temperature section (Wong and
Bioletti, 2002). Moreover, these waste products are normally generated around
atmospheric pressure. The implication of all the above disadvantages is that it results in
the cryogenic separation being less economical than the rest in the separation of CO2 from
flue gases.
1.3 Drawbacks of Chemical Absorption based Post-Combustion Capture
Post-combustion capture involving chemical absorption is plagued with a number
of limitations in its operation and applicability. Since it is the most mature technology in
use, tackling the existing limitations faced by this technology will go a long way to aid in
the drastic reduction of CO2 emissions. The limitations of this process include high energy
requirement, solvent corrosiveness, slow kinetics, low absorption capacity and low
thermal stability (solvent degradation). A closer look at the limitations highlights two main
areas of improvements: Solvent and Process enhancement. Hence, current studies are
focused primarily on formulating better solvents and overall process optimization (Narku-
Tetteh et al., 2017).
9
1.4 Research Problem
Post-combustion capture has seen significant progress since its inception in
comparison to other competing technologies. Its practical implementation has generated
much awareness on how to strategically optimize the process. Most current studies have
been – and still are - in the area of minimizing the energy penalty or heat duty for solvent
regeneration. In the same vein of reducing energy requirements, Process Optimization of
the CO2 capture process has triggered many technological advancements in this regard.
Some process improvements including absorber inter-cooling, stripper inter-heating,
multi-pressure stripping and others have been undertaken (Cousins et al., 2011).
Khalilpour and Abbas (2011) made improvements to the Heat Exchanger Network (HEN)
resulting in a percentage reduction in energy penalty from about 19.4% to 15.9%. These
approaches are aimed at reducing the energy penalty for solvent regeneration. However,
additional requirements in terms of controls and required equipment may tend to introduce
costs in other areas, hence making benefits derived from their incorporation marginal. Not
minimizing the need for energy reductions, it is of utmost importance that other equally-
pertinent areas are given due concern as well. A more holistic look at the process reveals
the need to also have designs for minimizing the plant size (absorption and desorption
columns), developing online analytical methods, enhanced reclaiming methods, as well as
efficient and economic flue gas polishing strategies (van der Ham et al., 2014; Elmoudir
et al., 2012; Pouryousefi, 2016; Idem et al., 2015). A concurrent study on these areas,
especially in the areas of both lower regeneration energy and smaller column sizing, will
go a long way to making the Post-combustion capture process more economical than its
counterpart capture technologies. Minimizing plant size does not only reduce bulkiness
10
but also significantly cuts down capital costs which can be put to good use in other areas.
The main determinant to having smaller plant sizes is faster system kinetics.
Many researchers have sought ways to improve the kinetics of the solvent-based
capture process. The types of solvents that have been developed and put to use are
alkanolamines, ionic liquids, amino acid salt, chilled ammonia, phase change solvents and
biphasic solvents (Idem at al., 2015). The most advanced in use are alkanolamines as they
have been applied to chemical absorption Post-combustion capture for a much longer
period before the emergence of the other solvents. In the field of alkanolamine solvent
development, many solvents have been formulated and tested over the years, showing
great improvements in system kinetics. Generally, primary alkanolamines are the most
reactive with CO2 and fastest of the three, with tertiary alkanolamines being the slowest in
CO2 absorption kinetics. Thus, in view of enhancing the system kinetics, many researchers
have been more focused on primary and secondary amines as compared to tertiary amines.
It has been found out that N-ethylmonoethanolamine (EMEA), a secondary amine, yields
faster CO2 absorption kinetics than its counterpart secondary amines, DEA and di-
isopropanol amine (DIPA) in studies conducted by Sutar et al. (2012). A sterically-
hindered amine, 2-amino- 2-methyl-1-propanol (AMP), showed the highest thermal
stability when compared with MEA, DEA and methyl monoethanolamine (MMEA) along
with seven (7) other amine solvents in the work of Eide-Huagmo et al. (2011). Piperazine
(PZ), a cyclic amine, has also shown good absorption and desorption performance over
MEA (Rochelle, 2009). However, CO2 absorption has to occur at high temperatures due
to its limited solubility in water (Babamohammadi et al., 2015). Yu et al. (2012) conducted
studies on CO2 capture with the single alkanolamine solutions, Diethylene triamine
11
(DETA) and PZ, in a Rotating Packed Bed. It was discovered that the CO2 capture
efficiency of DETA was superior to that of MEA with regards to the overall mass transfer
coefficient and Height of Transfer Units (HTU). This is due to the higher CO2 absorption
capacity and faster kinetics possessed by DETA over MEA. Owing to its higher boiling
point and lower vapour pressure resulting in lower heat duty and solvent losses in
desorption, DETA was suggested to be a promising solvent as compared to MEA for Post-
Combustion CO2 capture. Many other solvents have been developed and studied in this
regard.
Other researchers have proven the effect of combining two or three of these
solvents in forming a blend. Usually, primary and secondary amines are combined with a
tertiary amine to accrue both the advantage of faster kinetics of the former and larger
absorption capacity as well as low regeneration energy of the latter. The idea of blended
amines was first introduced by Charkravarty et al., (1985) and has since seen a wide
patronage by others in the CO2 capture industry. Blended solutions of DETA + PZ revealed
higher CO2 capture efficiency when PZ was used as a promoter in the work of Yu et al.,
2012 than when used individually. The works of Xu et al. (1992); Zhang et al., 2001., Liao
et al., 2002, Mandal et al., 2003, Sun et al., 2005; Choi et al., 2009, Sutar et al., 2012 have
proven synergistic improvements by blending a number of various single amines. Very
recently, a rigorous criterion of amine-based solvent development has been done by Xiao
et al., (2016), Narku-Tetteh et al (2017) and Muchan et al., (2017). In the work of Narku-
Tetteh et al., (2017) and Muchan et al., (2017), a group of primary, secondary and tertiary
amines were studied to check for the effect of their side chain structures and number of
hydroxyl groups on CO2 absorption and desorption. A combination of solvent properties
12
and performance estimation parameters such as CO2 absorption and desorption kinetics,
equilibrium loading, heat duty, cyclic capacity, pKa and heat of absorption were grouped
into Absorption and Desorption parameters. A novel bi-solvent aqueous amine blend
constituting 2-butyl-aminoethanol (BEA) and 2-amino-2-methyl-1-propanol (AMP) of
equimolar concentration (2M each) outperformed other potential solvents, including MEA
and MDEA (known for its excellent desorption characteristics) based on a newly
developed “Absorption and Desorption parameter”. Further studies done by Narku-Tetteh
et al. (2017) proved a considerably lower heat duty requirement of this novel blend on a
benchmark pilot plant scale as against MEA-MDEA blend reported by Srisang et al
(2017). The studies by Narku-Tetteh et al., (2017) were however done on a semi-batch
scale. To fully exploit its potential, a full-cycle bench scale pilot plant is necessary. This
study aims to do that.
Still with the aim of minimizing plant size (by faster reaction kinetics), other
aspects other than solvent development have been considered. Quite a number of
researchers have employed inorganic liquid catalysts to enhance CO2 absorption into
aqueous solutions and have been successful. (Sharma et al, 1963; Bandyopadhyay et al.,
1980; Ghosh et al., 2009; Guo et al, 2011; Nicholas et al, 2014; Phan et al., 2015).
Sivanesan et al. (2016) used tertiary amine nitrate salts in the presence of an aqueous
tertiary amine medium to enhance CO2 absorption rate using the stopped-flow technique.
Clearly, this has triggered further studies into the application of catalysts, both mineral and
bio-based, to the CO2 capture process. Saville and Lalonde (2011) and Chu et al. (2009)
have showcased the enzymatic acceleration of CO2 absorption from flue gases. Carbonic
anhydrase (CA), a biocatalyst, has been employed to speed up the capture of CO2 into a
13
potassium carbonate (K2CO3) solution (Kanth et al., 2013). However, Saville and Lalonde
(2011) also reported on the inability of these biocatalysts to withstand harsh conditions.
The limitations in their rather ephemeral lifetime and loss of activity owing to these harsh
conditions (temperature or pH) has been a huge hindrance to their commercialization
(Saeed and Deng, 2015).
The introduction and application of solid mineral catalysts in both absorption and
desorption by the use of solid base and acid catalysts, respectively, was recently introduced
by Idem et al. (2011) and followed up by Shi et al. (2014). The motivation was to reduce
the heat duty for solvent regeneration as well as to reduce the size of the columns. The
positive results obtained led to subsequent tests on solid acid catalysts by Liang et al.
(2016) and Zhang et al. (2017). All these studies, performed on a batch scale, showed
considerable reduction in heat duty. Application of solid acid catalysts on a bench-scale
pilot plant by Akachuku (2016), Osei et al., (2017), Decardi-Nelson et al., (2017) and
Srisang et al., (2017) have proven the results obtained by Shi et al. (2014) and a successful
translation from a batch system to a bench-scale pilot plant level.
The kinetics of heterogeneous catalytic studies involving solid mineral alkaline
catalysts (related to absorption), and for that matter, for the novel solvent BEA/AMP
blend, is almost nonexistent in the literature. However, most recently, Shi et al. (2017),
studied the addition of solid base catalysts to the secondary amine diethanolamine (DEA)
solvent to enhance the absorption process using CaCO3 and MgCO3 on a batch scale. A
reduction in overall reaction time up to 14-28% and 11-28% were obtained for CaCO3 and
MgCO3, respectively.
14
It can be concluded that reliable experimental estimates of the kinetic
improvements in catalyst-aided CO2 absorption into BEA/AMP has not been reported in
the literature. The uniqueness of the coupled merit offered by the novel solvent and solid
base catalyst is yet to be ascertained. This work evaluates, for the first time, the kinetic
performance of the novel solvent blend, 4M BEA/AMP and the incorporation of a solid
base catalyst to the absorption section of a full-cycle bench-scale pilot plant.
1.5 Research Objectives and Scope of Work
This research generally seeks to harness the synergistic advantages of utilizing a
heterogeneous solid alkaline catalyst and a heterogeneous solid alkaline catalyst with a
novel solvent blend in a full-cycle bench-scale CO2 capture pilot plant. Therefore, the
objectives of this research were to:
1. Evaluate the kinetic performance of a novel solvent blend, butyl (amino)-
ethanolamine (BEA) + 2-amino-2-methyl-1-propanol (AMP), with conventional
Monoethanolamine (MEA) and blended monoethanolamine (MEA) + -n-
Methyldiethanolamine (MDEA)
2. Compare their kinetic performance with the incorporation of a solid acid catalyst
(HZSM-5) in the desorber section of a bench-scale pilot plant.
3. Perform screening tests based on the physicochemical properties of a number of
solid alkaline catalysts prepared in-house on a semi-batch scale with an equimolar
mixture of the novel solvent 4M BEA-AMP blend and further select the best
among them based on the above criteria.
15
4. Obtain intrinsic experimental kinetic data for the absorption of CO2 into the novel
solvent blend 4M BEA-AMP over the selected solid alkaline catalyst.
5. Obtain a power law model describing the relationship between the reaction rate
and reactant and/or product concentrations.
6. Perform parametric sensitivity studies on the impact of various process parameters
on the reaction kinetics for the heterogeneous CO2-BEA-AMP-H2O system.
1.6 Thesis Organization
The thesis is organized as follows:
• Chapter 1 presents an overview of the CO2 capture process and technologies
employed, after which the objectives of this work are outlined.
• Chapter 2 presents and discusses available and extensive literature on CO2
absorption and desorption kinetics, important solvents employed, chemistry of the
absorption process, catalyst-aided CO2 absorption and desorption, available
alkaline catalysts and their role in CO2 capture.
• Chapter 3 discusses the experimental set-ups, procedure and condition used.
• Chapters 4 and 5 presents the results and discussion
• Chapter 6 concludes this research and suggests viable recommendations for future
work.
16
CHAPTER 2: LITERATURE REVIEW
This chapter covers a thorough review of existing literature on the scope of this
work. This comprises studies on important alkanolamine solvents employed, CO2
absorption kinetics, chemistry of the absorption process, catalyst-aided CO2 absorption,
available alkaline catalysts and their role in CO2 capture.
2.1 Solvents
The performance of the chemical solvent-based post-combustion capture is
primarily hinged on the solvent characteristics. Numerous solvents have been employed
over the years with improvements in performance compared with previous solvents. Based
on the hydrogen atoms directly attached to nitrogen, amines can be classified as primary,
secondary and tertiary. The conventional ones in relation to their classification are:
• Primary: monoethanolamine-MEA; diglycolamine (DGA)
• Secondary: diethanolamine – DEA; diisopropanolamine (DIPA)
• Tertiary: triethanolamine – TEA; Methyldiethanolamine (MDEA)
Amines with two hydrogen atoms attached to the nitrogen are primary, while those
with one hydrogen attached are secondary. Tertiary amines have no hydrogen atom
attached but rather have alkyl groups in the place of hydrogen. The most utilized amine
Monoethanolamine (MEA) which falls under primary amines is known for its good
absorption properties. However, in terms of its desorption performance, it is limited as it
requires huge energy for its regeneration, it is prone to corrosion and possesses a high
degradation rate and (Osei, 2016). DEA, a secondary amine, has also been reported to have
good absorption performance though lower than that of MEA. However, both MEA and
17
DEA (primary and secondary amines) have limited absorption capacities. This is
overcome by the use of tertiary amines which have a larger capacity of 1 mole of CO2 to
1 mole of amine. MDEA (a tertiary amine) is an example of such an amine, and it has
found wide applicability due to this property as well as its low regeneration energy
requirement and high solvent stability (Osei, 2016). However, they are generally the
slowest among the three classes of amines. Kim and Savage (1987) introduced a tertiary
alkanolamine, N,N diethyl ethanolamine (DEEA) and reported on its reaction with CO2.
Experiments by Li et al. (2007) showed faster kinetics for DEEA over MDEA (Methyl
diethanolamine). Fouad et al. (2011) reported on the larger absorption capacity of MDEA
over TEA. Much recently Naami et al. (2012) showed the superior performance of 4-
diethylamino-2-butanol (DEAB) over MDEA in terms of regeneration energy
requirement. Gao et al. (2015) studied a novel solvent 2-[(3-aminopropyl) methyl amino]
ethanol (HMPDA), containing a primary and tertiary amino group, to enhance
performance. A higher absorption rate, absorption capacity and good physical properties
were exhibited by this solvent over MEA and MDEA. This was due to the multiple reaction
sites present in the HMPDA. Another group of amines known as sterically-hindered
amines (which can be either primary or secondary) have been reported to also exhibit
larger absorption capacities, and are faster than tertiary amines; making them the preferred
amine types (Vaidya et al., 2007). Examples are 2-amino-2-methyl-1-propanol (AMP) and
2-piperidineethanol (PE) which are primary and secondary sterically hindered amines
respectively.
As mentioned in the previous chapter, a technique of blending single amine
solvents have also received due recognition where mostly, primary and secondary amines
18
are combined with a tertiary amine to provide both the advantage of faster kinetics of the
former and larger absorption capacity as well as lower regeneration energy of the latter.
Rinprasertmeechai et al. (2012), conducted tests on blends of MEA, DEA and TEA with
PZ. It was concluded that MEA+PZ blend showed the largest absorption capacity while
the TEA+PZ blend was reported to have the highest regeneration efficiency of 95.09%.
Blends of MEA-MDEA, MEA-AMP, DEA-MDEA and DEA-AMP were studied
by Aroonwilas and Veawab (2004). AMP based blends were seen to be more effective
than MDEA based blends. Higher absorption performance was also observed with MEA
blends as compared to DEA blends. Tri-blends of 6M MEA+AMP+PZ were studied by
Nwaoha et al. (2016) for their potential capability in CO2 capture. AMP and PZ
concentrations were varied while keeping their total concentration at 3M. To eliminate the
probability of precipitation, the maximum concentration of PZ used was 1.5M. Results
reveal that the tri-solvent blend possessed higher cyclic capacities, initial desorption rates,
and lower heat duties as compared to the standard 5M MEA.
The above solvents (both single and blended), just to mention a few, are clear
justifications for improving the performances they offer to the solvent-based post-
combustion capture process. The structure of the amines studied in this work are shown in
figure 2.1.
19
Figure 2.1 Molecular Structure of amines studied in this work
20
2.2 CO2 Absorption Kinetics Data
Investigations for Kinetic data for both absorption and desorption have been
performed in a variety of apparatuses. Very few works have been performed on the kinetics
of the reaction involving single BEA and CO2; moreover, experimental kinetic data for the
blended solutions of BEA is scarce in the literature, unlike AMP. Mimura et al. (1998)
conducted kinetic studies on the reaction between CO2 from flue gases of power plants
and the secondary amine, BEA at a temperature of 298K utilizing a stirred tank absorber
having a plane unbroken gas-liquid interface. The absorption rate data were analyzed
under the fast reaction regime using the chemical absorption theory. The second order
reaction rate constant at 298K for the BEA concentration range of 0.9 to 2.5M was
determined to be 4.76 × 103 m3kmol-1s-1. Ali et al. (2002) studied the kinetics of the
reaction between CO2 and aqueous BEA using the direct stopped flow technique for the
temperature range from 283 to 308 K. The reaction kinetics were explained by the
Zwitterion mechanism. The Zwitterion formed was found to be largely deprotonated by
water and its stability decreased with temperature. The second order reaction rate constant
was obtained for the temperature range stipulated. At 298K, it was determined as 2.0
m3mol-1s-1. Experimental absorption data were obtained by Hwang et al. (2016) for
estimating the solubility of BEA (which is a function of reaction kinetics) at a pressure
range of 0.02 to 395 kPa at different temperatures of 40, 80 and 120oC. For CO2
equilibrium partial pressures below 1 kPa, data were obtained using a modified gas
sparging reactor unit while an equilibrium cell unit was employed for pressures higher
than 1 kPa. Results showed higher cyclic absorption capacities and heat of absorption of
BEA over MEA. Two concentrations of 15 and 30wt% were understudied. Ma’mun (2005)
21
reported on the absorption rates in molL-1s-1 of 30wt% BEA and other amines at 40oC and
atmospheric pressure of 1 atm using a screening apparatus comprising of six lab-scale
bubble absorbers. His report showed higher absorption rates were obtained over the entire
loading range (0 – 0.6 mol CO2/mol amine) for the BEA solvent when compared to MEA.
Couchaux et al. (2014) also reported a value of 3.17×10-1 m3mol-1s-1 for the second order
rate constant of BEA after studying a number of amines solvents existing in literature.
Kinetic data for AMP have been reported by many researchers both as a single
solvent and as a blend. The first kinetic studies on AMP was performed by Chakraborty et
al. (1986) where he investigated the equilibrium behaviour of the hindered primary amine
in aqueous solutions. It was established that two equilibrium constants: protonation
constant and carbamate stability constant, dominated the equilibrium behaviour of this
solvent. The carbamate stability constant was found to be very small and has since been
the basis for speculating insignificant carbamate yields for AMP-based reactions with
CO2. In 1989, Bosch et al., under reaction-controlled conditions, further studied the
reaction kinetics in aqueous solutions between CO2 and AMP, with varying AMP
concentrations from 200 to 2400 molm-3 in a stirred vessel with smooth horizontal
interface. The Zwitterion mechanism could satisfactorily explain the reaction rate;
however, the reaction rate constants for the zwitterion deprotonation were not able to be
fully explained. A year on, Alper in 1990, successfully investigated the reaction kinetics
of AMP using the stopped-flow reactor at conditions of temperature ranging from 278 to
298 K. He was able to determine the second order reaction rate constant for AMP at 298
K as 520 m3kmol-1s-1. Saha et al. (1995) further studied the kinetics of aqueous CO2+AMP
reactions in a wetted wall column at 294 to 318 K in the concentration range of 0.5 to 2
22
kmolm-3. A value of 439 m3kmol-1s-1 was estimated to be the second order rate constant
which was found to agree very closely with the work of Alper (1990). A much recent work
done by Zheng et al. (2015) using a microfluidic method at 298 to 318 K over the
concentration range of 1 to 2 kmolm-3 gave a second order rate constant of 1450 m3kmol-
1s-1 at 318 K.
Many researchers have investigated the kinetics of the blended systems of AMP
with other aqueous amine solvents. Using the wetted wall column, Sun et al. (2005)
investigated the kinetics for the aqueous CO2+AMP+PZ blend at 30 to 40oC. A second
order rate constant was found to adequately describe the obtained kinetic data for CO2
absorption into the system. For a concentration of 1.5M AMP and 0.4M PZ, the kapp
obtained for the system was 27744 s-1 at 40oC. Prior to this, Xiao et al. (2000) also reported
on the kinetics of a blend comprising AMP and MEA at various concentrations also using
a laboratory wetted wall column for the temperature range of 30 to 40oC. His results show
that a smaller kapp with a value of 6661.2 s-1 was obtained for his system as compared to
AMP+PZ system of Sun et al. (2005), which had a value of 27744s-1. Experimental
absorption kinetic data for a tri-solvent blend of AMP+PZ+MEA were obtained by
Nwaoha et al. (2016). It was revealed that AMP/PZ concentration ratios of 1 and 2 yielded
higher initial absorption rates as compared to single 5M MEA at a temperature of 313K.
The total AMP+PZ concentration was fixed at 3M while they were varied individually.
Choi et al. (2009) investigated the performance of CO2 reactions with a blend of
AMP+MEA using a stirred cell tank reactor over the temperature range of 20 to 40oC.
Absorption kinetics were expressed in terms of specific absorption rates and rate constants.
The specific absorption rates were shown to be higher for the blended system than the
23
single amines. The second order rate constant of AMP was reported as 1001 m3kmol-1s-1
at 40oC which was similar to that obtained by Yih and Shen (1988) but was slightly higher
than values reported by other researchers (Xu et al., 1996 and Alper, 1990). He attributed
the variation in rate constants to differences in reactor configuration as well as other
reaction conditions. An experimental and theoretical analysis was conducted by Mandal
et al. (2003) on the absorption of CO2 into aqueous blends of AMP+DEA; and was
explained by a mass-transfer reaction-kinetics equilibrium model. The model was
formulated according to that of Higbie’s penetration theory. A value of 3100 m3kmol-1s-1
was reported as the second order reaction rate constant at a temperature of 313K. Table
2.1 displays the rate constants of some AMP blended systems. Other works on the kinetics
of AMP blended systems include Seo et al. (2000), Choi et al. (2007), Sakwattanapong et
al. (2009), Sodiq et al. (2014), Zhou et al. (2016) and many others.
24
Table 2.1Rate constants for CO2 absorption into some blended aqueous AMP systems
System Reactor Type Temperature
(K)
Rate constant Reference
AMP+MEA Wetted-wall
Column
303 - 313 kapp = 6661.2
s-1
Xiao et al.,
(2000)
AMP+DEA Wetted-wall
column
313 k2 =3100
m3kmol-1s-1
Mandal et al.,
(2003)
AMP+PZ Wetted-wall
Column
303 kapp =27744
s-1
Sun et al.,
(2005)
AMP+MEA Stirred-cell
tank reactor
293 - 313 k2 =1001
m3kmol-1s-1
Choi et al.,
(2009)
25
2.3 Solvent Chemistry
The mechanism of CO2 reactions with amines is key to understanding and
interpreting obtained experimental kinetic data. Also, with the incorporation of catalysts,
a thorough understanding of the reaction mechanism gives one a rigid platform to
understudy the interaction between the solvent, acid gas (CO2) and catalyst surface. The
amine solvent is made up for 2 main functional groups: the hydroxyl (OH) group and the
amino (NH2) group. The hydroxyl group enhances the solvents solubility while decreasing
its vapour pressure and during regeneration helps to reduce losses. Correspondingly, the
amino group is the main centre for the solvents reactivity owing to its alkaline nature (Kohl
and Nielsen, 1997). Numerous researchers have extensively understudied the reaction
mechanism between CO2 and amines (Caplow, 1968; Danckwerts et al., 1970; Crooks and
Donellan, 1989; Versteeg et al., 1996; Vaidya et al., 2007), resulting in different positions
on the mechanism involved in the reaction. A well-known mechanism which was
introduced by Caplow in 1968 suggests a two-step mechanism where the first involves a
reaction (an electrophilic addition reaction) between CO2 and the amine solvent to yield
an intermediate. The intermediate formed is called a Zwitterion, and this intermediate
reacts in the next step with any available base to produce the final products. Products
formed are carbamate ions and protonated amines. Tertiary amines do not have a hydrogen
atom in their amino group hence cannot form a Zwitterion ion. Their reactions with CO2
are seen to be base-catalysed. This was proposed by Donaldson and Nguyen in 1980 and
has thus been used to interpret the kinetic results for tertiary amines. In 1989, Crooks and
Donellan came up with a contrary view on the suggested mechanism by Caplow (1968).
Their mechanism proceeded via a single step where three molecules react simultaneously
26
to yield carbamate and protonated amines and was given the name Termolecular
mechanism. Presumably, no intermediates are formed. Most published kinetic data have
been analyzed by employing both mechanisms. No single mechanism has thus been
selected to be the authoritative path for CO2-amine reactions. Owing to its applicability
and popularity, the mechanism proposed by Caplow (1968) is adopted in this work for the
meticulous study of the role played by the catalyst in absorption.
2.3.1 Reaction of CO2 with aqueous primary and secondary amines
Reactions involving primary and secondary amines with CO2 are known to result
in carbamate and protonated amine formation and they generally proceed via the overall
reaction:
𝐶𝑂2 + 2𝑅1𝑅2𝑁𝐻 ⟺ 𝑅1𝑅2𝑁𝐶𝑂𝑂− + 𝑅1𝑅2𝑁𝐻2+ (2.1)
Where R1 is an alkyl group and R2 is an alkyl group and H for secondary and primary
amines respectively. The detailed reaction is shown below:
𝐶𝑂2 + 𝑅1𝑅2𝑁𝐻 ⟺ 𝑅1𝑅2𝑁𝐻+𝐶𝑂𝑂− (2.2)
𝑅1𝑅2𝑁𝐻+𝐶𝑂𝑂− + 𝐵 ⟺ 𝑅1𝑅2𝑁𝐶𝑂𝑂− + 𝐵𝐻+ (2.3)
Where B can be H2O, OH- or an amine.
2.3.2 Reaction of CO2 with aqueous tertiary amines
Tertiary amine reactions with CO2 as suggested by Donaldson and Nguyen
undergo a reaction classified as a base-catalyzed hydration mechanism. It was proposed
27
that the tertiary amine does not react directly with CO2, but acts as a base to catalyze the
hydration of CO2. The reaction occurs as follows:
𝐶𝑂2 + 𝑅1𝑅2𝑅3𝑁 + 𝐻2𝑂 ⟺ 𝑅1𝑅2𝑅3𝑁𝐻+ + 𝐻𝐶𝑂3− (2.4)
2.3.3 Reaction rate dependence on AMP
The reaction kinetics of the non-catalytic absorption of CO2 into aqueous solutions
of AMP have been widely studied and is evident by in the works of Sun et al. (2005), Xu
et al. (1996), Saha et al. (1995), Chakraborty et al. (1986); Zioudas and Dadach (1986);
Sartori et al. (1987); Yih and Shen (1988), and Alper (1990). The primary sterically-
hindered amine, AMP, in its reaction with CO2, has been reported to have an overall
reaction order of 2 by the above researchers. The zwitterion mechanism was employed in
arriving at the preceding deduction and has been successfully used in various aqueous
amine solvents. The Zwitterion mechanism with respect to AMP when applied to the
uncatalyzed CO2+AMP+BEA+H2O system will take the form:
]))[][][][((1
]][2[
221
22
BEAkAMPkOHkOHkk
AMPCOkr
BEAAMPOHOH
AMPAMPCO
(2.5)
where k2,AMP represents the reaction rate constant for zwitterion formation from CO2 and
AMP, k−1 represents the reverse reaction rate constant of the zwitterion, kH2O, kOH−, kAMP
and kBEA represent the reaction rate constants for the deprotonation of the zwitterion by
the bases in the system which are H2O, OH− , AMP and BEA respectively.
28
2.3.4 Reaction rate dependence on BEA
The reaction kinetics of aqueous BEA with CO2 is nonexistent in the literature.
Since most amines studied have been successfully described by the zwitterion mechanism,
the reaction rate dependency on BEA can also be safely represented by the Zwitterion
mechanism:
]))[][][][((1
]][2[
221
22
BEAkAMPkOHkOHkk
BEACOkr
BEAAMPOHOH
BEABEACO
(2.6)
2.3.5 Reaction rate for uncatalyzed CO2 absorption into aqueous AMP+BEA
system
The overall reaction rate can be expressed as:
OHCOOHCOBEACOAMPCOOV rrrrr22222 (2.7)
The last term is usually neglected due to the negligible contribution of H2O to the overall
reaction (Blauwhoff et al., 1984). Hence substituting reactions (4) and (5), into reaction
(6) gives:
]))[][][][((1
]][2[
221
22
BEAkAMPkOHkOHkk
AMPCOkr
BEAAMPOHOH
AMPAMPCO
+
]))[][][][((1
]][2[
221
2
BEAkAMPkOHkOHkk
BEACOk
BEAAMPOHOH
BEA
+ ]][[ 2
* OHCOk OH (2.8)
The above expression represents the overall reaction rate of the uncatalyzed reaction for
the CO2+H2O+AMP+BEA system.
The apparent reaction rate constant is given as:
][* OHkkk OHOVapp (2.9)
29
2.4 Catalysis in solvent-based CO2 Capture
Many researchers have sought ways to improve the kinetics of the solvent-based
capture process. It is obvious that a solvent process alone may not be enough to provide
all the desired features for enhancing the kinetics of the system. A technological strategy
which involves the application of catalysts have been investigated in this regard. Over the
years, a number of researchers have employed inorganic liquid catalysts to enhance the
rate of CO2 absorption into aqueous solutions and have proven to be successful (Sharma
and Danckwerts, 1963; Bandyopadhyay et al., 1980; Ghosh et al., 2009; Guo et al., 2011;
Nicholas et al., 2014; Phan et al., 2015). Sharma and Danckwerts (1963) were the first to
study the introduction of liquid catalysts such as arsenite, formaldehyde and hypochlorite
to speed up CO2 reactions with alkaline solutions. Later in 1980, Bandyopadhyay et al.
(1980) conducted further studies on effect of arsenite catalyst on the rate of reaction
between CO2 and a sodium carbonate-bicarbonate buffer using a stirred cell reactor at
20oC. A rate constant of 7.322×105 cm3mol-1s-1 was obtained. In 2014, Phan et al. (2014)
corroborated their findings by using oxoanions to accelerate the reaction between CO2 and
water. Kinetic studies were conducted in a stopped-flow reactor at 25oC and a mechanism
describing the reaction was proposed. Despite the fast kinetics provided by these
oxoanions, it was reported that the health effects of arsenic and phosphate will rather make
their usage less practical. Sivanesan et al. (2016) used tertiary amine nitrate salts in the
presence of an aqueous tertiary amine medium to enhance CO2 absorption rate using the
stopped-flow technique.
The application of bio-based catalysts (enzymes) to the solvent-based capture
process has also been investigated. More related work with amines was done by Nathalie
30
et al. (2013) when they tested the absorption rates of CO2 into aqueous MDEA by using
Carbonic Anhydrase (CA) as biocatalyst in a stirred-cell reactor over the temperature
range 298 to 333 K. Two temperature-dependent rate constants were determined and the
overall rate of reaction was seen to have been improved by the incorporation of the
biocatalyst. To corroborate their earlier findings, Nathalie et al. (2015) further evaluated
the performance of CA on the CO2 absorption rate into MEA, TEA, N,N-diethyl
ethanolamine (DEMEA), N,N-dimethyl ethanolamine (DMMEA) and tri-isopropanol
amine (TIPA). This work confirmed their earlier deductions of the improved rate of
reaction between CO2 and the alkanolamines. Kunze et al. (2015) reported on laboratory
scale pilot plant studies (absorption column only) on the rate of CO2 absorption into single
solutions of MEA, MDEA, DEEA and K2CO3 over CA. It was discovered that the addition
of CA to the system increased the rate of CO2 absorption by a factor greater than four (4).
In light of its slow reactivity, K2CO3 solution reaction with CO2 was enhanced by
employing Carbonic Anhydrase (NZCA) in the work of Hu et al. (2017). The experiments
were conducted in a wetted-wall column and stopped-flow reactor. A Michaelis-Menten
parameter (kcat/Km) and activation energy of the catalytic reaction were estimated as
2.7×107 M-1s-1 and 51±1 kJ/mol respectively over a temperature range of 298 to 328 K.
Biocatalytic studies on the reaction of CO2 and AMP along with other solvents was
performed by Gladis et al. (2017) in a wetted-wall column over a temperature range 298
to 328 K. An enzymatic rate constant of 1.4×103 m3kg-1s-1 was obtained for a 30wt%
AMP+CO2 system. Other works done include Davy et al. (2011) and Zhu et al. (2016).
The introduction and application of solid mineral catalysts in both absorption and
desorption by the use of solid base and acid catalysts respectively, was recently introduced
31
by Idem et al. (2011) and followed up by Shi et al. (2014). By employing a batch system,
two solid acid catalysts (HZSM-5 and γ-Al2O3) were investigated for their desorption
capabilities on the conventional MEA solvent. The positive results obtained led to
subsequent tests on the solid acid catalysts by Liang et al. (2016) and Zhang et al. (2017).
All these studies, performed on a batch scale, showed appreciable improvement in
desorption parameters. Kinetic studies on a bench-scale pilot plant was recently conducted
by Akachuku (2016) on the application of the above-mentioned solid acid catalysts in
enhancing CO2 desorption from MEA and MEA-MDEA. Activation energies and
frequency factors for both systems as studied in her work are summarised in Table 2.2.
This was a confirmation to the results obtained by Shi et al. (2014) and a successful
translation from a batch system to a bench-scale pilot plant level.
As stated in the earlier chapter, kinetics of heterogeneous catalytic studies
involving solid mineral alkaline catalysts (related to absorption), for the novel solvent
BEA/AMP blend, is almost inexistent in literature. However, recent studies by Shi et al.
(2017), on the addition of solid mineral alkaline catalysts (CaCO3 and MgCO3) to enhance
the absorption of CO2 into DEA on a batch scale has been done. He reported on an overall
reduction in reaction time up to about 14-28% and 11-28% for both CaCO3 and MgCO3
systems respectively. Very recently, Xiao et al. (2018) reported on enhanced initial rates
of CO2 absorption into AMP over an MCM-41 catalyst in a batch system. His results
revealed better absorption rates over the blank case of no catalyst in the absorption system.
He further proposed a mechanism for the catalytic CO2+AMP system.
32
Table 2.2 Activation energies and Frequency factors for catalyst-aided desorption of CO2
from MEA and MEA-MDEA (Akachuku, 2016).
Solvent Catalyst Activation energy,
Ea (J/mol)
Frequency factor, ko
(L/mol.s.gcat)
MEA HZSM-5 7.23×104 2.31×1012
γ-Al2O3 9.87×104 7.72×1012
MEA-MDEA HZSM-5 6.63×104 1.02×1010
γ-Al2O3 6.40×104 1.88×109
33
2.4.1 Heterogeneous alkaline/base catalysts
In the homogeneous phase, acids and bases are defined in various ways, of which
the most adopted are definitions made by Bronsted-Lowley and Lewis (Dwyer and
Schofield, 1994). Heterogeneous catalysis, in relation to its acid-base chemistry, employs
these two definitions as they satisfactorily interpret the surface chemistry surrounding its
applicability. As defined by Bronsted-Lowley, bases accepts a proton; while Lewis defines
bases as lone electron pair donors. A typical reaction scheme describing the two definitions
are as follows:
𝐴𝐻 + 𝐵− → 𝐴− + 𝐵𝐻 (2.10)
𝐴+ ∶ 𝐵 → 𝐴𝐵 (2.11)
From the above reactions, B- is a Bronsted base as it accepts a proton from the acid (AH)
while “:B” is a Lewis base as it donates its lone pair of electrons to “A” in the second
reaction. Solids with sites serving as a Bronsted base and/or Lewis base are named solid
(heterogeneous) bases or solid alkalines.
H – scale, a measure of identifying solid base strengths, was proposed by Tanabe
et al., (1978) where they defined the H– value from equation 2.12 as:
H_ = pKa – log ([AH]s/[A-]s) (2.12)
where AH and A- represent the surface concentrations of AH and A- respectively. With
respect to this definition, they classified numerous solid base catalysts as either strong or
weak. Solid bases with H– values greater than +26 were classified as superbases. Various
works done by researchers (Kijenski et al., 1978; Higuchi et al., 1993; Sun et al., 1999;
Meier at al., 1998) showed some superbases based on the above criteria. These superbases
were proven to be very reactive for most organic reactions including alkene isomerization
34
and toluene side-chain alkylation (Tanabe et al., 1989). Out of these, seven catalysts were
selected in this work to be screened for amine-based CO2 capture. They are BaCO3,
CaCO3, Ca(OH)2, Cs2O/α-Al2O3, Cs2O/γ-Al2O3, K/MgO and Hydrotalcite.
2.4.2 Role of Catalyst in Absorption
The use of catalysts in a reaction is to accelerate the rate of formation of products.
Incorporating a porous solid base catalyst to the absorption column of the capture system
is to capitalize on its ability to enhance the reaction chemically and/or physically. The
basic sites of the catalyst can generate a catalytic pathway where a lower activation is
required for the conversion of reactants into products. Another way is by increasing the
frequency of collision between reactant molecules, thus increasing the probability of
reactant molecules forming products. Hence a greater number of reactant molecules (in
this case CO2) can be absorbed. Also, the porous nature of the catalyst provides a large
interfacial area for mass transfer. Comparatively, the production rate with the inclusion of
catalyst will always be faster than that of an uncatalyzed reaction under similar operating
conditions. The Zwitterion mechanism proposed by Caplow (1968) provides a good
platform for the analysis of the role of the catalyst. Therefore, this mechanism is employed
in this study for the aqueous CO2-AMP-BEA system. According to Caplow (1968), the
zwitterion formation (a nucleophilic addition reaction) step in the zwitterion mechanism
happens to be the rate determining step (RDS). This step involves the transfer of electrons.
Therefore, it is imperative to state that an electron-requiring process will be enormously
enhanced in the presence of free electrons. A class of basic catalysts known as Lewis base
catalysts have this ability to release their electrons ahead of the amine solvents resulting
35
in faster system kinetics. The possible reactions that occur for our aqueous CO2-AMP-
BEA system are outlined as follows:
Water ionization:
𝐻2𝑂 ⟺ 𝐻+ + 𝑂𝐻− (2.13)
Physical Absorption of CO2:
𝐶𝑂2(𝑔) ⟺ 𝐶𝑂2(𝑎𝑞) (2.14)
Bicarbonate formation from CO2:
𝐶𝑂2 + 𝐻2𝑂 ⟺ 𝐻𝐶𝑂3− + 𝐻+ (2.15)
𝐶𝑂2 + 𝑂𝐻− ⟺ 𝐻𝐶𝑂3−
(2.16)
AMP and BEA Zwitterion formation:
𝐴𝑀𝑃 + 𝐶𝑂2 ⟺ 𝐴𝑀𝑃+𝐶𝑂𝑂− (2.17)
𝐵𝐸𝐴 + 𝐶𝑂2 ⟺ 𝐵𝐸𝐴+𝐶𝑂𝑂− (2.18)
Carbamate formation from AMP and BEA
𝐴𝑀𝑃+𝐶𝑂𝑂− + 𝐻2𝑂 ⟺ 𝐴𝑀𝑃𝐶𝑂𝑂− + 𝐻3𝑂+ (2.19)
𝐵𝐸𝐴+𝐶𝑂𝑂− + 𝐻2𝑂 ⟺ 𝐵𝐸𝐴𝐶𝑂𝑂− + 𝐻3𝑂+ (2.20)
𝐴𝑀𝑃+𝐶𝑂𝑂− + 𝑂𝐻− ⟺ 𝐴𝑀𝑃𝐶𝑂𝑂− + 𝐻2𝑂 (2.21)
𝐵𝐸𝐴+𝐶𝑂𝑂− + 𝑂𝐻− ⟺ 𝐵𝐸𝐴𝐶𝑂𝑂− + 𝐻2𝑂 (2.22)
𝐴𝑀𝑃+𝐶𝑂𝑂− + 𝐴𝑀𝑃 ⟺ 𝐴𝑀𝑃𝐶𝑂𝑂− + 𝐴𝑀𝑃𝐻+ (2.23)
36
𝐵𝐸𝐴+𝐶𝑂𝑂− + 𝐵𝐸𝐴 ⟺ 𝐵𝐸𝐴𝐶𝑂𝑂− + 𝐵𝐸𝐴𝐻+ (2.24)
𝐴𝑀𝑃+𝐶𝑂𝑂− + 𝐻𝐶𝑂3− ⟺ 𝐴𝑀𝑃𝐶𝑂𝑂− + 𝐻2𝐶𝑂3 (2.25)
𝐵𝐸𝐴+𝐶𝑂𝑂− + 𝐻𝐶𝑂3− ⟺ 𝐵𝐸𝐴𝐶𝑂𝑂− + 𝐻2𝐶𝑂3 (2.26)
𝐴𝑀𝑃+𝐶𝑂𝑂− + 𝐶𝑂32− ⟺ 𝐴𝑀𝑃𝐶𝑂𝑂− + 𝐻𝐶𝑂3
− (2.27)
𝐵𝐸𝐴+𝐶𝑂𝑂− + 𝐶𝑂32− ⟺ 𝐵𝐸𝐴𝐶𝑂𝑂− + 𝐻𝐶𝑂3
− (2.28)
AMP and BEA amine protonation
𝐴𝑀𝑃 + 𝐻2𝑂 ⟺ 𝐴𝑀𝑃𝐻+ + 𝑂𝐻− (2.29)
𝐵𝐸𝐴 + 𝐻2𝑂 ⟺ 𝐵𝐸𝐴𝐻+ + 𝑂𝐻− (2.30)
𝐴𝑀𝑃 + 𝐻+ ⟺ 𝐴𝑀𝑃𝐻+ (2.31)
𝐵𝐸𝐴 + 𝐻+ ⟺ 𝐵𝐸𝐴𝐻+ (2.32)
AMP and BEA amine deprotonation
𝐴𝑀𝑃𝐻+ + 𝑂𝐻− ⟺ 𝐴𝑀𝑃 + 𝐻2𝑂 (2.33)
𝐵𝐸𝐴𝐻+ + 𝑂𝐻− ⟺ 𝐵𝐸𝐴 + 𝐻2𝑂 (2.34)
𝐴𝑀𝑃𝐻+ + 𝐻2𝑂 ⟺ 𝐴𝑀𝑃 + 𝐻3𝑂+ (2.35)
𝐵𝐸𝐴𝐻+ + 𝐻2𝑂 ⟺ 𝐵𝐸𝐴 + 𝐻3𝑂+ (2.36)
Carbamate hydrolysis
𝐴𝑀𝑃𝐶𝑂𝑂− + 𝐻2𝑂 ⟺ 𝐴𝑀𝑃 + 𝐻𝐶𝑂3−
(2.37)
𝐵𝐸𝐴𝐶𝑂𝑂− + 𝐻2𝑂 ⟺ 𝐵𝐸𝐴 + 𝐻𝐶𝑂3−
(2.38)
37
All the above reactions are considered reversible. With respect to these reactions,
two classes of reactions can be seen to take place: Instantaneous or Kinetically-controlled
reactions. The instantaneous equilibrium reactions involve the transfer of protons and are
seen to be infinite while the kinetically-controlled reactions are seen to be finite. The finite
reaction expressions for the aqueous CO2 +AMP+ BEA system are as follows:
𝐶𝑂2 + 𝑂𝐻− ⟺ 𝐻𝐶𝑂3−
(2.39)
𝐶𝑂2 + 𝐻2𝑂 + 𝐵 ⟺ 𝐻𝐶𝑂3− + 𝐵+ (2.40)
𝐶𝑂2 + 𝐴𝑀𝑃/𝐵𝐸𝐴 + 𝐵 ⟺ 𝐴𝑀𝑃𝐶𝑂𝑂−/𝐵𝐸𝐴𝐶𝑂𝑂− + 𝐵+ (2.41)
Where B represents any base in the system which include: AMP, BEA, OH-, H2O, HCO3-
and CO32- while B+ represents their corresponding conjugate acids, namely: AMPH+,
BEAH+, H2O, H3O+, H2CO3 and HCO3
-, respectively. Reactions 2.40 and 2.41 are not
single reactions or do not occur in one step but are rather a combination of reactions
involving Zwitterion formation and breakdown.
The presence of O2- anions of unsaturated co-ordination accounts for the basic sites
in the Lewis solid base catalyst (Chen et al., 2013). For a Lewis base catalyst (e.g. K/MgO),
the catalytic mechanism can be broken down into 3 steps as follows:
1. Donation of electrons by the nucleophilic oxide anion in MgO to CO2.
2. Bond breaking of C=O and intramolecular electron transfer to oxygen.
38
3. Donation of electrons by Nitrogen in amine to CO2 and subsequent breaking away
of MgO.
The second step in the Zwitterion mechanism involving deprotonation of the
zwitterion is known to be instantaneous and therefore not rate limiting. However, the role
of a Brϕnsted base catalyst (e.g. Hydrotalcite), is exhibited in this reaction as it serves as
a proton abstractor along with the other bases in the system (Amine, OH- ions and H2O).
The mechanism begins with the abstraction of a proton from zwitterion by the dominant
hydroxyl (OH-) anions in Hydrotalcite resulting in the formation of carbamate and a
conjugate acid of Hydrotalcite. The conjugate acid is then attacked by the electron-rich
nitrogen in the amine, breaking the H+-OH- bond of the conjugate acid. This yields a
protonated amine and the detached Hydrotalcite catalyst.
39
CHAPTER 3: EXPERIMENTAL SECTION
The experimental section comprises the catalyst preparation procedure,
characterization, screening runs, as well as the pilot plant runs carried out in this study.
Details of the above are hereby presented.
3.1 Laboratory Health and Safety Measures
To ensure a safe and healthy laboratory working environment, the following safety
measures were taken:.
• It was ensured that all Personal Protective Equipment (PPE) consisting of a lab
coat, hand gloves, safety goggles, and safety shoes were worn during experimental
runs in the lab.
• All gas cylinders were well secured to prevent knocking over when in use. When
transporting cylinders, it was ensured they were properly capped and chained on
appropriate carts.
• All chemicals utilized were properly labelled and stored in their appropriate
cabinets according to WHMIS requirements.
• It was ensured that chemical spills were cleaned up immediately if safe to proceed
using standard procedures. Also broken glassware were collected,stored and
disposed off in their appropriate containment.
• Work areas were kept clean and free of obstructions.
• It was ensured that laboratory fume hoods were employed when working with toxic
and flammable vapours from chemicals in the laboratory.
40
3.2 Materials and Equipment
BaCO3(≥99%), CaCO3 (≥99%), Mg(OH)2(≥95%), KOH(≥99.99%),
CH3COOCs(≥95%), Al(NO3)3.9H2O(≥98%), Mg(NO3)2.6H2O(≥98%), Na2CO3(≥99%),
MEA (≥98%), MDEA (≥98%), BEA (≥98%) and Ludox HS 40 colloidal silica (40wt%
suspension in H2O) were all purchased from Sigma Aldrich Co. Canada. AMP (≥99%),
Ca(OH)2 (≥99%) and NaOH (≥99%) were purchased from Fisher Scientific Co. Canada.
γ-Al2O3 and α-Al2O3 were purchased from Zeochem Inc., US; and HZSM-5 was purchased
from Zibo Yinghe Chemical Company Limited, China. 100% CO2 and 100% N2 gas tanks
were supplied by Praxair Inc., Regina, Canada. 15% CO2 (N2 balance) gas tanks for the
Gas analyzer calibrations was also purchased from Praxair Inc., Regina, Canada. Standard
1N Hydrochloric acid for titration experiments was purchased from Sigma Aldrich Co.,
Canada.
3.3 Catalyst Preparation
Out of the seven catalysts screened, three were commercially obtained, which are:
BaCO3, CaCO3 and Ca(OH)2. The other four (K/MgO, Cs2O/α-Al2O3, Cs2O/γ-Al2O3 and
Hydrotalcite) were prepared in-house by following the preparation procedure from Cavani
et al. (1991), Climent et al. (2004), Diez et al. (2000) and Gorzawski et al. (1999) with
only few modifications. The preparation of Hydrotalcite was done following the procedure
outlined by Cavani et al. (1991) using the co-precipitation method. A solution containing
Al(NO3)3.9H2O and Mg(NO3)2.6H2O was prepared by dissolving calculated amounts of
these two precursors in a known quantity of water. A second solution consisting of NaOH
and Na2CO3 was also prepared. The two solutions were then co-added drop-wise at the
41
same rate into a beaker under constant stirring and keeping the pH of the solution at about
10. The product formed was kept at 333K for 16 hours. A white gelatinous precipitate was
formed, which was then filtered and washed until the pH obtained was 7. The product was
dried at 333K for 12 hours. The formed Hydrotalcite was finally calcined at 600oC for 6
hours and later cooled. The Hydrotalcite was then rehydrated by sprinkling about 10 ml of
water prior to its use.
Cs2O/α-Al2O3 and Cs2O/γ-Al2O3 were prepared following the procedure outlined
in Gorzawski et al. (1999) with little modifications. α-Al2O3 and γ-Al2O3 beads were
crushed and impregnated with prepared solutions of caesium acetate. For α-Al2O3, prior
to impregnation with caesium acetate, it was hydrothermally treated in a Parr reactor at
500oC for 2 hours and later dried for 12 hours. Upon impregnation with Caesium acetate,
both α-Al2O3 and γ-Al2O3 impregnated samples were stirred for approximately 2 hours
and finally calcined at 900oC for 2 hours for the decomposition of caesium acetate.
The steps outlined by Diez et al. (2000) were employed for the preparation of
K/MgO. Commercially-obtained Mg(OH)2 was calcined at 600oC for 2 hours to yield
MgO. A known concentration of KOH solution was prepared and impregnated on the
obtained MgO to give a final composition of 1mol% K on MgO. Upon impregnation, the
hydrated product was then dried for 12 hours and later calcined at 600oC for 2 hours. All
catalysts were pelletized to the desired size by passing through appropriate sieves after
being pressed using a 4-cm internal diameter die set under a hydraulic press.
42
3.4 Catalyst Characterization
The Brunauer-Emmett-Teller (BET) Surface Area, Pore Volume, and Average
Pore Size measurements and X-ray Diffraction (XRD) characterization experiments were
performed at the Chemical and Biological Engineering Department Laboratory at the
University of Saskatchewan, Saskatoon. The Temperature Programmed Desorption (TPD)
and Scanning Electron Microscope (SEM) experiments were conducted at the Clean
Energy Technologies and Research Institute (CETRI) laboratory at the University of
Regina.
The powder X-Ray Diffraction experiments were performed on a Rigaku Ultima
IV X-Ray Diffractometer, equipped with a Cu source (1.54056 Å), a CBO optical, and a
Scintillation Counter detector. The measurements were carried out on the Multipurpose
Attachment in the parafocusing mode, with a Kβ filter (Ni foils) inserted into the receiving
slit box. The intensity data were obtained over a 2θ scan range from 5° to 80°, with a scan
rate of 5° per minute and a step size of 0.02. The generator voltage and current were set to
40 kV and 40 mA, respectively. Identification of the crystalline phases were done using
the reference data from International Center for Diffraction Data (ICDD) and literature.
For the BET analysis, the instrument used was BET ASAP 2020 from
Micromeritics, Georgia, USA. The sample was degassed at 150oC for 5 hours. Nitrogen
gas was used during analysis. BJH method was employed to calculate the surface area,
pore volume and pore size obtained from the adsorption and desorption isotherms. 46
relative pressure points were recorded to give the Isotherm plots.
TPD measurements were done using a CHEMBET-3000 analyser with a TCD
Detector from Quantachrome Instruments. The catalyst sample was initially degassed by
43
being exposed to 100% helium gas accompanied by heating the furnace gradually to a
temperature of 250oC at 10oC/min ramping. The system was kept at this temperature for
60 minutes after which the temperature was reduced to 30oC. A 3% CO2 gas (balance
nitrogen gas) was introduced for 60 minutes at a flowrate of 30 ml/min for adsorption to
take place. The temperature was then increased to 700oC in a constant flow of helium gas.
The surface morphology of the prepared catalyst samples was investigated by
scanning electron microscopy (SEM) using a JEOL 5600 132-10 electron probe micro
analyser with an active area of 10 mm2. The sample was first crushed to obtain polished
flat surfaces and was then loaded into the specimen chamber. Beams were generated based
on the accelerating voltage of 25 kV. The positioning of the beam was controlled by the
computer software and micrographs were finally acquired.
3.5 Catalyst Screening
Absorption experiments for the catalyst screening were carried out at a temperature
of 45±1oC and at atmospheric pressure of 1 atm. For a fair basis of comparison, a catalyst
weight of 50g for each catalyst was used. A 4M BEA-AMP solvent concentration, solvent
volume of 500 ml and a constant stirring speed of 600 rpm were maintained throughout
all runs. The concentration was confirmed by titration with a 1N HCl solution. The
apparatus consisted of a 1000 ml three-necked round bottom flask immersed in a preheated
oil bath. The middle neck of the flask was equipped with a condenser while the other two
necks had a thermometer installed in one and a gas dispersion tube in the other to supply
a constant flow of gas into the filled flask. The catalyst (4 mm particle size) was carefully
placed in a stainless-steel basket and fully immersed into the solution by being suspended
44
with the aid of stainless steel wires ensuring no contact with the magnetic stirrer or bottom
of the flask as shown in figure 3.1. A non-catalytic (blank) run was also performed and
used as a baseline for comparing the performance of the various catalysts. The experiment
started with a known volume of solvent (500 ml) introduced into the flask; the filled flask
was then immersed into an oil bath which was heated to the desired absorption
temperature. Via the dispersion tube, the solvent was then bubbled through with a pre-
mixed gas of 15%CO2 (balance N2) at a flowrate of 650±5 ml/min. After reaching the
desired temperature, samples were taken at regular intervals of 5 minutes during the first
hour and subsequently at intervals of 30 minutes. This was done to measure the CO2
loadings at those time intervals with the aid of the Chittick apparatus as described by Ji et
al., 2009. Sampling continued until the solution attained equilibrium at 10 hours (600
minutes) of running time. Solutions were filtered prior to measuring their CO2 loadings in
order to eliminate catalyst particle interference with loading measurements. CO2 loading
(mol CO2/mol amine) versus time (minutes) curves were generated and slopes of the linear
portion of these curves gave the initial rate of absorption. Following the selection of the
suitable catalyst, γ-Al2O3 and Colloidal Silica (40 wt. %) were employed as binders for the
selected catalyst in order to be used in the absorption unit of the bench-scale Pilot plant.
Their effect on the overall performance of the selected catalyst was also tested under the
same experimental conditions of the absorption experiments. This was to ensure that there
was no added contribution or adverse effect whatsoever from the binders. Operating
conditions for the experimental run is summarised in Table 3.1.
45
Figure 3.1 Experimental set-up of semi-batch run for catalyst screening
Table 3.1Operating conditions of the semi-batch catalyst screening experiments
Parameter Value
Gas flowrate 650 ml/min
Liquid volume 500 ml
Absorption temperature 45oC
CO2 in feed gas 15%
Catalyst weight 50g
46
3.6 Pilot plant
The system consisted of two lagged stainless-steel columns each with dimensions
of 3.5ft (1.067 m) in height and having an internal diameter of 2 inches (0.0508m). The
absorption column was designed with 4 ports, being the gas inlet, off-gas outlet, lean-
solvent inlet and rich-solvent outlet. However, the desorber column has 3 ports namely;
rich-solvent inlet, lean-solvent outlet and CO2 product gas outlet. Both columns were
equipped with 5.08 cm LDX sulzer structured packing arrangement with the solid base
catalyst beds interspersed between them for that of the absorption column. The absorber
column had the desired solid base catalyst weight evenly distributed between any two
structured packing. Also, the desorber column packing arrangement enclosed a solid acid
catalyst bed (HZSM-5) mixed with 3 mm inert marbles. Between the structured packing
arrangement and the catalyst bed-3mm inert marbles section, were 6 mm inert marbles
which acted as support for the catalyst bed-3mm inert marbles section. The bench-scale
pilot plant, absorber and desorber beds arrangement are shown in figures 3.2 and 3.3
respectively.
The key feature of the experimental set-up was the replacement of the reboiler in
conventional systems with a rich amine heater. A typical experimental run began with the
lean amine solvent, with desired concentration and flowrate, fed from the storage tank to
the top of the absorber column via a variable-speed gear pump. At the same time the
heating bath was set to the desired temperature to heat up the rich amine prior to entering
the desorber. Once amine solvent circulation was set, a mixture of CO2 and N2 gas at the
appropriate CO2 concentration of 15% was introduced to the bottom of the absorber
column via a gas flow meter, after being passed through a saturator, where it was met by
47
a counter-current flow of lean amine solvent from the top of the column. Here, a three-
phase system was set-up comprising the amine solvent, CO2-N2 gas and solid base catalyst.
The catalyst aids in the faster rate of CO2 absorption. Treated gas exited the top of the
column while the rich amine solvent exited at the absorber bottom and exchanged heat
with the hot lean amine stream coming from the bottom of the desorber. The rich amine
stream was further heated, through a heat-exchanger network, by the heating medium. The
heated rich amine stream was then fed to the top of the desorber column. Upon contacting
the catalytic desorber bed, further desorption was enhanced by the catalyst bed and the
lean amine exited the bottom of the desorber, was cooled and then fed into the absorber
column making a complete cycle. A condenser was employed to cool the CO2 product gas
exiting the top of the desorber column so as to remove any entrained water after which the
product gas was dried by a desiccant bed prior to being measured by the rotameter.
The absorber column temperature profile was consistently monitored to check for
equilibrium attainment. At equilibrium, the CO2 concentrations in the gas phase along the
absorber and temperature profiles in both columns were measured using the Infra-Red (IR)
gas analyzer from Nova Analytical Systems Inc., Canada and J-type thermocouples from
Cole Parmer Inc., Canada respectively. Also, lean and rich amine samples were taken from
the bottom of both columns to determine the lean and rich CO2 loadings (liquid phase CO2
concentrations). The CO2 loadings were determined using a Chittick apparatus as
described by Ji et al. (2009). Loading measurements were done thrice to ensure accuracy.
Loading errors were as low as ±0.01. Likewise, gas phase CO2 concentrations at the inlet
and outlet of the absorber column were taken twice also to ensure accuracy in
measurements. Prior to this, the IR gas analyzer was calibrated with a 15% CO2 premixed
48
gas. The gas phase CO2 concentration obtained using the IR gas analyzer recorded errors
with magnitude of ±0.2. A mass balance error calculation for the entire system was done
to determine the validity of each run. This error analysis compares the quantity of CO2
removed from the gas phase to the CO2 quantity absorbed by the liquid phase. A value of
≤10% was considered a valid run. Prior to extracting data for use, the pilot plant set-up
was validated by comparing with previous work by Decardi-Nelson (2016). Results are
shown in the next chapter.
49
Figure 3.2 Schematic representation of bench-scale pilot plant experimental set-up
50
Figure 3.3 Absorber and desorber columns packing and catalyst bed arrangement
51
Table 3.2 Typical operating conditions of bench-scale pilot plant system
Parameter Value
Feed Gas flowrate 15 slpm
CO2 concentration in feed gas 15%
Solvent flowrate 60 ml/min
Absorber and Desorber Catalyst weight 150 g
Amine temperature at absorber inlet 30oC
Average desorber bed temperature 85 oC
Pressure in both columns 1 atm
Lean loading 0.2 – 0.42 mol/mol
52
CHAPTER 4: RESULTS AND DISCUSSION
This section is broadly divided into two: the first looks at the solid alkaline catalyst
screening and selection (semi-batch runs) results while the second part reports on the
results on its application in the full-cycle bench-scale pilot plant. The latter is further
broken down into the evaluation of the kinetic performance of the novel solvent blend with
the addition of heterogeneous acid and alkaline catalysts as well as kinetic parameter
estimations of the absorption process. Finally, the effects of various process parameters on
CO2 conversion is discussed.
4.1 Catalyst Characterization
The X-ray diffraction spectra for all catalysts studied are shown in Figures 4.1 to
4.7. The XRD peaks of crystallized powders of BaCO3 are in agreement with the reflection of
a pure orthorhombic structure and single phase of BaCO3 (witherite). This was also evident in
the works of Zelati et al. (2011) and Salehizadeh et al. (2018). That of CaCO3 revealed the
presence of a single rombohedrical crystal structure corresponding to a single calcite phase
which is the most thermodynamically stable form of CaCO3 predominant at room
temperature. Won et al. (2010), Harris et al. (2015) and Render et al. (2016) also reported
similar phase appearance corresponding to calcite. The XRD pattern of the commercially
obtained Ca(OH)2 revealed a predominant portlandite phase and a peak corresponding to
CaCO3 which corroborates findings in literature (Khachani et al., 2014; Saoud et al.,
2014). The sharp distinct peaks present in the Hydrotalcite sample reflect the presence of
a layered double hydroxide which is characteristic of Magnesium-Aluminum
53
Hydrotalcites (Meira et al., 2006; Macala et al., 2008; Obadiah et al., 2012; Yanming et
al., 2013). Other smaller peaks obtained revealed the presence of gibbsite, brucite and
MgO periclase phases (Meira et al., 2006). Figures 4.5 and 4.6 show the diffraction
patterns obtained for Cs2O/γ-Al2O3 and Cs2O/α-Al2O3 respectively. They both showed
phases corresponding to their constituents as well as other alumina phases. The alumina
phases present in both samples were γ-Al2O3, α-Al2O3 and θ-Al2O3 (Kakooei et al., 2012;
Hu et al., 2015). XRD pattern of K/MgO revealed distinct phases of MgO periclase, brucite
(Mg(OH)2), and very subtle KOH phases. The results are in close agreement with those in
the literature (Jimenez et al., 2006; Diez et al., 2006).
SEM images of the catalysts studied are shown in Figure 4.8 where their surface
morphology and distribution of active species can be seen. From Figure 4.8, CaCO3
particles show a very large degree of agglomeration while that of BaCO3 displays a rather
smooth appearance. It can also be observed that both Hydrotalcite and Cs2O/ γ-Al2O3 show
a somewhat flaky appearance. The surface morphology of K/MgO and Cs2O/ α-Al2O3
catalysts are seen to be very porous with the distribution of the active site K clearly evident
for the K/MgO catalyst. The hydrothermal treatment of the Cs2O/ α-Al2O3 may have
resulted in improving the surface characteristics of the catalyst. This is not unusual as can
be seen from the works of Kovanda et al. (2009) and Jung et al. (2008) where
improvements in physical characteristics of Ni-Al layered double hydroxides and CuO-
CeO2 were observed after undergoing hydrothermal treatment. The surface morphology,
which is a physical characteristic of the catalyst, helps in explaining the superior
performance of one catalyst over the other as will be seen in subsequent sections.
54
The TPD profiles of the catalysts are shown in Figures 4.9 and 4.10 with the
exception of BaCO3 and CaCO3 since they do not desorb CO2 but rather undergo
decomposition at very high temperatures (Arvanitidis et al., 1996; Galan et al., 2013).
55
Figure 4.1 XRD pattern of BaCO3 catalyst
Figure 4.2 XRD pattern of CaCO3 catalyst
0
500
1000
1500
2000
2500
3000
3500
0 10 20 30 40 50 60 70 80 90
Inte
nsi
ty (a
.u.)
2 theta
BaCO3
0
1000
2000
3000
4000
5000
6000
7000
8000
9000
10000
0 10 20 30 40 50 60 70 80 90
Inte
nsi
ty (a
.u.)
2 theta
CaCO3
56
Figure 4.3 XRD pattern of Ca(OH)2 catalyst
Figure 4.4 XRD pattern of Hydrotalcite catalyst
0
200
400
600
800
1000
1200
1400
0 10 20 30 40 50 60 70 80 90
Inte
nsi
ty (a
.u.)
2 theta
Ca(OH)2
CaCO3
Ca(OH)2
CaCO3
0
200
400
600
800
1000
1200
1400
1600
1800
0 10 20 30 40 50 60 70 80 90
Inte
nsi
ty
2 theta
HTMgO periclasebrucitegibbsite
57
Figure 4.5 XRD pattern of Cs2O/ γ-Al2O3 catalyst
Figure 4.6 XRD pattern of Cs2O /α-Al2O3 catalyst
0
200
400
600
800
1000
1200
0 10 20 30 40 50 60 70 80 90
Inte
nsi
ty
2 theta
γ-Al2O3
θ-Al2O3
α-Al2O3
Cs2O
0
200
400
600
800
1000
1200
1400
1600
1800
2000
0 10 20 30 40 50 60 70 80 90
Inte
nsi
ty
2 theta
α-Al2O3
γ-Al2O3
θ-Al2O3
Cs2O
58
Figure 4.7 XRD pattern of K/MgO catalyst
0
1000
2000
3000
4000
5000
6000
7000
0 10 20 30 40 50 60 70 80 90
Inte
nsi
ty
2theta
MgO periclase Mg(OH)
2
KOH
\
a b
59
Figure 4.8 SEM images of catalysts studied (a) BaCO3 (b) CaCO3 (c) Ca(OH)2 (d)
Hydrotalcite (e) Cs2O/γ-Al2O3 (f) Cs2O/α-Al2O3 (g) K/MgO
c d
e f
g
60
Figure 4.9 TPD profiles of catalysts studied
Figure 4.10 TPD profile of Cs2O/γ-Al2O3
-20
80
180
280
380
480
580
680
0 200 400 600 800 1000 1200
sign
al (
a.u
.)
Temperature (oC)
K/MgO Hydrotalcite Cs2O/a-Al2O3 Cs2O/g-Al2O3 Ca(OH)2
0
5
10
15
20
0 200 400 600 800 1000
Sign
al (a
.u.)
Temperature (oC)
61
4.2 Catalyst Screening Results (Semi-batch runs)
The CO2 absorption profiles for all catalysts studied are presented in Figures 4.11
and 4.12. The slopes of the linear portion of these profiles were extracted and represents
the initial CO2 absorption rates into the solvent in the presence of the various catalysts
studied. The criterion for linearity was the coefficient of determination, R2 within a
specific period. A value of 95% or greater was accepted. Detailed plots showing the linear
portions used for the initial absorption rates calculation are shown in figures 4.13 to 4.22
and the results are summarised in Table 4.1. The initial absorption rate can be expressed
as:
𝐼𝑛𝑖𝑡𝑖𝑎𝑙 𝑎𝑏𝑠𝑜𝑟𝑝𝑡𝑖𝑜𝑛 𝑟𝑎𝑡𝑒 = 𝐶𝑂2𝑙𝑜𝑎𝑑𝑖𝑛𝑔 (
𝑚𝑜𝑙 𝐶𝑂2𝑚𝑜𝑙 𝑎𝑚𝑖𝑛𝑒
)×𝑎𝑚𝑖𝑛𝑒 𝐶𝑜𝑛𝑐𝑒𝑛𝑡𝑟𝑎𝑡𝑖𝑜𝑛 (𝑚𝑜𝑙 𝑎𝑚𝑖𝑛𝑒
𝐿 )
𝑡𝑖𝑚𝑒 (𝑚𝑖𝑛𝑢𝑡𝑒𝑠) (4.1)
62
Figure 4.11 CO2 absorption profiles of various catalysts understudied
0
0.1
0.2
0.3
0.4
0.5
0.6
0 100 200 300 400 500 600 700 800
Load
ing
(mo
l CO
2/m
ol a
min
e)
time (minutes)
blank
BaCO3
K/Mgo
Hydrotalcite
Ca(OH)2
Cs2O/g-Al2O3
CaCO3
Cs2O/a-alumina
K/MgO+g-alumina
K/MgO + CS
63
Figure 4.12 Linear portion of CO2 absorption profiles
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
0.4
0 50 100 150 200 250 300
load
ing
(mo
l/m
ol)
time (min)
K/MgO
Cs2O/a-aluminaCa(OH)2
BaCO3
Cs2O/g-aluminaHydrotalcite
blank
CaCO3
64
Figure 4.13 Initial rate determination of blank run (solvent only)
Figure 4.14 Initial rate determination of CaCO3
y = 0.0013x + 0.0175R² = 0.9962
0.00
0.05
0.10
0.15
0.20
0.25
0.30
0.35
0 50 100 150 200 250 300
Load
ing
(mo
l /m
ol)
Time (min)
y = 0.0012x - 0.0005R² = 0.9952
0.00
0.05
0.10
0.15
0.20
0.25
0.30
0.35
0 50 100 150 200 250 300
load
ing
(mo
l/m
ol)
Time (min)
65
Figure 4.15 Initial rate determination of BaCO3
Figure 4.16 Initial rate determination of Ca(OH)2
y = 0.0014x + 0.0155R² = 0.9903
0.00
0.05
0.10
0.15
0.20
0.25
0.30
0.35
0.40
0 50 100 150 200 250 300
load
ing
(mo
l/m
ol)
Time (min)
y = 0.0015x + 0.0081R² = 0.9902
0.00
0.05
0.10
0.15
0.20
0.25
0.30
0.35
0.40
0 50 100 150 200 250 300
load
ing
(mo
l/m
ol)
Time (min)
66
Figure 4.17 Initial rate determination of Cs2O/γ-Al2O3
Figure 4.18 Initial rate determination of Cs2O/ α-Al2O3
y = 0.0014x + 0.0222R² = 0.9883
0.00
0.05
0.10
0.15
0.20
0.25
0.30
0.35
0.40
0 50 100 150 200 250 300
load
ing
(mo
l/m
ol)
Time (min)
y = 0.0015x + 0.0248R² = 0.9939
0.00
0.05
0.10
0.15
0.20
0.25
0.30
0.35
0.40
0 50 100 150 200 250 300
load
ing,
mo
l CO
2/m
ol a
min
e
Time,min
67
Figure 4.19 Initial rate determination of Hydrotalcite
Figure 4.20 Initial rate determination of K/MgO
y = 0.0013x + 0.019R² = 0.9918
0.00
0.05
0.10
0.15
0.20
0.25
0.30
0.35
0.40
0 50 100 150 200 250 300
load
ing
(mo
l/m
ol)
Time
y = 0.0015x + 0.0228R² = 0.9928
0.00
0.05
0.10
0.15
0.20
0.25
0.30
0.35
0.40
0 50 100 150 200 250 300
load
ing
(mo
l/m
ol)
time
68
Fig 4.21 Initial rate determination of K/MgO + Colloidal Silica binder
Fig. 4.22 Initial rate determination of K/MgO+γ-Al2O3 binder
y = 0.0015x + 0.0238R² = 0.9908
0.00
0.05
0.10
0.15
0.20
0.25
0.30
0.35
0.40
0.45
0 50 100 150 200 250 300
load
ing
(mo
l/m
ol)
time
y = 0.0014x + 0.0276R² = 0.9846
0.00
0.05
0.10
0.15
0.20
0.25
0.30
0.35
0.40
0 50 100 150 200 250 300
load
ing
(mo
l/m
ol)
time
69
Table 4.1. Initial rate of absorption for solid alkaline catalysts studied
Catalyst Initial rate of absorption
(mol/L.min) × 103
Percentage increase
with respect to blank
run (%)
Blank (solvent only) 5.2 0
BaCO3 5.6 7.7
CaCO3 4.8 -7.7
Hydrotalcite 5.2 0
Ca(OH)2 6.0 15.4
Cs2O/γ-Al
2O
3 5.6 7.7
Cs2O/α-Al
2O
3 6.0 15.4
K/MgO 6.0 15.4
K/MgO + CS binder 6.0 15.4
K/MgO + γ-alumina binder 5.6 7.7
70
Lewis base catalysts (K/MgO, Ca(OH)2, Cs2O/γ-Al2O3, BaCO3, Cs2O/α-Al2O3 and
CaCO3) are electron donors whereas the Bronsted base catalyst (Hydrotalcite) is a proton
acceptor. From the graphs, it was observed that K/MgO, Ca(OH)2 and Cs2O/α-Al2O3 (all
Lewis bases), recorded the fastest rates of absorption, followed by Cs2O/γ-Al2O3, BaCO3,
Hydrotalcite, blank and CaCO3 in decreasing order of absorption rates. The trend observed
can be summarised as: K/MgO ~ Ca(OH)2 ~ Cs2O/α-Al2O3 > Cs2O/γ-Al2O3 ~ BaCO3 >
Hydrotalcite ~ blank > CaCO3. The trend can be explained on the basis of the mechanism
of CO2 reactions with amines. As mentioned earlier, the zwitterion formation step in the
zwitterion mechanism happens to be the rate determining step. This step involves the
transfer of electrons. Therefore it is imperative that an electron transfer process will be
enhanced in the presence of electrons. The presence of O2- anions of unsaturated co-
ordination accounts for the basic sites in Lewis solid base catalysts thereby possessing the
ability to release their electrons ahead of the amine solvents to enhance the reactivity of
CO2 with amines, and later recover them from these amines.
Generally, this results in faster kinetics as can be seen when one compares the
initial rate of absorption of the blank (solvent only) to that of catalysts incorporated into
the system. The lower value in initial rate for the CaCO3 catalyst – though a Lewis base –
when compared with the blank case can be due to the strong bonds between the oxide
anions and carbon existing within the CaCO3 molecule, hence making it difficult for
electrons to break away. This may have in a long run altered the mechanism of the reaction,
thus adversely affecting the rate of CO2 absorption and resulting in lower rates when
compared to the blank. Also, as can be seen from the SEM results in Figure 4.8, CaCO3
71
show a large degree of agglomeration which may also have resulted in its rather poor
performance.
K/MgO recorded one of the fastest rates of absorption. According to Chen et al.
(2013), the generation of super basic sites was related to the existence of these O2- anion
vacancies in MgO and its accompanying electrical induction effect. Jimenez et al. (2006)
reported on an interaction between K and Mg in MgO resulting in the weakening of the
Mg-O bonds and therefore aiding in the easy migration of the O2- anion species. They also
indicated that with the introduction of K, the amount and stability of carbonates on the
MgO surface is very minimal, which thereby improves upon the basicity of the catalyst –
since carbonates are known to inhibit the formation of active oxygen species. Another role
of K is to poison acidic sites, hence increasing the catalyst basicity (Ono and Hattori,
2011). In the presence of the amine, the electron-rich anion species (O2-) easily attack
dissolved CO2, and this interaction ties the CO2 molecules to the surface of the catalyst,
making them readily available for the Nitrogen (N) atom of the amine. In this way, a
greater contact time is realized between the amine solvent and CO2 hence enhancing the
rate of reaction. The very porous nature and large number of basic sites (Figure 4.9) of the
K/MgO catalyst may also have contributed to its superior performance.
Apart from O2- anion species, OH- ions also account for basicity. This was the case
for Ca(OH)2 which had comparable absorption results with K/MgO. From the TPD results,
Ca(OH)2 was seen to exhibit very strong basic sites and its high performance can be due
to this property. Although the number of basic sites was much smaller than that of K/MgO,
its strength resulted in comparable results with K/MgO. The performance of Cs2O/α-Al2O3
was at par with K/MgO and Ca(OH)2, though it showed slightly lower basic strengths from
72
its TPD profile when compared to the latter two. Again, it possesses a very porous structure
which may have resulted in its rather good performance. The reason for this can be due to
the hydrothermal treatment given to α-Al2O3 which may have improved its physical
properties including surface area of the catalyst as well as pore and crystallite sizes. A
number of studies have shown an improvement in the physical and chemical properties of
catalysts when they underwent hydrothermal treatments. This is evident in the work of
Kovanda et al. (2009) where an increase in pore size, crystallite size as well as an
improvement in thermal stability was observed when Ni-Al layered double hydroxides and
other mixed oxides were hydrothermally treated. Jung et al. (2008) reported on an
enhancement in the chemical stability of CuO-CeO2 where cuprous ion was shown to have
migrated to the surface of catalyst leading to an increase in surface concentration of copper
and the subsequent formation of cupric oxide on the surface of catalyst.
BaCO3 and Cs2O/γ-Al2O3 exhibited moderate activities. It is interesting to note that
Cs2O/γ-Al2O3 exhibited the lowest number of basic sites as can be seen from Figure 4.10.
Hydrotalcite barely showed any activity. Since Hydrotalcite is a bronsted base (proton
abstractor), its contribution is insignificant in the CO2-amine mechanism, thus explaining
its low performance. Despite their high activities, Ca(OH)2 and Cs2O/α-Al2O3 exhibited
very poor mechanical stability and were found to disintegrate easily even after pelletizing.
K/MgO on the other hand was found to possess good mechanical stability. Consequently,
K/MgO was selected and its application was transferred to a bench-scale pilot plant. Prior
to transferring its application to the bench-scale pilot plant (which is subject to agitations
from process equipment), it was imperative that we improved upon the mechanical
stability of K/MgO without altering its activity or performance. Thus, binders such as
73
40wt% Colloidal Silica (CS) and γ-alumina were added. No change in activity was seen
with the CS binder but a drop in activity was observed with the γ-alumina binder. Hence
the CS binder was selected for use with K/MgO.
4.3 Pilot Plant Studies
As stated in the previous chapter, the pilot plant set-up was validated prior to
extracting data for use. Results for 5M MEA on CO2 concentration profile in absorber and
temperature profiles in both absorber and desorber are shown in figures 4.23 to 4.25. The
results show very close agreement between the both works with a maximum AAD of
2.15%. Minimum deviations in data may be associated with fluctuations in process
conditions such as total gas flowrate, amine inlet temperature to absorber, inlet gas phase
CO2 concentration and others, during experimental runs.
4.3.1 Kinetic Performance of BEA-AMP, MEA-MDEA and MEA (Effect of solid
acid catalyst)
The Kinetic performance of the three solvents were evaluated in terms of CO2
conversion and rate at which this conversion occurs in the presence and absence of a solid
acid catalyst, HZSM-5. The kinetic data were obtained from an integral type (plug-flow)
reactor and rate of reaction was determined by using the differential method of analysis.
CO2 conversion and rate of reaction are expressed as:
𝑋𝐶𝑂2=
𝐶𝑂2,𝑖𝑛−𝐶𝑂2,𝑜𝑢𝑡
𝐶𝑂2,𝑖𝑛
(4.2)
74
−𝑟𝐴 =𝑑𝑋𝐴
𝑑(𝑉/𝐹𝐴0)=
𝑑𝑋𝐶𝑂2
𝑑(𝑉/𝐹𝐶𝑂20) (4.3)
The absorption rates were obtained by taking the slopes of 𝑋𝐶𝑂2versus 𝑉/𝐹𝐶𝑂20 curves and
evaluating them at different points on the reactor. The average rate of absorption was
determined by taking the logarithmic mean of the rates at specific points along the column.
Other performance parameters were cyclic capacity, which represents the quantity of CO2
absorbed in the liquid phase, and CO2 removal efficiency (absorber efficiency) which
represents the quantity of CO2 removed from the gas phase. They are represented in the
form:
Cyclic capacity (kg/hr) = 60 × 106 × FAm × MWCO2× (αrichCAm,rich − αleanCAm,lean) (4.4)
Removal efficiency (%) =V̇inXCO2,in−V̇outXCO2,out
V̇inXCO2,in×
60×103MWCO2
Vm,CO2
× 100% (4.5)
For the absorber, gas phase CO2 concentrations were obtained along the column. The
desorber is not equipped with sampling points along the column, hence CO2 loading
(liquid phase CO2 concentration) at the top and bottom of the column were used in
determining CO2 conversion and finally the rate of desorption. Thus, for the rate of
desorption, the derivative in the above equation becomes a finite difference, ∆.
The novel solvent, BEA-AMP was tested based on comparative runs with the
conventional MEA and MEA-MDEA solvent blend at the bench-scale pilot plant level.
Akachuku (2016), Osei et al. (2017), Decardi-Nelson et al. (2017) and Srisang et al. (2017)
studied the use of solid acid catalyst (HZSM-5) on the latter two solvents. Therefore, in
this work we compared the novel solvent with these solvents on the same basis of
employing the solid acid catalyst (HZSM-5) in the desorber. Figures 4.26, 4.27, 4.28 and
75
4.29 show the absorption rates, desorption rates, absorption efficiency and cyclic
capacities respectively of the three solvents in the absence and presence of the solid acid
catalyst (HZSM-5). From these figures, it can be observed that the novel solvent, BEA-
AMP outperformed the other two, both in the absence and presence of the catalyst. For the
blank case (solvent only), percentage increments of 110% and 79% in cyclic capacity were
recorded for BEA-AMP compared to MEA and blended MEA-MDEA respectively. With
the addition of the desorber catalyst (HZSM-5) to all three solvent systems, values of 97%
and 66% increase in cyclic capacity for BEA-AMP over MEA and blended MEA-MDEA
respectively were observed. Similar increments were observed in absorption efficiency.
The CO2 concentration and temperature profiles in the absorber are shown in figures 4.30
and 4.31 respectively. The above trend is supported in these profiles where it is observed
that the largest bulge in the absorber temperature profile and lowest exit CO2 concentration
corresponds to BEA-AMP signifying higher reactivity of this solvent over the other two
for both cases of blank (solvent only) and the inclusion of HZSM-5 in the desorber.
Comparatively, lower gas phase CO2 concentrations and larger temperature bulges in the
absorber were observed with the addition of HZSM-5 in the desorber as compared to runs
with solvents only.
76
Figure 4.23 Validation of CO2 concentration profile along absorber for 5M MEA by
comparison with Decardi-Nelson (2016)
Figure 4.24 Validation of temperature profile along absorber for 5M MEA by
comparison with Decardi-Nelson (2016)
0
5
10
15
20
25
30
35
40
10 11 12 13 14 15 16
Hei
ght
fro
m b
ott
om
(in
ches
)
CO2 concentration (vol%)
Decardi-Nelson (2016)
This work
AAD = 2.15%
0
5
10
15
20
25
30
35
40
25 27 29 31 33 35
he
igh
t fr
om
bo
tto
m, i
n
temperature, C
Decardi-Nelson (2016)
this work
AAD = 0.45%
77
Figure 4.25 Validation of temperature profile along desorber for 5M MEA by
comparison with Decardi-Nelson (2016)
Table 4.2 Validation operating conditions for 5M MEA for comparison with Decardi-
Nelson (2016)
Parameter Condition
Gas flowrate 15 slpm
CO2 concentration in feed gas 15%
Liquid flowrate 60 ml/min
Average desorber bed temperature 85oC
Operating pressure 1 atm
0
5
10
15
20
25
30
35
40
70 75 80 85 90 95
hei
ght
fro
m b
ott
om
(in
)
temperature (oC)
Decardi-Nelson (2016)
this work
AAD = 1.82%
78
4.3.1.1 Absorber performance
For the blank run, the 4M BEA-AMP blend had the highest CO2 absorption rate,
followed by 7M MEA-MDEA, with 5M MEA being the slowest. This could be explained
on the basis of their structural properties and lean loadings. As stated by Narku-Tetteh et
al. (2017), BEA has an alkyl (butyl) group (which is electron-donating) in its structure
which tends to increase the electron density around Nitrogen (N) hence increasing the
reactivity of the amine, whereas MEA has a hydrogen atom, H (lower electron donating
ability) in place of the butyl group in BEA. Since alkyl groups are more electron donating
than H, a higher reactivity is observed for BEA. Also in the same work, Narku-Tetteh et
al. (2017) showed an amine selection chart (figure 4.32) where absorption and desorption
parameters were compared for a number of single amine solvents after they developed two
performance parameters namely, “Absorption Parameter” and “Desorption Parameter”. In
this chart, it was shown that AMP exhibited a relatively higher absorption parameter than
MEA. Hence a higher reactivity over MEA is rightly seen. Thus, the BEA-AMP blend
outperforms MEA in the rate of CO2 absorption. The BEA-AMP blend similarly
outperformed the conventional MEA-MDEA blend. This is because MDEA possesses two
–OH groups (electron-withdrawing) in its structure attached to Nitrogen atom of the amine
which tends to decrease the electron density around it, hence resulting in lowering the
reactivity of the MEA-MDEA blend. However, a higher rate of absorption is observed for
MEA-MDEA blend as compared to MEA. This could be due to the difference in solvent
lean loadings as MEA had a higher lean loading of 0.42 mol CO2/mol amine whereas
MEA-MDEA blend had a lower lean loading of 0.35 mol CO2/mol amine. Thus, a lower
amount of CO2 was present in the MEA-MDEA blend, meaning more active free amines
79
were available, therefore allowing a greater driving force for reaction, hence the observed
trend. Table 4.3 displays the lean loadings obtained for the three solvents.
Similarly, with the incorporation of the solid acid catalyst, HZSM-5, in the
desorber, an identical trend was observed but at faster rates when compared to the blank
case. This is because the inclusion of the catalyst in the desorber provided an alternative
pathway where there was a greater weakening of the N-C bond in carbamate, leading to a
faster and greater release of CO2 from the solvents. Hence, a considerable drop in solvent
lean loadings led to higher reactivity in the absorber as compared to the blank run of no
catalysts in both columns. BEA-AMP still emerged as the fastest in absorption rate while
MEA was the least reactive An increase in absorption rate of 26% was observed for BEA-
AMP while the MEA-MDEA blend and MEA had a 14% and 12% respective increase in
absorption rate with the inclusion of HZSM-5.
4.3.1.1 Desorber performance
From figure 4.27, it can be observed that for the blank case, BEA-AMP blend had
the highest desorption rate, followed by MEA-MDEA blend, with MEA being the slowest.
As stated previously and shown in figure 4.32, it is observed that the single solvents
comprising the novel blend, BEA and AMP had considerably higher absorption and
desorption parameter values than MEA. The BEA-AMP blend having the highest
desorption rate can be attributed to the steric hindrance effect of AMP as it forms a highly
unstable carbamate which easily breaks down to form bicarbonate ions, and enhances
desorption of CO2. Also, the longer alkyl group (butyl) in the BEA structure forms a bulky
carbamate also making it unstable and is easily broken down thus enhancing CO2
80
desorption. As stated earlier, MEA has an H in place of the alkyl group hence it forms a
stable carbamate making it difficult to release CO2. MDEA, being a tertiary amine, forms
bicarbonate ions which accepts protons to form carbonic acid and finally releases CO2.
Hence, MDEA blended with MEA increased the desorption rate of CO2 as compared to
single MEA solvent. Also, BEA-AMP had a higher desorption rate than MEA-MDEA.
Aside the effect of the sterically-hindered AMP, the secondary amine, BEA has an electron
donating group (butyl) attached to the Nitrogen, N of the amine, whereas MDEA has two
electron-withdrawing groups (–OH groups) attached to N as explained earlier. Due to this,
a higher electron density is generated around N in BEA-AMP making the amine more
reactive than the lower electron density-N in MEA-MDEA.
With the addition of the solid acid HZSM-5 catalyst, a similar trend resulted but at
faster desorption rates. The effect of the catalyst is seen with an increase in desorption
rates for all the three solvents. BEA-AMP recorded an increase of 17% in the CO2
desorption rate, while MEA-MDEA blend and MEA had an increase of 41% and 35%
respectively. The presence of the catalyst lowers the activation energy by providing an
alternative catalytic pathway. According to Akachuku (2016), HZSM-5 has both Lewis
and Bronsted acid sites which play an important role in increasing the rate of CO2
desorption. For a bronsted acid site, a proton is donated to the carbamate ion converting it
to carbamic acid. Chemisorption on the Al site weakens the N-C bond causing CO2 to
break away. Also, a proton can be transferred to bicarbonate ion which eventually leads to
the release of CO2. For the Lewis acid site, Al3+ (which lacks electrons), an attack is made
on the high electron density Nitrogen (N) in carbamate, again weakening the N-C bond.
CO2 consequently breaks away. The novel solvent thus exhibited better performance than
81
the conventional solvents for the full cycle operation of the pilot plant in both cases of
solvent run only and catalyst inclusion in the desorber.
82
Figure 4.26 CO2 absorption rates of MEA, MEA-MDEA and BEA-AMP with and without
HZSM-5 in desorber
Figure 4.27 CO2 desorption rates of MEA, MEA- MDEA and BEA-AMP with and
without HZSM-5 in desorber
0.0086 0.0089
0.0149
0.01180.0128
0.0181
0
0.002
0.004
0.006
0.008
0.01
0.012
0.014
0.016
0.018
0.02
MEA MEA-MDEA BEA-AMP
reac
tio
n r
ate
(mo
l/L.
min
)
solvent
blank HZSM-5
0.0167
0.024
0.035
0.023
0.034
0.041
0
0.005
0.01
0.015
0.02
0.025
0.03
0.035
0.04
0.045
MEA MEA-MDEA BEA-AMP
reac
tio
n r
ate
(mo
l/L.
min
)
solvent
blank HZSM-5
83
Figure 4.28. CO2 absorption efficiency of MEA, MEA- MDEA and BEA-AMP with and
without HZSM-5 in desorber
0
10
20
30
40
50
60
MEA MEA-MDEA BEA-AMP
abso
rpti
on
eff
ieci
eny
(%)
SOLVENT
by CO2 mass flow by CO2% by loading
84
Figure 4.29. CO2 cyclic capacity of MEA, MEA- MDEA and BEA-AMP with and without
HZSM-5 in desorber
0
0.02
0.04
0.06
0.08
0.1
0.12
0.14
MEA MEA-MDEA BEA-AMP
cycl
ic c
apac
ity
(kg/
hr)
Solvent
blank HZSM-5
85
Figure 4.30 CO2 concentration profile along absorber
0
0.2
0.4
0.6
0.8
1
1.2
6 7 8 9 10 11 12 13 14 15 16
Hei
ght
fro
m b
ott
om
(m
)
CO2 concentration (%)
MEA blank MEA-MDEA blank BEA-AMP blank
MEA HZSM-5 MEA-MDEA HZSM-5 BEA-AMP HZSM-5
86
Figure 4.31 Temperature profile along absorber
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
6 11 16 21 26 31 36 41 46 51
Hei
ght
fro
m b
ott
om
(m
)
Temperature (oC)
MEA blank MEA-MDEA blank BEA-AMP blank
MEA HZSM-5 MEA-MDEA HZSM-5 BEA-AMP HZSM-5
87
Table 4.3 Solvent lean loading of solvents studied
Lean loading (mol
CO2/mol amine)
5M MEA 5/2M MEA-
MDEA
2/2M BEA-AMP
no catalyst 0.42 0.35 0.33
HZSM-5 catalyst
(Si/Al = 19) catalyst
0.41 0.32 0.30
Figure 4.32 Amine Selection Chart ( Narku-Tetteh et al., 2017)
0.000
0.100
0.200
0.300
0.400
0.500
0.600
0.700
0.800
0.900
0.0000 0.0100 0.0200 0.0300 0.0400 0.0500 0.0600 0.0700
Abso
rpti
on p
aram
eter
,*10
-2(m
ol
CO
2ab
sorb
ed)2
/(m
ol
amin
e.m
in.L
solt
n)
Desorption Parameter,
*10-2 (mol CO2 desorbed)3/ (kJ.(Lsoltn)2.min
MEA
AMP
BEA
tBEA
BDEA
tBDEA
4-A-1B
MDEA
88
4.3.2 Kinetic Performance of BEA-AMP (Effect of Solid alkaline and acid catalysts)
The selected solid base catalyst (K/MgO) from the screening results was
transferred to the absorption column of the bench-scale pilot plant in conjunction with the
novel solvent 4M BEA-AMP (2/2) and solid acid catalyst (HZSM-5) in the desorber. A
catalyst weight of 150g and average desorber bed temperature of 85oC were used. This
selected catalyst weight was based on previous studies (Akachuku, 2016) where 150g of
a solid acid catalyst (HZSM-5) for the desorber was the optimum weight after performing
a sensitivity analysis. Absorption and desorption rates were determined for three
configurations shown in table 4.4. It is important to note that all three configurations were
done on a full cycle. Thus, both absorber and desorber columns were in operation during
experimental runs. The absorber CO2 concentration and temperature profiles are shown in
figures 4.33 and 4.34 respectively. The highest reactivity in the absorber is seen with
configuration 3 (catalysts in both columns) where its temperature bulge is largest and
consequently shows the lowest exit CO2 concentration. Configuration 2, the case of only
HZSM-5 in the desorber and no absorber catalyst, comes next and finally configuration 1
(solvent only) exhibits the smallest bulge in temperature along the absorber and the least
drop in CO2 concentration. From figure 4.35, it can be observed that the addition of
HZSM-5 to the desorber system resulted in an increase in the absorption rate from about
0.015 to 0.018 mol/L.min which corresponds to a 22% increase and this can be attributed
to the lean loadings. It was observed that, the lean loading dropped when HZSM-5 was
incorporated into the desorber system. HZSM-5 contributes to better desorption
performance as explained earlier. This translates into enhancing CO2 absorption since the
process is cyclic. The leaner solvent meant more active free amines were available to react
89
thereby resulting in an increase in the reaction rate. The closeness in lean loadings (Table
4.5) for the 3 configurations suggests that the catalyst effect is somewhat minimal. This is
because the 4M BEA/AMP solvent has very good desorption performance due to its
inherent solvent characteristics as proven by Narku-Tetteh et al (2017). Hence, the better
the solvent performance in desorption, the lesser the benefit derived from the desorber
catalyst.
90
Table 4.4 Absorber and Desorber Configurations
System Configuration Absorber Desorber
1 Solvent Solvent
2 Solvent Solvent + solid acid
catalyst (HZSM-5)
3 Solvent + solid alkaline
catalyst (K/MgO)
Solvent + solid acid
catalyst (HZSM-5)
91
Upon the addition of the solid base-catalyst (K/MgO) into the absorber
(configuration 3), a huge improvement is seen in the rate of CO2 absorption. Faster kinetics
occurs resulting in a higher rich loading of the amine. When compared to the case of only
HZSM-5 in desorber (configuration 2), an increase of 61% is made when K/MgO is added.
A synergistic increase in absorption rate of about 99% is observed with the addition of
K/MgO and HZSM-5 (configuration 3) using configuration 1 as basis of comparison. The
explanation for the observed trend is based on established proof that CO2 reactions with
amines proceeds through the Zwitterion mechanism and that the rate determining step is
the Zwitterion formation step which is a nucleophilic addition reaction (Caplow, 1968).
As highlighted in previous sections, this step involves the transfer of electrons. Therefore
any enhancement in electron transfer will speed up Zwitterion formation. Since K/MgO is
a Lewis base catalyst (electron donor), it facilitates the easy transfer of electrons which
accelerates the rate limiting step hence improving upon the overall rate of reaction. Hence,
a faster rate of CO2 absorption is observed. With no solid base catalyst in the absorber, the
electron transfer process is highly hinged on the inherent solvent characteristics which
results in relatively slower reaction rates as compared to when an easy electron transfer
facilitator (solid base catalyst) is present in the process.
The desorption rate had a similar trend with configuration 1 having the slowest
desorption rate, followed by configuration 2, and the fastest being configuration 3. The
performance in both columns are linked, in that whatever transpires in the absorber is
largely translated to the desorber. Since the fastest rate of CO2 absorption was seen for
configuration 3 (catalysts in both column), it implies more CO2 was absorbed into the
amine solvent at the absorber section, hence any little application of heat coupled with the
92
presence of the solid acid catalyst (HZSM-5) in the desorber will lead to faster and greater
release of CO2. Desorption rates are summarized in Fig. 4.36. Table 4.5 displays the lean
and rich loadings for the three configurations studied with errors of ±0.01.
93
Figure 4.33 CO2 concentration profile along absorber for the different system
configurations
0
0.2
0.4
0.6
0.8
1
1.2
4 6 8 10 12 14 16
Hei
ght
fro
m b
ott
om
(m
)
CO2 concentration (%)
1 2 3
94
Figure 4.34 Temperature profile along absorber for the different system configurations
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
6 11 16 21 26 31 36 41 46 51
Hei
ght
fro
m b
ott
om
(m
)
Temperature (oC)
1 2 3
95
Figure 4.35 CO2 absorption rates for the different system configurations
Figure 4.36 CO2 desorption rates for the different system configurations
0
0.005
0.01
0.015
0.02
0.025
0.03
0.035
1 2 3
Ab
sorp
tio
n r
ate
(mo
l/L.
min
)
System Configuration
0
0.01
0.02
0.03
0.04
0.05
0.06
0.07
1 2 3
Des
orp
tio
n r
ate
(mo
l/L.
min
)
System Configuration
96
Table 4.5 Lean and Rich loadings for the different system configurations
Configuration 1 2 3
Lean loading (mol
CO2/mol amine)
0.33 0.3 0.32
Rich loading (mol
CO2/mol amine)
0.49 0.49 0.58
97
4.3.3 Catalytic Absorption Kinetic Studies
Experimental kinetic data were collected at atmospheric pressure and temperatures
of 293, 303 and 313 K, and contact times measured in terms of W/FCO2 in the range of 0 to
1561 g(cat). min/mol(CO2). As recommended by Froment and Bischoff (1990), the criteria
for plug flow conditions were ensured. According to this criterion, the values obtained
were 𝐿
𝑑𝑝= 242.5 > 50 and
𝐷
𝑑𝑝= 12.5 > 10 which provide for plug-flow conditions in the
reactor. To obtain intrinsic kinetic data from the absorber with the inclusion of the solid
base catalyst, the possibility of heat and mass transfer limitations had to be assessed. CO2
reactions with amines occur in the liquid phase and are very fast since the amines are
highly reactive. It is well known that for both exothermic and endothermic reactions, the
temperature gradient existing on the catalyst or the temperature gradient between the bulk
liquid and the catalyst surface may have an effect on the observed rate of reaction.
Therefore, it is paramount to determine if there is an onset of heat and mass transfer
limitations and to what extent the rate of reaction is affected, if any. Theoretical
calculations as reported by Ibrahim and Idem (2007) were carried out, and the possibility
of these effects were determined.
4.3.3.1 Evaluation of Heat Transfer Limitation
The internal pore heat transfer resistance was estimated using the Prater analysis
given as:
∆𝑇𝑝𝑎𝑟𝑡𝑖𝑐𝑙𝑒,𝑚𝑎𝑥 =𝐷𝑒𝑓𝑓(𝐶𝐴𝑠−𝐶𝐴𝑐)∆𝐻𝑟𝑥𝑛
𝜆𝑒𝑓𝑓 (4.6)
98
A ∆𝑇 value less than 1oC is considered sufficient to show a negligible effect in heat transfer
on the reaction rate; where Δ𝑇𝑝𝑎𝑟𝑡𝑖𝑐𝑙𝑒 𝑚𝑎𝑥 is the upper limit to temperature variation between
pellet centre and pellet surface; 𝐶𝐴𝑆 𝑎𝑛𝑑 𝐶𝐴𝐶 are the concentrations at the pellet surface
and centre which are assumed to be the bulk concentration and zero respectively
(Levenspiel, 1999). Δ𝐻𝑟𝑥𝑛 is the heat of reaction. 𝐷𝑒𝑓𝑓 is the effective mass diffusivity
defined as 𝐷𝑒𝑓𝑓 =𝜀𝐷𝐴𝐵/𝜏 (Fogler, 1999) and 𝐷𝐴𝐵 is the bulk diffusivity of component A
(CO2) in B (lean solvent), which was estimated using Brokaw equation (Perry and Green,
1997). The value of 𝐷𝐴𝐵 at maximum temperature was found to be 7.3 x 10-10 m2.s-1 with
𝐷𝑒𝑓𝑓 also estimated to be 4.61 x 10-11 m2.s-1. 𝜏 represents the tortuosity factor. The void
fraction, 𝜀 was calculated using the formula 𝜀 = 0.38 + 0.073[1 +(
𝑑
𝑑𝑝−2)
2
(𝑑
𝑑𝑝)
2 ] (Geankoplis,
2003) where 𝑑 𝑎𝑛𝑑 𝑑𝑝 are the reactor diameter and catalyst diameter, respectively. 𝜆𝑒𝑓𝑓=
effective thermal conductivity and is calculated using the equation 𝜆𝑒𝑓𝑓𝜆=5.5+ 0.05𝑁𝑅𝑒
for Packed Bed Tubular Reactors (Walas, 1990). 𝜆 is the molecular thermal conductivity
which was calculated using the correlation developed by Wassiljewa (Perry and Green,
1997) and obtained to be 5.41 x 10-1 Wm-1K-1. The effective thermal conductivity, 𝜆𝑒𝑓𝑓
was found to be 2.99 x 10-3 kWm-1K-1. A value of 5.29 x 10-3 K was obtained which is
much less than 1oC. Detailed calculations are shown in Appendix B5.
The external film heat transfer limitation was estimated using the following
relation:
∆𝑇𝑓𝑖𝑙𝑚,𝑚𝑎𝑥 =𝐿𝑐(−𝑟𝐴,𝑜𝑏𝑠)∆𝐻𝑟𝑥𝑛
ℎ (4.7)
99
This correlation was adopted from Ibrahim and Idem (2007); where Δ𝑇𝑓𝑖𝑙𝑚, 𝑚𝑎𝑥 is the upper
limit temperature difference between the pellet surface and the gas bulk, 𝐿𝑐 is the
characteristic length, −𝑟𝐴, is the observed rate of reaction, and h is the heat-transfer
coefficient obtained from the correlation
𝐽𝐻 = 𝐽𝐷 = (ℎ
𝑐𝑝𝑢𝜌) 𝑁𝑃𝑟
23⁄
. Here, 𝐽𝐻 is the heat-transfer 𝐽 factor, NPr is the Prandtl number
given as 𝑁𝑝𝑟 = 𝐶𝑝𝜇/𝜆, and λ is the molecular thermal conductivity. The 𝐽𝐷 factor was also
calculated by the following correlations: 𝐽𝐷 = (0.4548
ε) 𝑁𝑅𝐸
−0.4069 = (𝑘𝑐/𝑣)2/3 (Geankoplis,
2003). Reynolds number, 𝑁𝑅𝐸 =𝜌𝑣𝑑𝑝
µ(1−𝜀) . 𝑘𝑐 is the mass-transfer coefficient obtained as
2.62 x 10-7 m/s. The heat transfer coefficient, ℎ, was also estimated to be 1.4 x 10-1
𝑘𝐽𝑚−2𝑠−1𝐾−1. The Δ𝑇𝑓𝑖𝑙𝑚, 𝑚𝑎𝑥 was finally estimated as 1.92 𝑥 10−2 K. The detailed
calculation is shown in the appendix section (B6).
The much more rigorous Mears criterion was also used to estimate if there was any
onset of heat transfer limitation. It is given as:
−𝑟𝐴,𝑜𝑏𝑠𝜌𝑐𝑅𝑐𝐸∆𝐻𝑟𝑥𝑛
ℎ𝑇2𝑅< 0.15 (4.8)
Upon substituting values for each term in Eqn (4.8), a value of 1.21 x 10-3 which is much
less than 0.15 was obtained. This signifies the absence of any limitations with respect to
heat transport in the system. These estimations are summarised in Table 4.6.
100
4.3.3.2 Evaluation of Mass Transfer Limitation
Similarly, the possibility of a mass transfer resistance in the system was evaluated.
The internal pore mass transfer resistance was estimated using the Weisz-Prater analysis
procedure reported by Ibrahim and Idem (2007) shown in equation 4.9:
𝐶𝑤𝑝,𝑖𝑝𝑑 =𝑟𝐴,𝑜𝑏𝑠𝜌𝑐𝑅𝑐
2
𝐷𝑒𝑓𝑓𝐶𝐴𝑠 (4.9)
Here, 𝐶𝑤𝑝, 𝑖𝑝𝑑 is defined as the Weisz-Prater criterion for internal pore diffusion, 𝜌𝑐 is the
pellet density, 𝑅𝑐 is the catalyst radius. Cwp, ipd was estimated to be 0.517 which is much
less than 1. Thus, it is an indication of a negligible concentration difference between the
reactant on the catalyst surface and within its pores. This means the absence of internal
pore diffusion limitation (Fogler, 1999).
To estimate the film mass transfer resistance, the ratio of the observed rate to the
rate if film mass transfer resistance controls was determined as:
𝑜𝑏𝑠𝑒𝑟𝑣𝑒𝑑 𝑟𝑎𝑡𝑒
𝑟𝑎𝑡𝑒 𝑖𝑓 𝑓𝑖𝑙𝑚 𝑟𝑒𝑠𝑖𝑠𝑡𝑎𝑛𝑐𝑒 𝑐𝑜𝑛𝑡𝑟𝑜𝑙𝑠=
(−𝑟𝐴,𝑜𝑏𝑠)
𝐶𝐴𝑏𝑘𝑐
𝑑𝑝
6 (4.10)
The above ratio gave a value of 2.99 x 10-2 which indicates that the observed rate is less
than the film transfer rate; therefore, there should not be any influence from the film
resistance on the reaction rate (Levenspiel, 1999).
Again, the Mears criterion (Fogler, 1999) was utilized to ascertain if the mass
transfer resistance on the rate of reaction was negligible. It is given as:
−𝑟𝐴,𝑜𝑏𝑠𝜌𝑏𝑅𝑐𝑛
𝐾𝑐𝐶𝐴< 0.15 (4.11)
101
The value on the left-hand side of this equation is 1.179×10-1 which is less than the RHS.
Therefore, it can be concluded that there was no mass transport limitation in the film. The
results of these analyses are summarised in Table 4.6 and shows the absence of any heat
and mass transfer limitations. Appendices B8 to B10 show the details of the calculation.
102
Table 4.6 Summary of Heat and Mass transfer limitations.
Internal pore
heat transfer
resistance,
∆𝑇𝑝𝑎𝑟𝑡𝑖𝑐𝑙𝑒,𝑚𝑎𝑥
(K)
External film
heat transfer
resistance,
∆𝑇𝑓𝑖𝑙𝑚,𝑚𝑎𝑥
(K)
Mears
Criterion for
heat transfer
resistance
< 0.15
Internal pore
mass transfer
resistance
Film mass
transfer
resistance
Mears
Criterion for
mass transfer
resistance
< 0.15
5.29E-03 1.92E-02 1.21E-03 5.17E-01 2.99E-02 1.18E-01
103
4.3.3.2 Determination of Reaction Rate
The reaction rate of the aqueous CO2+AMP+BEA system was determined
experimentally with an integral type (plug-flow) reactor, as stated earlier, using the
differential method of kinetic data analysis. Levenspiel (1999) outlines the details of this
method of analysis. As earlier shown in equation 4.2, CO2 Conversion was employed as a
measure of evaluation of the catalyst performance. The term V in equation 4.3 was
substituted with W in the determination of the rate of reaction and is shown in equation
4.6 as:
−𝑟𝐴 =𝑑𝑋𝐴
𝑑(𝑊/𝐹𝐴0)=
𝑑𝑋𝐶𝑂2
𝑑(𝑊/𝐹𝐶𝑂20) (4.6)
Thus, the slopes of conversion, X against 𝑊/𝐹𝐶𝑂20 were used to determine the rates of
reaction and the plot is shown in figure 4.37.
104
Figure 4.37 XCO2 versus 𝑊/𝐹𝐶𝑂20 at different temperatures and CO2/Amine molar
ratios.
0.30
0.35
0.40
0.45
0.50
0.55
0.60
0.65
0.70
0 500 1000 1500 2000
X
W/Fao (g cat. min/mol)
293K & CO2/AM=0.39
303K & CO2/AM=0.39
313K & CO2/AM=0.39
303K & CO2/AM=0.47
303K & CO2/AM=0.34
105
4.3.3.3 Parameter Estimation of Power law model
CO2 reactions with amines are known to be reversible. The forward reaction (CO2
absorption) is exothermic and is favoured at low reaction temperatures while the reverse
reaction (CO2 desorption) is endothermic and is thermodynamically favoured at high
temperatures. The kinetic data obtained from experiments were fitted to a power law
model. Considering a reversible reaction, the power law model can be represented as:
−r𝐶𝑂2 = 𝑘𝑓𝑜e−𝐸𝑎1
𝑅𝑇⁄ 𝐹𝐴𝑛𝐹𝐵
𝑚 − 𝑘𝑟𝑜e−𝐸𝑎2
𝑅𝑇⁄ 𝐹𝐶𝑜𝐹𝐷
𝑝𝐹𝐸
𝑞𝐹𝐹
𝑠 (4.7)
Where 𝑘𝑓𝑜 and 𝑘𝑟𝑜 refer to the frequency factor of the forward and reverse reactions
respectively, 𝐸𝑎1 and 𝐸𝑎2 refer to activation energies of the forward reaction and reverse
reactions respectively, R is the universal gas constant, FA, FB, FC, FD, FE and FF are the
molar flowrates of CO2, amine, protonated amine, carbamate, bicarbonate and carbonate
ions respectively; and n, m, o, p, q and s are also the orders with respect to the above
mentioned species in the same order. The speciation plots of the single solvents were
adopted to determine the species concentrations and flowrates. AMP speciation was
obtained from ProMax 4.0 ® software (Bryan Research &Engineering, Inc., USA) with
specified process conditions. The speciation of BEA was obtained from literature from the
work of Jakobsen et al. (2005). The following assumptions were used in arriving at the
final reversible power law model:
• All carbamates in the system are that of BEA since the carbamate hydrolysis for
AMP is very fast, and that all of AMP’s carbamates are hydrolysed to bicarbonates.
• The rate of CO2 pick-up by the single amines is fairly equal on the basis of their
acid dissociation constant (pKa). According to Narku-Tetteh et al. (2017), the
106
reported pKa values of AMP and BEA are 9.8 and 10 respectively for which in
solvent chemistry can be safely approximated to be the same.
• The amounts of H+ ions, OH- ions and unattached CO2 in the blend is negligible
and these were not included in the model.
Considering the process conditions at which CO2 absorption was carried out in this
study, where the maximum inlet temperature was 40oC, the possibility of an appreciable
reversibility of the reaction at these conditions is very low. Since CO2 desorption
(backward reaction) occurs at considerably higher temperatures than what was used in the
experiments, the reversible reaction was thus truncated to that of an irreversible reaction.
In that case, the power law model reduced to:
r𝐶𝑂2 = 𝑘𝑓𝑜e−𝐸𝑎1
𝑅𝑇⁄ 𝐹𝐴𝑛𝐹𝐵
𝑚 (4.8)
The values of the kinetic parameters were estimated based on the minimization algorithm,
which comprises the merging of Levenberg–Marquardt and Gauss–Newton methods. The
Non-Linear Regression (NLREG) software was utilized. A summary of the parameter
estimates for both cases of irreversible and reversible reaction is presented in Table 4.8.
This work is the first attempt at estimating the kinetic parameters for a solid
(heterogeneous) base catalyst-aided reaction between CO2 and an aqueous amine. The
model was validated by determining the percentage average absolute deviation (AAD %)
existing between the observed experimental rate and the predicted rate from the power law
model. Both models gave acceptable AAD % <15. Also, to portray the extent to which the
predicted rate fits the experimental rate, a parity plot was made and is shown in Figure
4.38. Clearly, one can observe the closeness in correlation existing between the
107
experimental and predicted rates. The reaction order of 2 for CO2 for the irreversible power
law model is an indication of a strong coverage of K/MgO by CO2. The negative orders
obtained for some products of the reversible model may be due to inadequate variation in
process conditions directly linked to their concentration or flowrates. Details of the
calculation and software results are shown in Appendices C and D.
108
Table 4.7 Experimental Kinetic Data
Run T (K) Rate
(mol/g.min)
×104
FA
(mol/min)
×102
FB
(mol/min)
×102
FC
(mol/min)×
102
FD
(mol/min)
×102
FE
(mol/min)
×102
FF
(mol/min)
×102
CO2/Amine
molar ratio
1 293 0.841 3.662 1.200 8.361 2.237 2.000 2.689 0.39
2 293 0.423 3.351 0.240 8.884 2.369 2.230 2.824 0.39
3 293 0.279 3.173 0.240 8.884 2.369 2.230 2.824 0.39
4 303 1.227 3.921 1.440 7.973 2.225 2.004 2.476 0.39
5 303 0.616 3.539 1.200 8.200 2.225 2.119 2.533 0.39
6 303 0.416 3.353 0.960 8.289 2.292 2.157 2.551 0.39
7 303 2.108 3.962 1.200 8.200 2.225 2.119 2.533 0.47
8 303 1.045 3.664 0.720 8.231 2.292 2.122 2.539 0.47
9 303 0.712 5.960 1.400 6.644 1.855 1.670 2.064 0.47
10 303 0.617 5.045 1.000 6.833 1.855 1.765 2.111 0.34
11 303 0.311 4.842 0.600 6.859 1.910 1.768 2.116 0.34
12 303 0.207 3.600 1.680 9.302 2.596 2.338 2.889 0.34
13 313 2.514 3.294 1.400 9.567 2.596 2.472 2.955 0.39
14 313 1.239 3.233 1.120 9.671 2.674 2.516 2.976 0.39
15 313 0.833 6.405 3.360 6.911 1.927 1.636 2.148 0.39
109
Table 4.8 Summary of Parameter Estimates for reversible and irreversible power law
models.
Parameter Reversible Irreversible
kfo (min/mol.g)a or (min2/mol2g)b 2.47E+07 7.98E-07
kro (mol/g.min) 6.61E+12 -
Ea1 (J/mol) 5.67E+04 3.40E+04
Ea2 (J/mol) 9.03E+04 -
N 0.46 2.18
M 0.19 0.42
O -0.56 -
P 1 -
Q -1 -
S 0.87 -
(NB: a – reversible case; b – irreversible case)
110
Figure 4.38 Parity plot of predicted rate versus experimentally observed rate
0.0E+00
1.0E-04
2.0E-04
3.0E-04
4.0E-04
0.0E+00 5.0E-05 1.0E-04 1.5E-04 2.0E-04 2.5E-04 3.0E-04 3.5E-04 4.0E-04
pre
dic
ted
rat
e (m
ol/
g.m
in)
experimental rate (mol/g.min)
reversible, AAD=13.29%
irreversibe, AAD=14.10%
111
4.3.3.4 Effect of Process Parameters on CO2 conversion
4.3.3.4.1 Effect of Catalyst weight (W/FA0)
It is an established fact that conversion increases with residence time of reactant
species. For a packed bed reactor, this can best be analysed by using the weight time or
W/FA0 ratio. In this work, the catalyst weight was expressed in terms of weight
time(𝑊/𝐹𝐶𝑂20) and was varied by increasing the weight of the catalyst while keeping the
CO2 flowrate constant. Figure 4.39 displays the effect of catalyst weight on the CO2
conversion and hence rate. It can be observed that as the catalyst weight was increased,
CO2 conversion also increased. An increase in catalyst weight means greater availability
of active surface area, therefore allowing for a greater number of reacting species to have
access to these additional sites, hence resulting in an increase in conversion. A percentage
increase of 36% relative to 0g catalyst was observed when catalyst weight of 50g was
introduced to the system at an absorber inlet lean loading of 0.42 (corresponding to
desorber bed temperature of 75oC).
This is as a result of the chemical contribution the catalyst introduces to the system
by lowering the activation energy and increasing the frequency of collision between
reacting molecules allowing for the ease in formation of products. The physical
contribution is seen on the basis of the presence of greater porous surfaces. An increase
of about 8.5% and 5.9% was seen with catalyst increments from 50 to 100g and 100 to
150g respectively. However, after 150g (corresponding to a weight time of 1561
min.gcat/mol), the conversion in the absorber is seen to be fairly constant. This might be
the result of the reaction having attained its thermodynamic limit and as such no increase
in conversion is seen with further addition of catalyst. The criterion for determining
112
thermodynamic limit in amine-based CO2 absorption is the equilibrium loading.
Therefore, once this loading value has been reached, no quantity of catalyst can alter the
transfer of CO2 into the amine. For all conditions studied, increasing the W/FA0 led to a
general increase in CO2 conversion. The CO2 removal efficiency and cyclic capacity is
displayed in Figure 4.40.
113
Figure 4.39 Effect of catalyst weight (W/FA0) on CO2 conversion (Absorber inlet
temperature: 300C, Absorber pressure: 1atm, Amine concentration: 2M/2M BEA/AMP,
Absorber inlet lean loading: 0.42, gas flowrate: 15 slpm, amine flowrate: 60 ml/min,
Desorber temperature: 75oC)
Figure 4.40 Cyclic capacity and Removal efficiency at different catalyst weights (Absorber
inlet temperature: 300C, Absorber pressure: 1atm, Amine concentration: 2M/2M
BEA/AMP, Amine flowrate: 60 ml/min, gas flowrate: 15 slpm, Desorber temperature:
85oC)
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
0.4
0 528 1057 1561 1781
CO
2 c
on
vers
ion
, X
W/FAO (min.gcat/mol)
48
50
52
54
56
58
60
62
64
66
0
0.02
0.04
0.06
0.08
0.1
0.12
0.14
0.16
0.18
0g 50g 100g 150g 170g
Ab
sorb
er e
ffic
ien
cy (%
)
Cyc
lic c
apac
ity
(kg/
hr)
Cyclic capacity Removal efficiency
114
4.3.3.4.2 Effect of lean loading
A key focus of catalytic studies is to work with lower temperatures thus reducing
the energy penalty. Previous works by Akachuku (2016), Osei (2016), Decardi-Nelson
(2016) and Srisang (2017) reveal a successful reduction in the conventional desorption
temperature of 120oC to an average desorption bed temperature of 85oC by using acid
catalysts (HZSM-5 and γ-Al2O3). The experiment was conducted on a full cycle bench-
scale pilot plant which. This indicated a direct link between absorption and desorption
processes in their study. Therefore, each average desorption bed temperature yields a
corresponding lean CO2 loading. Hence, in this work, by keeping the average desorber bed
temperature constant at values of 75oC, 85oC and 95oC, yields of corresponding
temperature profiles in the absorber were observed based on their inlet lean loadings.
Figure 4.41 shows the effect of solvent lean loading on the absorber CO2
conversion at the specified conditions. It can be inferred from the plot that there exists an
inverse relationship between solvent lean loading and CO2 conversion. This is not
unexpected as more active free amines are available to react as one decreases lean loading.
The lowest lean loading of 0.2 (mol CO2/mol amine) was seen at 95oC, and that at 85oC
and 75oC were 0.33 and 0.42 respectively. Increasing lean loading from 0.2 to 0.33 resulted
in a drop in absorber CO2 conversion of about only 8.4% while a 41.8% decline was seen
when the lean loading was increased from 0.33 to 0.42. The percentage drop is much
greater as lean loading increases. This suggests that there is only a marginal change in
performance between a desorber bed temperature of 85 and 95oC and a rather considerable
change when temperature is reduced from 85 to 75oC. The reason being that the solvent
viscosity is influenced by CO2 loading. Viscosity increases with CO2 loading. Hence, at a
115
lean loading of 0.42, the viscosity of the solvent was high to the extent of limiting the
transfer of CO2 into the solvent. As loading decreased however, the viscosity effect is
greatly reduced, resulting in very similar performance at loadings of 0.33 and 0.2.
Therefore, operating at a desorber temperature of 85oC (loading of 0.33) will be cost
effective since a lower energy penalty in terms of heat duty will be evident than at a higher
temperature of 95oC (loading of 0.2). The trend was consistent for all absorber catalyst
weights. CO2 conversion at different lean loadings is summarised in Table 4.9. The
absorber temperature profiles at 50g catalyst weight for the three lean loadings are
displayed in Figure 4.42. Since CO2-amine reactions are exothermic in nature, the largest
release of heat in the absorber yielded the highest absorber temperature profile. This was
at a lean loading of 0.2.
116
Figure 4.41 Effect of lean loading on CO2 conversion. (Absorber inlet temperature: 300C,
Absorber pressure: 1 atm, Gas flowrate: 15 slpm, Amine flowrate: 60 ml/min, Amine
concentration: 2M/2M BEA/AMP, Catalyst weight of 150g).
Table 4.9 CO2 fractional conversion at solvent lean loadings of 0.2, 0.33 and 0.42 for
various absorber catalyst weights (Absorber inlet temperature: 300C, Absorber pressure:
1 atm, Gas flowrate: 15 slpm, Amine flowrate: 60 ml/min, Amine concentration: 2M/2M
BEA/AMP)
CO2 fractional conversion
Cat. weight (g) 0.2 0.33 0.42
0 0.229 0.520 0.586
50 0.311 0.566 0.627
100 0.338 0.589 0.667
150 0.358 0.614 0.671
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0 0.1 0.2 0.3 0.4 0.5
CO
2 c
on
vers
ion
, X
lean loading (mol CO2/mol amine)
117
Figure 4.42 Absorber temperature profiles at lean loadings of 0.20, 0.33 and 0.42
(Absorber inlet temperature: 300C, Gas flowrate: 15 slpm, Amine flowrate: 60 ml/min.,
Amine concentration: 2M/2M BEA/AMP, Catalyst weight: 50g).
Figure 4.43 Cyclic capacity and Removal efficiency at different lean loadings (Absorber
inlet temperature: 300C, Absorber pressure: 1atm, Amine concentration: 2M/2M
BEA/AMP, Amine flowrate: 60 ml/min, gas flowrate: 15 slpm, Catalyst weight: 150g)
0
5
10
15
20
25
30
35
40
45
0 10 20 30 40 50 60 70
hei
ght
fro
m b
ott
om
(in
)
temperature (0C)
0.42
0.33
0.2
0
10
20
30
40
50
60
70
80
0
0.02
0.04
0.06
0.08
0.1
0.12
0.14
0.16
0.18
0.2
0.42 mol/mol 0.33 mol/mol 0.2 mol/mol
Rem
ova
l eff
icie
ncy
(%)
Cyc
lic c
apac
ity
(kg/
hr)
Cyclic capacity Removal efficiency
118
4.3.3.4.3 Effect of Solvent flowrate
The effect of increasing solvent flowrate is evident in higher CO2 conversions at
fixed W/FA0. This is expected with the logic that more free amines are available per unit
time as the solvent flowrate is increased. This means a greater contact between the catalyst
and the solvent. Thus, more solvent results in greater wetness of catalyst yielding faster
and much larger transfer of CO2 into the solvent. This results in higher CO2 conversions.
Also, an increase in solvent flowrate means a greater driving force resulting in faster
absorption of CO2 into the solvent. Figure 4.44 shows the variation in amine flowrate from
50 to 70 ml/min while keeping the catalyst weight constant (fixed W/ FA0). It is observed
that conversion increases as the amine flow rate is increased. The catalyst effect is also
coupled with the variation in liquid flow rate. The catalyst provides lower activation
energy as its weight is increased and results in richer CO2 loadings. The effect of solvent
flow rate on CO2 conversion is seen to be greater from 50 to 60 ml/min with an average
percentage increase in conversion of 54.3%. A lower effect is observed from 60 to 70
ml/min and only a 4.2% average increase in conversion is seen for each catalyst weight.
At 50 ml/min the solvent was not enough to wet the entire catalyst surface area hence
limiting its use. The variation in CO2 conversion from 60 to 70ml/min was very marginal,
hence it would not be beneficial to operate at 70ml/min considering the fact that an
increase in solvent flow rate translates into higher circulation and regeneration costs,
which will decrease the overall system efficiency (Naami et al., 2012). A plot of removal
efficiency and cyclic capacity is also shown in Figure 4.45.
119
Figure 4.44 Effect of solvent flowrate on CO2 conversion (Absorber inlet temperature:
300C, Absorber pressure: 1atm, Amine concentration: 2M/2M BEA/AMP, Absorber inlet
lean loading: 0.33, gas flowrate: 15 slpm, amine flowrate: 60 ml/min, Desorber
temperature: 85oC)
Figure 4.45 Cyclic capacity and Removal efficiency at different solvent flowrates
(Absorber inlet temperature: 300C, Absorber pressure: 1atm, Amine concentration:
2M/2M BEA/AMP, Absorber inlet lean loading: 0.33, gas flowrate: 15 slpm, Desorber
temperature: 85oC, Catalyst weight: 150g)
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
40 50 60 70 80
frac
tio
nal
CO
2co
nve
rsio
n
solvent flowrate (ml/min)
0g
50g
100g
150g
0
10
20
30
40
50
60
70
0
0.02
0.04
0.06
0.08
0.1
0.12
0.14
0.16
0.18
50ml/min 60ml/min 70ml/min
Rem
ova
l eff
icie
ncy
(%)
Cyc
lic c
apac
ity
(kg/
hr)
Cyclic capacity Removal efficiency
120
4.3.3.4.4 Effect of Solvent concentration ratio
The total solvent concentration was kept at 4M while varying the BEA and AMP
concentrations. BEA concentration was varied from 1.5M to 3M with AMP consequently
being varied from 2.5M to 1M. Figure 4.46 shows the variation in solvent concentration
ratio on conversion. From figure 4.46, it is evident that as BEA concentration increased
(AMP concentration increase), CO2 conversion decreased. The lower conversion observed
as BEA concentration was increased is due to the drop in moles of the sterically hindered,
AMP. Since, AMP is a sterically-hindered amine, it is noted for its high CO2 absorption
capacity. Hence, reducing AMP’s concentration resulted in lowering CO2 absorption into
the solvent since the solvent’s capacity was reduced.
Another explanation is that the variation in viscosity of these solvents could have
greatly affected the absorption of CO2, hence conversion. The viscosities and densities for
both unloaded and loaded solvent for all concentration ratios were measured in this work.
Figure 4.47 shows the dynamic viscosities of the unloaded solvents and their variation
with temperature. Figures 4.48 to 4.55 show the densities and dynamic viscosities of the
loaded solvent across all concentration ratios studied. Generally, it is evident that the
viscosity is highest for the 3M BEA/1M AMP solvent and the trend in decreasing order of
viscosity is as follows for the four solvents: 3M BEA/1M AMP>2.5M BEA/1.5M
AMP>2M BEA/2M AMP>1.5M BEA/2.5M AMP. With this trend, it can be established
that increasing the BEA concentration resulted in an increase in the solvent viscosity, thus
affecting mass-transfer of the system. From Figure 4.46 it can be observed that the catalytic
effect is much more pronounced at higher BEA concentrations while at lower BEA
concentrations, the solvent effect dominates.
121
A possible explanation to this is the onset of mass transfer limitations in the liquid
film at higher BEA concentrations which masked the solvent contribution, hence making
the catalytic effect more evident. At lower BEA concentrations, the viscosity was
relatively lower; thus, the solvent contribution superseded that of the catalyst. Therefore,
an increase in catalyst weight at lower BEA concentrations showed little variations in CO2
conversion. Across the range of catalyst weights, an average percentage decrease of 8.4%,
24.2% and 9.3% is seen when the concentration of BEA increases from 1.5M to 2M, from
2M to 2.5M and finally from 2.5M to 3M respectively.
122
Figure 4.46 Effect of solvent concentration ratio on CO2 conversion (Absorber inlet
temperature: 300C, Absorber pressure: 1atm, Gas flowrate: 15 slpm, Amine flowrate: 60
ml/min, Desorber temperature: 85oC, *Total amine concentration BEA/AMP: 4M)
Figure 4.47 Dynamic viscosities of unloaded solvent for different concentration ratios
(BEA:AMP)
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.5 1 1.5 2 2.5 3 3.5 4
frac
tio
nal
CO
2co
nve
rsio
n
BEA solvent concentration (M)
0g
50g
100g
150g
0
1
2
3
4
5
6
7
0 20 40 60 80 100
dym
vis
c (m
Pa.
s)
Temperature (oC)
1.5M:2.5M
2M:2M
2.5M:1.5M
3M:1M
123
Figure 4.48 Densities of loaded 1.5M BEA/ 2.5M AMP solvent.
Figure 4.49 Dynamic viscosities of loaded 1.5M BEA/ 2.5M AMP solvent
0.96
0.98
1
1.02
1.04
1.06
1.08
1.1
0 0.1 0.2 0.3 0.4 0.5 0.6
Den
sity
, g/c
m3
loading, mol CO2/mol amine
20oC
30oC
40oC
50oC
60oC
0
2
4
6
8
10
12
14
16
18
0 0.1 0.2 0.3 0.4 0.5 0.6
dyn
amic
, mP
a.s
loading, mol CO2/mol amine
20oC
30oC
40oC
50oC
60oC
124
Figure 4.50 Densities of loaded 2M BEA/ 2M AMP solvent.
Figure 4.51 Dynamic viscosities of loaded 2M BEA/ 2M AMP solvent
0.96
0.98
1
1.02
1.04
1.06
1.08
1.1
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7
Den
sity
, g/c
m3
loading, mol CO2/mol amine
20oC
30oC
40oC
50oC
60oC
0
2
4
6
8
10
12
14
16
18
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7
dyn
vis
c, m
Pa.
s
loading, mol CO2/mol amine
20oC
30oC
40oC
50oC
60oC
125
Figure 4.52 Densities of loaded 2.5M BEA/ 1.5M AMP solvent.
Figure 4.53 Dynamic viscosities of loaded 2.5M BEA/ 1.5M AMP solvent
0.96
0.98
1
1.02
1.04
1.06
1.08
0 0.1 0.2 0.3 0.4 0.5 0.6
Den
sity
, g/c
m3
loading, mol CO2/mol amine
20oC
30oC
40oC
50oC
60oC
0
2
4
6
8
10
12
14
16
18
0 0.1 0.2 0.3 0.4 0.5 0.6
dyn
vis
c, m
Pa.
s
loading, mol CO2/mol amine
20oC
30oC
40oC
50oC
60oC
126
Figure 4.54 Densities of loaded 3M BEA/ 1M AMP solvent.
Figure 4.55 Dynamic viscosities of loaded 3M BEA/ 1M AMP solvent
0.96
0.98
1
1.02
1.04
1.06
1.08
0 0.1 0.2 0.3 0.4 0.5 0.6
Den
sity
, g/c
m3
loading, mol CO2/mol amine
20oC
30oC
40oC
50oC
60oC
0
2
4
6
8
10
12
14
16
18
0 0.1 0.2 0.3 0.4 0.5 0.6
dyn
vis
c, m
Pa.
s
loading, mol CO2/mol amine
20oC
30oC
40oC
50oC
60oC
127
Figure 4.56 Cyclic capacity and Removal efficiency at different concentration ratios
(Absorber inlet temperature: 300C, Absorber pressure: 1atm, Absorber inlet lean loading:
0.33, gas flowrate: 15 slpm, Amine flowrate: 60 ml/min, Desorber temperature: 85oC,
Catalyst weight: 150g)
0
10
20
30
40
50
60
70
80
0
0.02
0.04
0.06
0.08
0.1
0.12
0.14
0.16
0.18
1.5M BEA2.5M AMP
2M BEA 2MAMP
2.5M BEA1.5M AMP
3M BEA 1MAMP
Rem
ova
l eff
icie
ncy
(%)
Cyc
lic c
apac
ity
(kg/
hr)
Cyclic capacity Removal efficiency
128
4.3.3.4.5 Effect of Gas flowrate
Figure 4.57 displays the direct effect of increasing gas flowrate on CO2 conversion.
This figure shows a strong positive relationship existing between the gas flowrate and
conversion. Increasing the gas flowrate introduced a slight increase in total pressure. This
means a relatively higher value in the absolute partial pressure of CO2 and consequently
more moles present per unit time. Therefore, a greater driving force was realised as
flowrate increased, allowing for more CO2 absorption. Also, this proves the existence of a
greater resistance in the gas phase at lower gas flowrates. As one increases the gas
flowrate, the gas phase resistance is considerably reduced. A percentage increase of 64%
is seen when gas flowrate is increased from 10 to 15 slpm, and a 24% increase is observed
by increasing from 15 to 20 slpm. Due to the system hydrodynamics, further increase in
gas flowrate resulted in considerable pressure drop and subsequent flooding in the column.
The temperature profiles of the three systems is shown in Fig. 4.58. The magnitude of the
bulge is representative of the heat of the reaction released when the gas contacts the amine,
and this is relatively largest at 20 slpm and signifies the presence of more CO2 molecules
at this flowrate. The bulge shows a shift to the top as gas flowrate is increased. This is
expected as the gas pushes the reaction zone to the top when an increase in gas flowrate is
made. The removal efficiency and cyclic capacity plots are shown in Figure 4.59.
129
Figure 4.57 Effect of Gas flowrate on CO2 conversion (Absorber inlet temperature: 300C,
Absorber pressure: 1atm, Amine concentration: 2M/2M BEA/AMP, amine flowrate: 60
ml/min, Desorber temperature: 85oC, Catalyst weight: 50g)
Figure 4.58 Temperature Profile for variation in gas flowrate (Absorber inlet
temperature: 300C, Absorber pressure: 1atm, Amine concentration: 2M/2M BEA/AMP,
amine flowrate: 60 ml/min, Desorber temperature: 85oC, Catalyst weight: 50g)
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
10 15 20Fr
acti
on
al c
on
vers
ion
Gas flowrate (slpm)
0
0.2
0.4
0.6
0.8
1
1.2
6 16 26 36 46 56
Hei
ght
fro
m b
ott
om
(m
)
Temperature (oC)
20 slpm 15 slpm 10 slpm
130
Figure 4.59 Cyclic capacity and Removal efficiency at different gas flowrates (Absorber
inlet temperature: 300C, Absorber pressure: 1atm, Amine concentration: 2M/2M
BEA/AMP, Absorber inlet lean loading: 0.33, Amine flowrate: 60 ml/min, Desorber
temperature: 85oC, Catalyst weight: 50g)
0
10
20
30
40
50
60
70
0.132
0.134
0.136
0.138
0.14
0.142
0.144
0.146
0.148
0.15
0.152
0.154
10slpm 15slpm 20 slpm
Rem
ova
l eff
icie
ncy
(%)
Cyc
lic c
apac
ity
(kg/
hr)
Cyclic capacity Removal efficiency
131
4.3.3.4.6 Effect of Absorber inlet temperature
The next variable considered is the absorber inlet temperature and its effect on CO2
conversion. Three temperatures (20oC, 30oC, and 40oC) were evaluated and their effect is
discussed in this section. From Figure 4.60, generally, an inverse relationship exists
between temperature and conversion. Thus, an increase in the inlet temperature results in
a decrease in CO2 conversion. As mentioned earlier, CO2 reactions with amines are
exothermic; and as with all exothermic reactions, the equilibrium conversion and
equilibrium constant decreases with a rise in temperature, while the rate of forward
reaction increases with temperature (Levenspiel, 1999). Therefore, it can be said that
temperature has a great influence on the system’s thermodynamics. At 20oC - for each
catalyst weight - conversion is seen to be highest as compared to that at 30 and 40oC. Two
factors contribute to CO2 conversion with variation in temperature: thermodynamics and
solvent viscosity. Viscosity of liquids decreases as temperature rises. Owing to this,
conversion is expected to drop as temperature is reduced. However, we realise a contrary
trend as conversion is seen to rather increase when temperature decreases. Here, the
thermodynamic factor comes in, where the exothermic nature of the reaction favours
higher conversion at low temperatures. Thus, the viscosity factor is somewhat masked by
the systems thermodynamics. Again, for CO2-amine reactions, desorption of CO2 occurs
at high temperatures. Therefore, at such relatively low temperatures, extremely little or no
desorption takes place.
At 40oC, the average kinetic energy of reactant molecules is higher and as such
more reactant molecules have enough energy to overcome the energy barrier to form
products. Also, the lower liquid viscosity at higher temperatures should favour the
132
conversion of reactants. However, the equilibrium constant reduces as temperature rises
due to the exothermic nature of the reaction and thereby resulting in a drop in CO2
conversion. This proves the dominance of thermodynamics in CO2-amine reactions.
Figure 4.61 shows the temperature profile for each inlet temperature for a catalyst weight
of 150g.
Across all catalyst weights, an increase in temperature from 20 to 30oC shows a
marginal drop in conversion whereas an increase from 30 to 40oC showed a considerable
drop in conversion. Average percentage reductions in conversion of 4% and 34.7% are
estimated with an increase in temperature from 20 to 30oC and from 30 to 40oC
respectively. This may be due to a very small equilibrium constant at 40oC. Also, one can
observe that the increase in conversion with catalyst weight is more prominent at this
temperature, followed by 30oC, with 20oC showing the least variation in conversion. The
effect of temperature on the catalyst activity comes into play. Generally, the chemical
contribution the catalyst introduces to the system is by lowering the activation energy and
increasing the frequency of collisions between reacting molecules allowing for the ease in
formation of products. This contribution by the catalyst is realized at higher temperatures
than at relatively lower temperatures for reversible exothermic reactions.
133
Figure 4.60 Effect of Absorber inlet temperature on CO2 conversion (Absorber pressure:
1atm, Gas flowrate: 15 slpm, Amine concentration: 2M/2M BEA/AMP, amine flowrate:
60 ml/min, Desorber temperature: 85oC)
Figure 4.61 Temperature Profile for variation in inlet temperature (Absorber pressure:
1atm, Amine concentration: 2M/2M BEA/AMP, Gas flowrate: 15 slpm, amine flowrate:
60 ml/min, Desorber temperature: 85oC, Catalyst weight: 150g)
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
10 20 30 40 50
frac
tio
nal
CO
2co
nve
rsio
n
Absorber inlet temperature (oC)
0g
50g
100g
150g
0
0.2
0.4
0.6
0.8
1
1.2
6 16 26 36 46 56
Hei
ght
fro
m a
bso
rber
bo
tto
m (
m)
Temperature (oC)
20C 30C 40C
134
Figure 4.62 Cyclic capacity and Removal efficiency at different absorber inlet
temperatures (Absorber pressure: 1atm, Amine concentration: 2M/2M BEA/AMP, Gas
flowrate: 15 slpm, Amine flowrate: 60 ml/min, Desorber temperature: 85oC, Catalyst
weight: 150g)
0
10
20
30
40
50
60
70
0
0.02
0.04
0.06
0.08
0.1
0.12
0.14
0.16
0.18
20 30 40
Rem
ova
l eff
icie
ncy
(%)
Cyc
lic c
apac
ity
(kg/
hr)
Absorber inlet temperature (oC)
Cyclic capacity Removal efficiency
135
4.3.3.4.7 Effect of Absorber Catalyst composition (K loading)
Another parameter that was also varied was the absorber catalyst composition. The
K% (mole-based) was varied (0, 0.5, 1, 3, 5, and 10%) while keeping the catalyst weight
fixed at 150g. From Figure 4.63, a K composition of 1% was seen to be the optimum for
the process conditions that were studied. An estimated rise of 7% was observed with the
introduction of 0.5% K loaded on MgO. With the increase in K from 0.5 to 1%, a huge
percentage increase in conversion of about 52% was observed. After the composition of
1%, further increments in K resulted in a decrease in the performance of the catalyst. The
least fractional CO2 conversion of 0.27 was obtained with 10%K/MgO. With an increase
from 1 to 3%K loading, the conversion dropped to a little over half the conversion at 1%
K loading. The K acts as a promoter and it can be observed that its effect is positive at
very low concentrations while it has a rather detrimental effect as its concentration is
further increased. As mentioned earlier, the major role of the K promoter is to weaken the
MgO bond which facilitates the easy migration of the O2- anion species (Jimenez et al.,
2006). As explained earlier, in the presence of the amine, these electron-rich anion species
easily attack the dissolved CO2, and this interaction ties the CO2 molecules to the surface
of the catalyst, making them readily available for the Nitrogen (N) atom of the amine. In
this way, a longer contact time between the amine solvent and CO2 is achieved, hence,
enhancing the rate of reaction. Another important role of the K is to poison the acid sites
(Mg2+ ions) found in MgO (Ono and Hattori, 2011). Therefore, as the K is increased, a
greater poisoning of the acid sites will occur leading to enhancement in the catalyst
performance. However, this was not so after 1% K. A possible explanation is that the
increase in K after 1% loading resulted in very poor dispersion on the MgO surface
136
resulting in the blocking of pores as well as particle agglomeration. This is evident in the
SEM characterization results showed in Figure 4.66. One can observe significant particle
agglomeration at K loadings of 5% and 10%. Table 4.10 shows the BET characterization
results for all K-loaded catalysts. Though the surface area was largest for 3% K/MgO, a
rather poor performance was realised at this loading in comparison to 1% K/MgO. This is
because the former recorded the smallest pore size, which limited the accessibility of the
reaction molecules to the active sites on the catalyst. This greatly affected its performance.
The removal efficiency and cyclic capacity followed the same trend. Figure 4.65 shows
the XRD patterns obtained for the various K loadings on MgO.
137
Figure 4.63 Effect of Catalyst composition on CO2 conversion (Absorber inlet
temperature: 300C, Absorber pressure: 1atm, Gas flowrate: 15 slpm, Amine
concentration: 2M/2M BEA/AMP, amine flowrate: 60 ml/min, Desorber temperature:
85oC, Catalyst weight: 150g)
Figure 4.64 Cyclic capacity and Removal efficiency at different K loadings (Absorber
pressure: 1atm, Amine concentration: 2M/2M BEA/AMP, Gas flowrate: 15 slpm, Amine
flowrate: 60 ml/min, Desorber temperature: 85oC, Catalyst weight: 150g)
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0% 0.5% 1% 3% 5% 10%
Frac
tio
nal
co
nve
rsio
n
K composition (%)
0
10
20
30
40
50
60
70
0.00
0.02
0.04
0.06
0.08
0.10
0.12
0.14
0.16
0.18
0% K 0.5% K 1% K 3% K 5% K 10% K
Rem
ova
l eff
icie
ncy
(%)
Cyc
lic c
apac
ity
(kg/
hr)
K loading (%)
Cyclic capacity Removal efficiency
138
Table 4.10 Structural characterization of K-loaded MgO catalysts
Catalyst BET surface area,
m2/g
Pore volume,
cm3/g
Pore size,
Nm
MgO 43.49 0.215 19.78
0.5% K/MgO 59.50 0.314 21.09
1% K/MgO 63.33 0.270 17.08
3% K/MgO 69.75 0.129 7.40
5% K/MgO 10.00 0.042 16.95
10% K/MgO 4.18 0.011 11.41
Figure 4.65 XRD pattern for K/MgO catalysts with different K loadings on MgO
139
Figure 4.66 SEM images of different K loadings on MgO (a) 0% (b) 0.5% (c) 1% (d) 3%
(e) 5% (f) 10%
a b
c d
e f
140
4.3.3.4.7.1 Catalyst Deactivation
A problem which typically occurs in catalysis is the drop in catalytic activity over
time. The loss of activity may vary from one catalyst to the other. Some occur very fast in
a matter of seconds and will have to be replaced sooner, whiles others usually take a much
longer time to deteriorate. Therefore, there is the need to either replace or regenerate all
catalysts as time passes (Levenspiel, 1999). Catalyst deactivation comes in many forms,
which are sintering, fouling and poisoning. Sintering refers to the loss or breakdown of
active surface area of catalyst due to prolonged exposure to high temperatures.
Agglomeration, growth of deposited metal on the surface of the support and pore-
narrowing are common features of this form of deactivation (Fogler, 1999).
If the catalyst deactivation is very fast and is as a result of physical blocking of the
active surface, then it is termed fouling (Levenspiel, 1999). A common example is the
deposition of carbon on the catalyst surface during reactions involving hydrocarbons. This
carbonaceous material is referred to as Coke. Poisoning occurs when molecules (either
impurities or reactants) are chemisorbed on the active sites thereby reducing the number
of active sites for reactivity. It may be either temporary or permanent. Permanent poisons
cannot be removed and are thus irreversible. Temporal poisons may require a chemical
treatment of the surface or in the worst case, a replacement of the deactivated catalyst. The
XRD pattern of the 1% K/MgO catalyst after run is shown in Figure 4.67. The only
significant phase change was the transformation of MgO to Mg(OH)2. This can be
attributed to the catalyst surface interaction with water from both the aqueous solvent as
well as the saturated gas. A simple method of regeneration which involves increasing the
141
temperature by flowing hot air through the system to remove moisture is proposed; or the
catalyst can be re-calcined for the same purpose.
142
Figure. 4.67 XRD pattern of 1%K/MgO after run
0
200
400
600
800
1000
1200
1400
1600
1800
2000
0 10 20 30 40 50 60 70 80 90
MgO
Mg(OH)2
KOHK2CO3
143
4.3.3.4.8 Effect of Desorber catalyst (HZSM-5/ γ-Al2O3) ratio
Owing to previous works (Akachuku, 2016) which showed excellent performance
of the single solid acid catalysts HZSM-5 and γ-Al2O3 on CO2 desorption, the performance
of a hybrid form of both catalysts was investigated. The ratios used were 75%HZSM-
5/25% γ-Al2O3, 50%HZSM-5/50% γ-Al2O3 and 25%HZSM-5/ 75%γ-Al2O3. The
individual performance of HZSM-5 and γ-Al2O3 were also tested and the results were
compared to that of the hybrid catalysts. Figures 4.68 and 4.69 show their performance in
terms of CO2 conversion as well as cyclic capacity and removal efficiency. It can be
observed that 100% HZSM-5 outperformed all the others, with 100% γ-Al2O3 performing
poorest. This can be attributed to the catalytic properties. It must be stated that the catalytic
properties reported by Osei (2016) was adopted in this work, since the same catalyst was
used. From the work of Osei (2016), characterization results showed that HZSM-5 had a
higher Bronsted to Lewis acid (B/L) ratio (about 2.5 times higher) than that of γ-Al2O3.
The results indicate a possibility of a larger role played by Bronsted acidity but also
presents possible influence by other parameters. According to Shi et al. (2014), the amine
deprotonation step is very difficult for amines with higher basic strength.
Thus, the order of increasing difficulty is tertiary amines<secondary<primary
amines. Hence, a great deal of energy is required to deprotonate primary amines followed
by secondary amines, with tertiary amines being the least energy intensive. Thus, HZSM-
5 (Bronsted acid) releases its protons into solution ahead of the amine, making it easier for
bicarbonate and carbamate to breakdown to release CO2 since they are the dominant
species in the rich loading region. 100%γ-Al2O3 (Lewis acid) performs poorly due to this
same reason. The amine enters the desorber in the rich loading region and due to the lack
144
of protons in γ-Al2O3, bicarbonate and carbamate ions must fully wait on the deprotonation
of the protonated amine prior to their breakdown.
For the hybrid catalysts, 25%HZSM-5/75% γ-Al2O3 showed a better performance
over the other two hybrids. It seems that increasing the γ-Al2O3 fraction while decreasing
that of HZSM-5 showed a progressive improvement but still didn’t match up to the
performance of 100% HZMS-5. It can be inferred that, the activity of HZSM-5 was fairly
constant for the hybrid catalysts hence making the effect of γ-Al2O3 increments to be
greatly felt. According to Liang et al. (2016), γ-Al2O3 performs better in the lean loading
region where the bicarbonate ion concentration is very low. He stated that a role of γ-Al2O3
in the lean loading region is to imitate the role of bicarbonate ions in this low CO2 region.
Also, the influence of temperature may have shifted the loading from the rich loading
region to the lean loading region where γ-Al2O3 performed better.
145
Figure 4.68 Effect of varying desorber catalyst ratio (HZSM-5/γ-Al2O3) on CO2 conversion
(Absorber inlet temperature: 30oC, Absorber pressure: 1atm, Amine concentration:
2M/2M BEA/AMP, Gas flowrate: 15 slpm, Amine flowrate: 60 ml/min, Desorber
temperature: 85oC, Total catalyst weight: 150g)
Figure 4.69 Cyclic capacity and Removal efficiency for varying desorber catalyst (HZSM-
5/γ-Al2O3) ratio (Absorber inlet temperature: 30oC, Absorber pressure: 1atm, Amine
concentration: 2M/2M BEA/AMP, Gas flowrate: 15 slpm, Amine flowrate: 60 ml/min,
Desorber temperature: 85oC, Total catalyst weight: 150g)
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
CO
2co
nve
rsio
n
40
42
44
46
48
50
52
54
56
0.11
0.115
0.12
0.125
0.13
0.135
0.14
Rem
ova
l eff
icie
ncy
(%)
Cyc
lic c
apac
ity
(kg/
hr)
Removal efficiency Cyclic capacity
146
CHAPTER 5: PARAMETRIC SENSITIVITY ANALYSIS, CONVERSION
CORRELATIONS AND PRELIMINARY ECONOMIC ANALYSIS
5.1 Parametric Sensitivity Analysis
An important feature that cannot be overlooked in any process industry is the effect
of processing conditions on overall plant performance. A way of determining which
parameter contributes more in quantity and quality to enhancing performance is classified
as parametric sensitivity analysis (Nwaoha et al., 2017). It plays an integral role in
optimizing the process plant operation. Optimizing the CO2 capture process with the aim
of improving CO2 conversion or attaining the greatest removal efficiency is desirable and
necessary. From the previous chapter, it is clear that the independent process parameters
(Lean Amine flowrate [LAF], Amine concentration ratio [ACR], Gas flowrate [GF], Inlet
amine temperature [IAT], Lean amine loading [LAL], Absorber catalyst weight [ACW],
Absorber catalyst composition [ACC], and Desorber catalyst composition [DCC]) are all
in different units of measure. As such, drawing deductions based on each individual unit
and how it affects the overall process performance tends to be biased.
To make fair deductions, one has to normalize all independent process parameters
between a scale of 0 and 1 using the correlation shown in equation 5.1
𝑥𝑛𝑜𝑟𝑚 =𝑥−𝑥𝑚𝑖𝑛
𝑥𝑚𝑎𝑥−𝑥𝑚𝑖𝑛 (5.1)
Where; xnorm represents the normalized value of the process parameter, x represents the
actual value of the process parameter to be normalized, xmin represents the minimum value
of the process parameter and xmax represents the maximum value of the process parameter.
In this case, a plot of the dependent process performance variable (y-axis) is made against
the normalized independent process parameters (x-axis). The graph indicates the
147
relationship and degree or extent the independent process parameter has on the dependent
process performance variable; whether directly proportional or inversely proportional. The
degree of dependency is indicated in the gradient of plot. In this way, the slope of the graph
serves as a measure of comparison between all independent process parameters and one
can fairly tell which of them has the greatest or least impact on the dependent process
performance variable (Conversion).
A Parametric sensitivity analysis (PSA) was performed to investigate the impact
of the various independent process parameters (listed above) on CO2 conversion for the
absorption process. It is important to note that there were cases where a Gaussian-like
profile (both increase and decrease zones) existed for a specific parameter curve. In such
situations, the plot was split into the different zones, and the slope of each zone was then
determined. For a fair basis of comparison of such independent process parameter with
other independent process parameters, a single slope was determined by adding the
absolute values of the different zone slopes. Parameters were classified as affecting either:
• The reactivity on catalyst surface (e.g. ACC, LAL and ACW)
• Liquid film resistance (e.g. LAF and ACR)
• Gas film resistance (e.g GF)
• and Solubility (e.g IAT)
Table 5.1 displays the impact of the different independent process parameters on
CO2 conversion. The values of the slopes shown are the absolute values since some
parameters (LAL, ACR and IAT) had an inverse relationship with CO2 conversion. From
the table one can observe that ACC, with a slope of 1.088, has the greatest impact on CO2
148
conversion. Varying the K loading on MgO greatly affected conversion owing to the role
played by the catalyst. A major role of the K promoter is to weaken the MgO bond
facilitating the easy migration of the O2- anion species as well poisoning the acid sites
(Mg2+) present. This provides an insight into the optimum K-loading suitable for the CO2
absorption process.
The next influential parameter was the gas flowrate (GF). This is not unexpected
as increasing the total gas flowrate corresponds to increasing the CO2 flowrate, and this
greatly affects the gas side mass transfer coefficient hence reduces the gas phase resistance
for CO2 transfer into the amine. Hence, any reduction in this resistance translates into
greatly increasing the driving force for mass transfer. This relationship was also obtained
in the work of Arshad et al., (2013). This is a huge benefit owing to the fact that with the
same lean amine circulation flowrate (hence no change in cost of solvent pumping) one
can attain higher CO2 removal capacities by increasing the flow of gas. This is however
impractical since the absorption unit for CO2 capture is designed for a specific gas
flowrate. As such, this process parameter’s variation impact is somewhat less significant
in the real word.
LAL shows the next greatest impact after GF. This is rightly so because a higher
lean loading means less available free amines for reaction. A higher availability of active
free amines translates into a greater driving force for mass transfer. LAL is a direct result
of the desorption temperature. Hence, they go hand-in-hand. Similar results were obtained
by Dey and Aroonwilas (2009), Xu et al. (2016) and Koronaki et al. (2017).
Table 5.1 also shows that varying both ACR and IAT affects the dependent
variable to a greater extent than LAF and ACW. For ACR, reaction kinetics and solubility
149
play a role as AMP concentration is increased. Owing to its sterical hindrance and larger
absorption capacity (due to carbamate hydrolysis), an increase in AMP concentration
results in higher conversion of CO2. The contribution from solubility (viscosity effects) is
seen with a corresponding decrease in BEA concentration as AMP concentration is
increased. As shown earlier in Figures. 4.48 to 4.55, the viscosity of the amine decreases
with decreasing BEA concentration. This means a reduction in mass transfer limitation
effects. IAT is seen to also have a strong impact on conversion. It is important to note that
the reaction between CO2 and aqueous amines is exothermic. Hence, at higher
temperatures, the reaction is impeded, reducing the net transfer of CO2 into the amine.
Also this is supported by the fact that gas viscosity increases with temperature, hence this
impedes the movement of gas into the liquid as temperature increases.
For LAF, an increase signifies larger interfacial area created between the gas and
liquid. Thus, the wetted area for mass transfer is enhanced, allowing easier movement of
gas into the liquid (Osei et al., 2017; Nwaoha et al., 2017; Xu et al., 2017). The impact of
ACW is relatively low and not really depicted probably due to the inherent characteristics
of the novel solvent blend, though it’s seen to have a positive effect on CO2 conversion.
Perhaps a greater impact would have been realized if a solvent with relatively poor
performance had been utilized.
DCC is seen to have the least impact on conversion. The variation in DCC (HZSM-
5/ γ-Al2O3 ratio) seems to have the least effect on conversion as compared to other process
parameters. Liang et al., (2015) reported on the effect of variation in catalyst composition.
A similar trend is seen. Hence according to this work, it has been shown that in order to
maximize CO2 conversion for the range of conditions studied, the most influential area is
150
the reactivity on the catalyst surface as its parameters (ACC and LAL) had the greatest
impact on conversion. The next influential area is the gas film resistance which is affected
by the GF. The liquid film resistance and solubility parameters were seen to have lower
effects on conversion. The order for the decreasing impact of process parameters on CO2
conversion is established to be: ACC>GF>LAL>ACR>IAT >LAF>ACW>DCC.
151
Table 5.1 Impact of various independent process parameters on CO2 conversion.
Parameter Slope
Lean Amine flowrate (LAF) 0.159
Lean Amine Loading (LAL) 0.288
Amine Concentration Ratio (ACR) 0.187
Inlet Amine Temperature (IAT) 0.163
Gas Flowrate (GF) 0.340
Absorber Catalyst Weight (ACW) 0.125
Absorber Catalyst Composition (ACC) 1.088
Desorber Catalyst Composition (DCC) 0.096
152
5.2 Conversion Correlation
Usually, mathematical representations also known as correlations are employed in
predicting the results of an experiment. Researchers with the aid of modelling are able to
conduct sensitivity studies to evaluate how variations in crucial system variables modify
the dynamic behaviour of a system. Statistical models help to determine an association
among variables. In this work, a statistical analysis was adopted with the objective of
developing a correlation or an empirical model to predict the CO2 conversion within the
boundaries of the experimental conditions studied.
Employing a multiple regression statistical tool in Excel software, an empirical
correlation representing CO2 conversion, X as a function of the process variables was
developed. The model is represented as:
Conversion, X = -1.926643963 + (0.010089725*Lean Amine Flowrate) +
(0.034640523*Gas Flowrate) + (0.1638727*Amine Concentration Ratio) +
(0.000491441*Absorber Catalyst Weight) - (0.011098313*Inlet Amine Temperature) +
(0.016139619*Desorber Bed Temperature) + (0.093958826*Desorber Catalyst
Composition) - (0.000101332*Desorber Catalyst Weight) - (3.111404492*Absorber
Catalyst Composition) (5.1)
The amine concentration ratio was that of AMP to BEA. Also, it is worth noting
that except for the case of absorber and desorber catalyst weights and compositions, which
can assume a zero (0) value, all other parameters utilized in this work were non-zero
values. Table 5.2 shows the range of parameters for which the correlation is applicable.
153
Parameters are statistically insignificant when their P-values in the Coded Coefficients in
Appendix E are less than α which is 0.05. The correlation adequacy was evaluated by the
coefficient of multiple determination, R2. The R2, R2-adjusted and R2-predicted of the
correlation were 0.92, 0.81 and 0.84 respectively. These suggest that the correlation fits
well with the experimental data. A parity chart of the predicted and experimental CO2
conversion in figure 5.1 shows a good correlation with an AAD of 9.15%.
154
Table 5.2 Parameter range for developed conversion correlation
Parameter Range Units
Lean amine flowrate 50 – 70 ml/min
Gas flowrate 10 – 20 slpm
Amine concentration ratio
(AMP/BEA)
0.33 - 5 -
Absorber catalyst weight 0 – 150 g
Absorber catalyst composition
(K-loading)
0 – 10 %
Inlet amine temperature 20 – 40 oC
Desorber bed temperature 75 – 95 oC
Desorber catalyst weight 0 – 150 g
Desorber catalyst composition 0 – 100 %
155
5.3 Statistical analysis for catalyst characteristics
A correlation was also developed to relate the catalyst physical properties with
conversion. The variables employed were the BET surface area, Pore volume and Pore
size. The statistical analysis was conducted using the multiple regression tool in Excel
software package. The relationship between conversion and the physical properties is
represented as:
Conversion, X = 0.233866 + (47.046*BET surface area*Pore volume) - (188183.711*
Pore size) (5.2)
The R2, R2-adjusted and R2-predicted of the correlation were 0.94, 0.88 and 0.76
respectively. The regression model (5.2), indicates that the BET surface area, pore volume
and pore size contribute to the CO2 absorption process. A parity chart of the predicted and
experimental CO2 conversion in figure 5.2 shows a good correlation with an AAD of
9.42%.
156
Figure 5.1 Parity plot of Predicted and experimental conversion for the conversion
correlation.
Figure 5.2 Parity plot of Predicted conversion and experimental conversion for catalyst
properties statistical analysis.
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7
157
5.4 Preliminary Economic Analysis
Despite its huge contribution to reduction in CO2 emissions, CO2 capture
technologies (including Post-Combustion CO2 capture) are currently plagued with their
relatively high costs. Efforts are currently underway to greatly reduce the cost of these
technologies. Costs associated with Chemical Absorption Post-Combustion CO2 Capture,
as with all other technologies, can be grouped into Capital costs (CAPEX) and Operating
costs (OPEX). Equipment costs is a major component of the capital costs. Usually, the
operating costs entails the cost of regenerating solvents and the electrical energy required
to operate pumps, blowers etc. (Zhang et al. 2017a). The largest contributor to operating
cost is the solvent regeneration energy which constitutes about 70–80% of the operating
cost for CO2 capture process (Zhang et al. 2017b).
A preliminary study was conducted to estimate and compare the cost of employing
the novel solvent (BEA-AMP) as against conventional solvents like MEA and MEA-
MDEA for CO2 capture. For the BEA-AMP system, costs were also estimated with the
introduction of absorber catalyst to the system, and a further comparative study involving
variations of different parameters and their associated costs were reported. The
components making up the cost for this study include cost of solvents, catalyst costs, cost
of structured packing, energy for regeneration and carbon tax.
Figure 5.3 shows annual cost incurred for the different solvent systems (MEA,
MEA-MDEA and BEA-AMP). Comparing the non-catalytic and catalytic systems of each
solvent, a general decrease in cost is observed with the introduction of desorber catalyst.
This is because with the addition of the desorber catalyst, a greater quantity of CO2 was
158
captured (increase in cyclic capacity). The cost was estimated per quantity of captured
CO2 as in:
𝐴𝑛𝑛𝑢𝑎𝑙 𝑐𝑜𝑠𝑡 ($
𝑘𝑔 𝐶𝑂2) =
𝑇𝑜𝑡𝑎𝑙 𝑐𝑜𝑠𝑡 ($)
𝑐𝑦𝑐𝑙𝑖𝑐 𝑐𝑎𝑝𝑎𝑐𝑖𝑡𝑦 (𝑘𝑔 𝐶𝑂2)
Cyclic capacity represents the quantity of CO2 captured. Since this value appears in the
denominator, a larger capture quantity results in reducing the cost incurred. Also, it is
worth noting that the high-priced structured packing had a significant effect on the total
cost incurred. Inferentially, the introduction of catalyst cut down the total cost incurred
since the catalyst replaces the structured packing. Hence the number of structured packing
in the catalytic system is lower than that of the non-catalytic system. Generally, comparing
the three solvents, BEA-AMP incurred the least cost, followed by MEA-MDEA and
finally MEA recording the highest cost for solvent-based Post-Combustion CO2 capture
based on the components employed in estimating cost in this study. Details of the
calculation are shown in Appendix F.
A separate analysis on the BEA-AMP system was also conducted. Here, the cost
of CO2 capture was estimated for the base case of no absorber catalyst at the conditions
shown in table 5.3. This cost was then compared with the cost incurred for incorporating
an optimum absorber catalyst weight of 150g as well as with non-catalytic cases (no
absorber catalyst) where variation in other process parameters (solvent flowrate, amine
inlet temperature, amine concentration ratio, desorber catalyst weight, and gas flowrate)
performed better than the base case in terms of CO2 captured.
For BEA-AMP system, the base case of no absorber catalyst incurred an annual
cost of CAD $6.08/kg CO2 captured (Figure 5.4). This cost was greatly reduced by about
159
40% with the introduction of the absorber catalyst (K/MgO) and was recorded as the least
incurred cost among all process parameter variations. As explained before, the reduction
in cost is partly due to the larger cyclic capacity of the catalytic system as well as the
replacement of the high-priced structured packing with the relatively cheaper catalyst.
From figure 5.4, the desorber bed temperature of 95oC (no absorber catalyst) was the
immediate next to the least incurred cost. Operating at this temperature resulted in better
performance (larger cyclic capacity) compared to the other variations in process
parameters. This is because desorption increases with temperature, hence at a temperature
of 95oC, more CO2 was removed from the solvent. Since the total cost is divided by the
amount of CO2 captured, this results in lowering the cost incurred. For the other variations
in process parameter, the cost incurred were quite close to the base case of no absorber
catalyst as shown in figure 5.4, with the closest being the case of operating at an absorber
inlet amine temperature of 20oC. A breakdown of the cost is shown in Appendix F.
Overall, it is realised that employing catalysts in Post-combustion capture helps in
truncating the associated operating costs. This greatly contributes to making it a long term
viable technology.
160
Fig 5.3 Annual cost incurred for the different solvent systems
Fig 5.4 Annual cost incurred for the different parameter variations for BEA/AMP system
0
2
4
6
8
10
12
14
16
18
cost
($)
/ kg
CO
2
Configuration
MEA MEA-MDEA BEA-AMP
0
1
2
3
4
5
6
7
cost
($)
/kg
CO
2
Parameter
161
Table 5.3 Base case conditions used for Preliminary Economic Analysis
Parameter Value
Absorber Catalyst weight 0 g
Amine Concentration ratio 2M AMP/2M BEA
Amine flowrate 60 ml/min
Amine inlet temperature 30oC
Desorber bed temperature 85oC
Gas flowrate 15 slpm
162
CHAPTER 6: CONCLUSIONS AND RECOMMENDATIONS
6.1 Conclusions
Screening studies were conducted on a total of seven solid basic catalysts at a semi-
batch scale to select which of them would be most suitable for full-cycle bench-scale pilot
plant studies in terms of initial rate of absorption and mechanical stability. K/MgO
exhibited excellent initial rate of absorption and was the most mechanically stable and was
thus selected.
Solvent performance comparison in a full-cycle bench-scale pilot plant between a
novel 4M BEA-AMP solvent blend and conventional solvents 5M MEA and blended 7M
MEA-MDEA revealed better carbon capture characteristics (faster kinetics) of the former
over the two latter solvents. Absorption and desorption kinetics were fastest for BEA-
AMP blend followed by MEA-MDEA with MEA being the slowest for both catalytic
(HZSM-5) and non-catalytic desorption. The inherent solvent structural properties and
lowest lean loading of BEA-AMP resulted in faster reaction rates as compared to single
MEA and MEA-MDEA blend.
For catalytic desorption, percentage increments of 53.4% and 78.3% in absorption
and desorption rates were seen for BEA-AMP over the conventional MEA solvent. The
presence of the butyl group in BEA enhanced absorption rates significantly for the blend.
The steric effect of AMP in the blend contributed to the fastest CO2 desorption rate for the
BEA-AMP blend. HZSM-5 increased desorption rates by providing an alternative pathway
where bicarbonate ions were produced hence resulting in the faster release of CO2.
163
Catalytic absorption (K/MgO) and catalytic desorption (HZSM-5) kinetics were
also studied at the pilot plant level for the aqueous CO2-BEA-AMP system. Upon the
addition of the solid base-catalyst (K/MgO) into the absorber, a huge improvement was
seen in the rate of CO2 absorption. When compared to the case of only HZSM-5 in
desorber, an increase of 61% was made when K/MgO was incorporated into the absorber.
A synergistic increase in the absorption rate of about 99% was observed with the addition
of both K/MgO and HZSM-5 using the blank case of no catalyst in both columns as basis
of comparison.
K/MgO exhibited excellent absorption performance due to its good electron
donating ability. The generation of super basic sites was related to the existence of O2-
anion vacancies in MgO. Also, an interaction between K and Mg in MgO resulted in the
weakening of the Mg-O bonds and therefore aided in the easy migration of the O2- anion
species. In the presence of the amine, these electron-rich anion species (O2-) easily attacked
dissolved CO2, and this interaction tied the CO2 molecules to the surface of the catalyst,
making them readily available for reaction with the Nitrogen (N) atom of the amine. In
this way, a greater contact time was realized between the amine solvent and CO2 hence
enhancing the rate of reaction. However, increasing the K% beyond 1% loading resulted
in very poor dispersion on the MgO surface resulting in the blocking of pores as well as
particle agglomeration. This resulted in lower conversions.
Higher absorption and desorption rates by the added effect of the catalyst translates
into vast reduction in size of the absorption and desorption columns, hence huge reduction
in capital costs for installing such columns.
164
Intrinsic kinetic analysis was conducted at the pilot plant level for the catalytic
absorption process for the aqueous CO2-BEA-AMP system over a solid alkaline catalyst
(K/MgO) which is the first of its kind. Kinetic performance was evaluated in terms of CO2
conversion, hence rate of reaction; and kinetic parameters were determined considering
both reversible and irreversible reaction of CO2 with aqueous amine solvents. The power
law model was employed in fitting the kinetic data. An activation energy, Ea of 5.67E+04
J/mol and 3.40E+04 J/mol were obtained for the reversible and irreversible reactions
respectively. A reaction order of 1 and 2 with respect to CO2 were obtained also with the
reversible and irreversible reactions respectively. This shows a higher dependency of the
reaction rate on CO2 with the introduction of a heterogeneous catalyst considering an
irreversible reaction. It is a further indication of the complexity of the reaction as a third
phase (solid) is introduced as well as a further indication of a greater coverage of the
K/MgO catalyst by CO2. Both cases gave an order of 1 for the blended amine solvent. A
parity plot showing the degree of correlation between the experimental and predicted rate
was shown, recording an AAD of 13.29% for the reversible case and 14.1% for the
irreversible case. The power law model for the reaction system was obtained as:
−r𝐶𝑂2 = 7.98 × 10−7 exp (−3.4 × 104
𝑅𝑇) 𝐹𝐴
2𝐹𝐵1
The effect of various process parameters on CO2 conversion, cyclic capacity and
removal efficiency were investigated. A solid alkaline catalyst weight of 150g was
established to be the optimum weight under the process conditions studied.
Parametric Sensitivity analysis (PSA) to investigate the impact of each
independent process parameter on the CO2 conversion was conducted and it was observed
165
that the most influential parameter was the Absorber catalyst composition (ACC),
followed by the Gas flowrate (GF) and Lean amine loading (LAL). The least influential
was seen to be the Desorber Catalyst composition (DCC). The order of decreasing impact
of process parameters on conversion was observed to be as follows:
ACC>GF>LAL>ACR>IAT>LAF>ACW>DCC.
A correlation to predict conversion was also developed. The correlation adequacy
was evaluated by the coefficient of multiple determination, R2. The R2, R2-adjusted and
R2-predicted of the correlation were 0.92, 0.81 and 0.84 respectively suggesting that the
correlation fits well with the experimental data. A parity plot of the predicted and
experimental CO2 conversion yielded an AAD of 9.15%. Another correlation was also
developed to relate the catalyst physical properties (BET surface area, pore volume and
pore size) with conversion. Here also the R2, R2-adjusted and R2-predicted of the
correlation were 0.94, 0.88 and 0.76 respectively. A parity plot of the predicted and
experimental CO2 conversion shows a good correlation with an AAD of 9.42%.
Preliminary economic analysis showed that the novel solvent, BEA-AMP recorded
the least annual operating cost incurred when compared with conventional MEA and
MEA-MDEA solvents. A separate analysis on the BEA-AMP system revealed that the
introduction of absorber catalyst resulted in lowering the operating costs by about 40%
using the base case of no absorber catalyst as reference. This was the least cost when
compared with the cost incurred upon varying other process parameters. It was realised
that employing catalysts in Post-combustion capture helps in truncating the associated
operating costs and greatly contributes to making it a long term viable technology.
166
6.2 Recommendations
Application of solid base or alkaline catalysts to the solvent based CO2 absorption
process has been proven to improve the kinetics of the system in terms of coversion and
absorption rate. This catalytic study however needs to be further probed prior to full
implementation at the industrial scale. As such, the following recommendations should be
investigated in the future:
• Novel alkaline catalysts should be produced and specifically tailored to
improve catalyst characteristics responsible for increasing conversion and
rate of absorption such as electron-donating ability, larger surface area and
pore volume.
• Further work should be performed on the stability of the catalyst (Time on
stream studies) as well as on catalyst deactivation (loss of catalyst activity).
• Comprehensive mechanistic models should be developed to describe and
justify the catalytic mechanism involved in the absorption process.
• A solvent degradation study on the novel solvent should be conducted both
in the presence and absence of the catalyst to analyse its effect.
167
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Greenhouse Gas Control, Volume 44, 2016, Pages 115-123.
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carbonic anhydrase and the biocatalyst for promoting CO2 capture in vertical reactor,
International Journal of Greenhouse Gas Control, Volume 49, 2016, Pages 290-296.
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amines. Chem. Eng. Sci. 1986, 41, 405-408.
193
APPENDICES
APPENDIX A1: Standard Operating Procedure for running the CO2 capture plant
for kinetic data
Pre-operation
• The desired absorber catalyst weight is measured with a mass balance and divided
into six (6) equal parts. The absorption column is unmounted from the rig, and the
structured packings and spent catalyst from the previosus run are then removed.
The structured packing and the column internals are thoroughly washed with water
and dried. The measured catalyst weights are then transferred into the column and
interspersed with the structured packings. The total number of structured packings
used in the absorption column is seven (7).
• A similar procedure is carried out for the desorption column but with a few differences.
The desired desorber catalyst quantity is weighed, and transferred into a 2-inch
diameter 1000 ml measuring cylinder. It is then topped up with 3mm inert marbles to
the 900 ml mark and transferred to a different container. It is ensured that when mixing
the catalyst with the 3mm inert marbles no catalyst particle attrition takes place. 6 mm
inert marbles are also measured in the 2-inch diameter measuring cylinder and filled
to the 100 ml mark. This is repeated as two sets of the 6mm inert marbles are
needed. The column is then loaded with structured packings first, then 6mm inert
marbles, then a mixture of 3mm inert marbles and catalyst. The second set of 6 mm
inert marbles is transferred and finally a last layer of structured packings is added.
• A known concentration of the amine solution to be used is prepared in a 2000 ml
volumetric flask hours before beginning the experiment to allow ample time for
194
mixing. It is kept in a fume hood and well stirred until the experiment begins. Prior
to starting the experiment, the concentration is confirmed. For the case where the
concentration is not exact as desired, the necessary adjustments are made.
• The infrared (IR) gas analyser is also calibrated with a 15% CO2 (balance N2) gas
cylinder before beginning the experiment. One may also choose to calibrate it
during the experiment to ensure accurate recordings.
• It is also ensured that the gas saturator is checked regularly before every
experimental run and topped up with water if the need be.
• 100% CO2 and N2 tanks are secured in place and connected to the plant.
• The LABVIEW software is started and thermocouples are checked to ensure they
are in proper working conditions. Faulty thermocouples are removed and replaced.
Prior to replacing faulty thermocouples, the new thermocouples are calibrated and
then connected to the plant.
During Operation
• The prepared amine solution is first circulated through the plant with the aid of a
pump. This continues until the liquid (amine) level indicators on both columns are
stable
• Simultaneously, both the cooler and heater are turned on and the latter is gradually
raised to the set temperature. The heating medium (glycerol) is then circulated
through the system once the liquid (amine) level in the columns have attained
stability.
195
• The gas is then introduced at the desired concentration into the bottom section of
the absorber via the saturator system. The concentration is verified with the gas
analyser and the plant is made to run continuously.
• After the introduction of the gas, a thorough leak check is done to ensure the
absence of any gas leaks in the system.
• Upon attaining stability, the temperature profiles of both columns, outlet CO2
concentration at the top of the absorber, and lean and rich loadings are checked
sporadically. This is done until their readings are fairly constant. It is then ensured
that the system is not disturbed at this point.
• The concentration profile along the absorber is then measured with the IR gas
analyser beginning from the top and gradually moving down to the last point on
the column. The inlet CO2 concentration is also measured. The values are then
entered manually into the LABVIEW software interface. At the same time, lean
and rich amine samples are taken and loadings are checked.
• Upon entering the CO2 concentration profile, the LABVIEW software is engaged
to write the whole plant data (including temperature profiles of both columns) into
an excel worksheet, after which the plant is shutdown.
196
Post-operation
• To shut down the plant, the gas flow to the column is ceased and the cooler is
allowed to run to gradually cool the system down. At this point, the heater is turned
off.
• The amine solution is still allowed to circulate for some time while cooling the
system. This is to ensure the gradual cooling of hot sections of the plant.
• After cooling, both absorber and desorber columns are dismounted, cleaned and
prepared for the next experiment using the procedure mentioned earlier.
• For cases where the amine type is to be changed, it is ensured that deionized water
is circulated thoroughly through the plant to eliminate the previous amine in the
system. This is done before dismounting both columns.
197
Fig. A1-1. Screenshot of LABVIEW software interface for data collection from CO2 capture plant
198
APPENDIX A2: Determination of Solvent Concentration and Loading
The concentration of the solvent (C1) is determined by titrating a known volume (V1) of
the solvent with 1 N Hydrochloric acid using methyl orange as indicator. The equation
used is as follows:
𝐶1𝑉1 = 𝐶2𝑉2 (A2.1)
Where:
𝐶1 = solvent concentration (mol/L) (unknown)
𝑉1 = solution sample volume (ml) = 1 ml
𝐶2 = HCl concentration (mol/l) = 1 mol/L
𝑉2 = HCl volume from titration (ml) = 4 ml
𝐶1 =𝐶2𝑉2
𝑉1=
1 × 4
1= 4 𝑚𝑜𝑙/𝐿
The Chittick apparatus is used in determining the lean and rich solvent loadings. 1 ml of
the solvent is placed in a conical flask and titrated against 1 N HCl solution. Usually, an
additional 2 ml HCl is added to ensure the complete the evolution of gas. CO2 is evolved
from the lean/rich solvent displacing the liquid in the graduated tube of the apparatus. The
volume of liquid displaced is equal to the CO2 volume evolved from the solvent. The
following equation is used to calculate the loading, 𝛼:
𝛼 = (𝑉𝐶𝑂2
− 𝑉𝐻𝐶𝑙,𝑡𝑜𝑡𝑎𝑙
𝑉𝑚𝑉1𝐶1) (
273
298)
199
Where:
𝑉𝐶𝑂2 – Volume of CO2 gas evolved
𝑉𝐻𝐶𝑙,𝑡𝑜𝑡𝑎𝑙 – Total volume of HCl used
𝑉𝑚 – Molar volume of gas at STP (22.4 L/mol)
For a typical case where 𝑉𝐶𝑂2= 60 𝑚𝑙, 𝑉𝐻𝐶𝑙,𝑡𝑜𝑡𝑎𝑙 = 6 𝑚𝑙, 𝑉1 = 1 𝑚𝑙 and 𝐶1 = 4 𝑚𝑜𝑙/𝐿,
we obtain a loading, 𝛼 = 0.552 mol CO2/mol amine
200
Table A2-1. Typical experimental data (100g K/MgO, 150g HZSM-5, 60 ml/min, 30oC
absorber amine inlet temperature run)
Inlet Outlet Unit
Gas flowrate reading 15.0 13.9 slpm
Meter Temperature 23.4 28.6 oC
Meter Pressure 15.8 14 psia
CO2 composition 15.1 6.2 %
H2O composition 0.0 0.0 %
N2 composition 84.9 93.8 %
Titration
Lean Rich
HCl at end point 4 4.1 ml
HCl total volume 6 6 ml
CO2 volume 38 61 Ml
BEA/AMP
concentration 4 4.1 mol/L
mol CO2 1.308 2.249 mol
loading 0.33 0.55 mol/mol
201
APPENDIX B: Estimation of Heat and Mass Transfer Limitations
Appendix B1: Calculation of Diffusion coefficient of CO2 in BEA/AMP (DAB) and
effective diffusivity (Deff)
The diffusion coefficient of CO2 in BEA/AMP solution was estimated by N2O analogy.
𝐷𝐴𝐵 = 𝐷𝐶𝑂2−𝑎𝑚𝑖𝑛𝑒 = 𝐷𝑁2𝑂−𝑎𝑚𝑖𝑛𝑒𝐷𝐶𝑂2−𝑤𝑎𝑡𝑒𝑟
𝐷𝑁2𝑂−𝑤𝑎𝑡𝑒𝑟 (B1-1)
𝐷𝑁2𝑂/𝑚2𝑠−1 = 5.07 × 10−6𝑒𝑥𝑝 (−2371
𝑇/𝐾) (Versteeg et al. 1987)
𝐷𝐶𝑂2/𝑚2𝑠−1 = 2.35 × 10−6𝑒𝑥𝑝 (−
2119
𝑇/𝐾)
The diffusion coefficients were determined at the maximum operating condition of 40oC
where heat and mass transfer limitations are likely to occur. The Stoke-Einstein equation
was used to estimate the Diffusion coefficient of N2O in the BEA/AMP solvent. It is
given as:
𝐷𝑁2𝑂 . 𝜇0.8 = 𝑐𝑜𝑛𝑠𝑡𝑎𝑛𝑡
Where 𝜇 – dynamic viscosity of BEA/AMP
The dynamic viscosity of BEA/AMP at 40oC was determined experimentally to be 3.4
mPa.s. Also, the constant was determined to be 7.3874×10-12 and used to find DN2O in
the amine as:
𝐷𝑁2𝑂 =7.3874×10−12
3.4×10−3 = 6.97 × 10−10 𝑚2𝑠−1
The diffusivity of CO2 in the solvent was then calculated from equation B1-1 as:
𝐷𝐴𝐵 = 𝐷𝐶𝑂2−𝑎𝑚𝑖𝑛𝑒 = 6.97 × 10−10 (2.70 ×10−9
2.61 ×10−9 ) = 7.3 × 10−10 𝑚2𝑠−1
202
The effective diffusivity was then calculated from the equation:
𝐷𝑒𝑓𝑓 =𝐷𝐴𝐵𝜀
𝜏 (Fogler, 1999)
Where 𝜀 – void fraction and 𝜏 – tortuosity usually taken as 8 (Fogler, 1999)
The void fraction was determined from the equation given by Geankoplis (2003):
𝜀 = 0.38 + 0.073[1 +(
𝑑
𝑑𝑝−2)
2
(𝑑
𝑑𝑝)
2 ]
Where d – internal diameter of reactor
dp – particle diameter
𝜀 = 0.38 + 0.073[1 +(
𝑑
𝑑𝑝−2)
2
(𝑑
𝑑𝑝)
2 ] = 0.38 + 0.073 [1 +(
0.051
4.0 ×10−4−2)2
(0.051
4.0 ×10−4)2 ] = 0.5049
Hence,
𝐷𝑒𝑓𝑓 =𝐷𝐴𝐵𝜀
𝜏=
7.29×10−10×0.5049
8 = 4.61 × 10−11𝑚2𝑠−1
203
Appendix B2: Calculation of Mass transfer coefficient (kc)
The mass transfer coefficient (kc) was determined using the correlation for packed beds
in Perry and Green (1997). The following correlations for dimensionless numbers were
used:
𝑁𝑆ℎ = 0.91𝜓( 𝑁𝑅𝐸)0.49( 𝑁𝑆𝐶)1
3⁄
𝑁𝑅𝐸 = 𝑑𝑝𝑉𝑠𝜌
𝜇(1−𝜀) , 𝑁𝑆𝐶 =
𝜇
𝜌𝐷𝐴𝐵 and 𝑁𝑆ℎ =
k𝑐𝑑𝑝
𝐷𝐴𝐵
Where 𝑁𝑆ℎ- Sherwood number, 𝑁𝑅𝐸 – Reynolds number, 𝑁𝑆𝐶 – Schmidt number, 𝜓 –
shape factor = 1 (for particle), dp – particle diameter, Vs – superficial velocity, 𝜇 – dynamic
viscosity of fluid (experimentally determined to be 8.08 mPa.s) and 𝜌 – density of fluid
(also determined experimentally to be 1026.27 𝑘𝑔/m3).
The superficial velocity was calculated as:
𝑉𝑠 = 𝑣𝑜𝑙𝑢𝑚𝑒𝑡𝑟𝑖𝑐 𝑓𝑙𝑢𝑖𝑑 𝑓𝑙𝑜𝑤
𝑐𝑟𝑜𝑠𝑠−𝑠𝑒𝑐𝑡𝑖𝑜𝑛𝑎𝑙 𝑎𝑟𝑒𝑎 =
60 𝑚𝑙/ min×1×10−6𝑚3
𝑚𝑙×
1 𝑚𝑖𝑛
60 𝑠
2.04×10−3𝑚2 = 4.90 × 10−4𝑚/𝑠
Reynolds number, 𝑁𝑅𝐸 was also calculated as:
𝑁𝑅𝐸 = 𝑑𝑝𝑉𝑠𝜌
𝜇(1−𝜀) =
4.0×10−3×4.9×10−4×1026.27
8.08×10−3 (1−0.5049) = 0.502
Also, Schmidt number was calculated as:
𝑁𝑆𝐶 =𝜇
𝜌𝐷𝐴𝐵=
8.08×10−3 𝑘𝑔
𝑚.𝑠
1026.27 𝑘𝑔/m3 ×7.29×10−10𝑚2
𝑠
= 10.78
Therefore
𝑁𝑆ℎ = 0.91𝜓( 𝑁𝑅𝐸)0.49( 𝑁𝑆𝐶)1
3⁄ = 0.91 × 1 × (0.502 )0.49(10.78)1
3⁄ = 1.435
204
Also, it is known that:
𝑁𝑆ℎ = k𝑐𝑑𝑝
𝐷𝐴𝐵
⟹ 𝑘𝑐 = 𝑁𝑆ℎ𝐷𝐴𝐵
𝑑𝑝=
1.435×7.29×10−10𝑚2
𝑠
4.0 ×10−3𝑚= 2.62 × 10−7𝑚/𝑠
205
Appendix B3: Calculation of Effective thermal conductivity (λeff)
The effective thermal conductivity was determined from the equation given by Walas et
al. (1990).
𝜆𝑒𝑓𝑓
𝜆= 5.5 + 0.05 𝑁𝑅𝐸
Where 𝜆𝑒𝑓𝑓- effective thermal conductivity and 𝜆- thermal conductivity which was
determined using the Bridgman’s equation as:
𝜆 = 3.0 (𝑁
𝑉)
23⁄
𝐾𝐵𝑉𝑆
Where KB - Boltzman constant = 1.381 𝑥 10-23 𝐽/𝐾, N - Avogadros number = 6.02 𝑥 1023,
Vs - speed of sound = 1654.84 ms-1 and V - average molar volume = average MW/density
= 27.879 gmol-1/ 1.02627gcm-3 = 27.17cm3mol-1.
Therefore,
𝜆 = 3.0 (𝑁
𝑉)
23⁄
𝐾𝐵𝑉𝑆 = 3.0 (6.02 x 1023
27.17x 10−6𝑚3𝑚𝑜𝑙−1)2
3⁄
1.381 x 10−23 J/K × 1654.84 ms-1
𝜆 = 5.41 × 10−1W/mK
Hence,
𝜆𝑒𝑓𝑓 = 𝜆(5.5 + 0.05 𝑁𝑅𝐸) = 5.41 × 10−1(5.5 + (0.05 × 0.502) ) = 2.988 W/mK
206
Appendix B4: Calculation of Heat transfer coefficient (h)
The heat transfer coefficient was estimated using the correlation adopted from Ibrahim and
Idem (2007):
𝐽𝐻 = 𝐽𝐷 = (ℎ
𝑐𝑝𝑢𝜌) 𝑁𝑃𝑟
23⁄
Where 𝐽𝐻 𝑜𝑟 𝐽𝐷 – Heat transfer J-factor, cp – heat capacity of feed stream at 40oC (2.85
KJ/kg/K - determined experimentally) and 𝑁𝑃𝑟 – Prandtl number which is represented in
the form:
𝑁𝑃𝑟 =𝑐𝑝𝜇
𝜆 =
2.85 KJ/kg/K×8.08 𝑚𝑃𝑎.𝑠
5.41 ×10−1W/mK = 42.6
Also,
𝐽𝐻 = 𝐽𝐷 = (0.4548
ε) 𝑁𝑅𝐸
−0.4069 (Geankoplis, 2003)
𝐽𝐻 = 𝐽𝐷 = (0.4548
ε) 𝑁𝑅𝐸
−0.4069 = (
0.4548
0.5049) 0.502−0.4069 = 1.192
Therefore;
ℎ =𝐽𝐻
𝑁𝑃𝑟2
3⁄× 𝑐𝑝 × 𝑢 × 𝜌
ℎ =1.192×2.85×4.89×10−4×1026.27
42.62
3⁄= 1.40 × 10−1 𝑘𝐽
𝑚2𝑠𝐾
207
Appendix B5: Determination of internal pore heat transfer resistance
(∆𝑻𝒎𝒂𝒙, 𝒑𝒂𝒓𝒕𝒊𝒄𝒍𝒆)
∆𝑇𝑚𝑎𝑥, 𝑝𝑎𝑟𝑡𝑖𝑐𝑙𝑒 =𝐷𝑒𝑓𝑓×(𝐶𝐴,𝑆−𝐶𝐴𝐶)×(∆𝐻𝑟𝑥𝑛)
𝜆𝑒𝑓𝑓
(∆𝐻𝑟𝑥𝑛) = -85.78 𝑘𝐽/𝑚𝑜𝑙 (Determined experimentally)
CAS = concentration at pellet surface taken as bulk concentration = 4 kmol/m3
CAC = concentration at catalyst center = 0
𝜆𝑒𝑓𝑓 is the effective thermal conductivity = 2.988 W/mK (determined in Appendix B3)
𝐷𝑒𝑓𝑓 is the effective mass diffusivity = 4.61 × 10−11𝑚2𝑠−1 (determined in Appendix B1)
∆𝑇𝑚𝑎𝑥, 𝑝𝑎𝑟𝑡𝑖𝑐𝑙𝑒 =𝐷𝑒𝑓𝑓×(𝐶𝐴,𝑆−𝐶𝐴𝐶)×(∆𝐻𝑟𝑥𝑛)
𝜆𝑒𝑓𝑓 =
4.61×10−11𝑚2
𝑠×(4−0)×1000×85.78 𝑘𝐽/𝑚𝑜𝑙
2.988 𝑊/𝑚𝐾×10−3
∆𝑇𝑚𝑎𝑥, 𝑝𝑎𝑟𝑡𝑖𝑐𝑙𝑒= 5.29 × 10−3 K
208
Appendix B6: Determination of external film heat transfer resistance
∆𝑇𝑚𝑎𝑥,𝑓𝑖𝑙𝑚 = 𝐿 ×(−𝑟𝐴,𝑜𝑏𝑠)×(∆𝐻𝑟𝑥𝑛)
ℎ
Where ∆𝑇𝑚𝑎𝑥,𝑓𝑖𝑙𝑚 = the upper limit of temperature difference between the gas and the
catalyst
L = characteristic length = 𝑅𝐶
3 =
2.0 ×10−3m
3 = 6.667 × 10−4𝑚
(∆𝐻𝑟𝑥𝑛) = -85.78 𝑘𝐽/𝑚𝑜𝑙
𝑟𝑜𝑏𝑠 = observed rate of reaction = 3.451 × 10−7k𝑚𝑜𝑙/𝑘𝑔 𝑐𝑎𝑡 . 𝑠 at 40oC and 150g
𝜌𝑏= catalyst bulk density = 0.15 kg/0.00218 m3 = 68.8 kg/m3
Converting from k𝑚𝑜𝑙/𝑘𝑔 𝑐𝑎𝑡 . 𝑠 to 𝑚𝑜𝑙/𝑚3𝑠 gives:
𝑟𝑜𝑏𝑠 = 3.451 × 10−7𝑘𝑚𝑜𝑙/𝑘𝑔 𝑐𝑎𝑡 . 𝑠 × 𝜌𝑏 = 3.451×10−7𝑘𝑚𝑜𝑙
𝑘𝑔 𝑐𝑎𝑡 . 𝑠 × 68.8 𝑘𝑔/𝑚3 =
4.704 × 10−5 𝑘𝑚𝑜𝑙/𝑚3𝑠
ℎ − heat transfer coefficient = 1.40 × 10−1 𝑘𝐽
𝑚2𝑠𝐾
∆𝑇𝑚𝑎𝑥,𝑓𝑖𝑙𝑚 = 6.667×10−4 𝑚×(4.704×10−5𝑘𝑚𝑜𝑙/𝑚3𝑠)×(85.78𝑘𝐽/𝑚𝑜𝑙)
1.40×10−1 𝑘𝐽
𝑚2𝑠𝐾
= 1.92 × 10−2K
209
Appendix B7: Determination of Mears Criteria for heat transport limitation
The Mears Criteria for heat transport limitation is calculated as:
𝑟𝑜𝑏𝑠𝜌𝑏𝑅𝑐𝐸(∆𝐻𝑟𝑥𝑛)
ℎ𝑇2𝑅< 0.15
[Data taken from experimental run at 313 K and 150 g].
Where 𝑟𝑜𝑏𝑠 = observed rate of reaction = 3.451 × 10−7k𝑚𝑜𝑙/𝑘𝑔 𝑐𝑎𝑡 . 𝑠
E = Activation Energy = 3.39 × 104𝐽/𝑚𝑜𝑙
(∆𝐻𝑟𝑥𝑛) = Heat of reaction = -85.78 𝑘𝐽/𝑚𝑜𝑙
T = Temperature = 40oC = 313 K
𝜌𝑏= catalyst bulk density = 0.15 kg/0.00218 m3 = 68.8 kg/m3
𝑅𝑐 = radius of catalyst = 2.0 × 10−3m
h = heat transfer coefficient = 1.40 × 10−1 𝑘𝐽
𝑚2𝑠𝐾
R = molar gas constant = 8.314 J/molK
𝑟𝑜𝑏𝑠𝜌𝑏𝑅𝑐𝐸(∆𝐻𝑟𝑥𝑛)
ℎ𝑇2𝑅
=3.451 ×10−7k𝑚𝑜𝑙/𝑘𝑔 𝑐𝑎𝑡 . 𝑠×68.8 kg/m3×2.0 ×10−3m×3.39 ×104𝐽/𝑚𝑜𝑙×85.78 𝑘𝐽/𝑚𝑜𝑙
1.40×10−1 𝑘𝐽
𝑚2𝑠𝐾×3132×8.314 J/molK
= 1.21× 10−3
Hence, the L.H.S = 1.21× 10−3 < 0.15
210
Appendix B8: Determination of Weisz-Prater Criterion for internal mass diffusion
The Weisz-Prater Criterion for internal mass diffusion is calculated as:
𝐶𝑤𝑝,𝑖𝑝𝑑 =−𝑟𝐴,𝑜𝑏𝑠×𝜌𝑐×𝑅𝑐
2
𝐷𝑒𝑓𝑓×𝐶𝐴,𝑠
[Data taken from experimental run at 313 K and 150 g].
𝑟𝑜𝑏𝑠 = observed rate of reaction = 3.451 × 10−7k𝑚𝑜𝑙/𝑘𝑔 𝑐𝑎𝑡 . 𝑠
𝜌𝑐 = 𝜌𝑏
ε𝑝 =
68.8
0.5049= 136.2 𝑘𝑔/𝑚3
𝑅𝑐 = 2.0 × 10−3m
𝐷𝑒𝑓𝑓 = 4.61 × 10−11 𝑚2
𝑠(determined already)
CAS = concentration of reactant A on the catalyst surface = Concentration in the liquid
bulk (CA,b) = 4 kmol/m3 (This is due to the absence of external film resistance. Hence, the
concentration in the bulk liquid and on catalyst surface are assumed to be equal).
Therefore:
𝐶𝑤𝑝,𝑖𝑝𝑑 =3.451 ×10−7k𝑚𝑜𝑙/𝑘𝑔 𝑐𝑎𝑡 . 𝑠×136.2 𝑘𝑔/𝑚3×(2.0 ×10−3)
2𝑚2
4.61×10−11𝑚2
𝑠×4 kmol/m3
= 0.515 < 1
Since 𝐶𝑤𝑝,𝑖𝑝𝑑 < 1, there is no resistance to internal pore diffusion
211
Appendix B9: Determination of External film diffusion limitation
The external film diffusion limitation calculation is adopted from Levenspiel (1999).
𝑜𝑏𝑠𝑒𝑟𝑣𝑒𝑑 𝑟𝑎𝑡𝑒
𝑟𝑎𝑡𝑒 𝑖𝑓 𝑓𝑖𝑙𝑚 𝑟𝑒𝑠𝑖𝑠𝑡𝑎𝑛𝑐𝑒 𝑐𝑜𝑛𝑡𝑟𝑜𝑙𝑠=
−𝑟𝐴,𝑜𝑏𝑠
𝐶𝐴,𝑏𝑘𝑐×
𝑑𝑝
6
Where:
𝑟𝑜𝑏𝑠 = observed rate of reaction = 4.704 × 10−5 𝑘𝑚𝑜𝑙/𝑚3𝑠
𝑑𝑝 = 4 𝑚𝑚 = 4.0 × 10−3𝑚
CA,b = bulk concentration = 4 kmol/m3
𝑘𝑐 = mass transfer coefficient = 2.62 × 10−7𝑚/𝑠 (calculation in Appendix B2)
Therefore:
−𝑟𝐴,𝑜𝑏𝑠
𝐶𝐴,𝑏𝑘𝑐×
𝑑𝑝
6=
4.704×10−2𝑚𝑜𝑙
𝑚3𝑠4 kmol
m3 ×2.62×
10−7𝑚
𝑠
×4.0 ×10−3𝑚
6 = 2.99 × 10−2 < 1
Since the observed rate is much less than the limiting mass transfer rate, this means there
is no mass transfer resistance in the film.
212
Appendix B10: Determination of Mears Criterion for External film diffusion
limitation
The Mears Criterion for external film diffusion limitation is calculated as:
𝑟𝑜𝑏𝑠×𝜌𝑏×𝑅𝑐×𝑛
𝑘𝑐×𝐶𝐴
[Data taken from experimental run at 313 K and 150 g].
𝑟𝑜𝑏𝑠 = observed rate of reaction = 3.451 × 10−7k𝑚𝑜𝑙/𝑘𝑔 𝑐𝑎𝑡 . 𝑠
Converting from k𝑚𝑜𝑙/𝑘𝑔 𝑐𝑎𝑡 . 𝑠 to 𝑚𝑜𝑙/𝑚3𝑠 gives:
𝑟𝑜𝑏𝑠 = 3.451 × 10−7𝑘𝑚𝑜𝑙/𝑘𝑔 𝑐𝑎𝑡 . 𝑠 × 𝜌𝑏 = 3.451×10−7𝑘𝑚𝑜𝑙
𝑘𝑔 𝑐𝑎𝑡 . 𝑠 × 68.8 𝑘𝑔/𝑚3 =
4.704 × 10−5 𝑘𝑚𝑜𝑙/𝑚3𝑠
𝜌𝑏 = 68.8 𝑘𝑔/𝑚3
𝑅𝑐 = 2.0 × 10−3m
𝑛 = 𝑜𝑣𝑒𝑟𝑎𝑙𝑙 𝑜𝑟𝑑𝑒𝑟 𝑜𝑓 𝑟𝑒𝑎𝑐𝑡𝑖𝑜𝑛 ≈ 2.6
CA = bulk liquid concentration = 4 kmol/m3
𝑘𝑐 = mass transfer coefficient = 2.62 × 10−7𝑚/𝑠 (calculation in Appendix B2)
Therefore
𝑟𝑜𝑏𝑠×𝜌𝑏×𝑅𝑐×𝑛
𝑘𝑐×𝐶𝐴 =
3.451 ×10−7k𝑚𝑜𝑙
𝑘𝑔 𝑐𝑎𝑡 . 𝑠 ×
68.8𝑘𝑔
𝑚3 ×2.0 ×10−3𝑚×2.6
2.62×10−7𝑚
𝑠×
4 kmol
m3
= 1.179 × 𝟏𝟎−𝟏
Since the left hand side is less than 0.15, we can conclude that there is no resistance to
external mass transfer for the system.
213
APPENDIX C: Calculation of experimental rate of reaction
Appendix C1: Rate of reaction based on volume of reactor
The experimental rate of reaction on volume basis were calculated using 2 methods (i) the
3-point differentiation formula (a numerical method) adopted from Fogler (1999) (ii)
Derivatives of 𝑋𝐶𝑂2 versus V/𝐹𝐴𝑜 curves which were generated using the Microsoft Excel
Solver Add-in software.
The numerical method is used in cases when the data points in the independent variable
(for this case V/𝐹𝐴𝑜) are evenly spaced.
A typical run for BEA/AMP at 30oC absorber inlet and 150 g HZSM-5 yielded the
following results
Point on
absorber
V/𝐹𝐴𝑜
(min.L/mol)
X Rate
(mol/L.min)×103
0 0 0 9.111
1 3.249527817 0.03289474 11.14
2 6.499055633 0.07236842 13.16
3 9.74858345 0.11184211 12.15
4 12.99811127 0.15131579 21.26
5 16.24763908 0.25657895 43.53
6 19.4971669 0.43421053 40.49
7 23.39063002 0.51973684 12.15
Based on the above data, the 3-point differentiation formulas are represented as:
214
Initial point: (𝑑𝑋
𝑑𝑉/𝐹𝐴𝑂)
(𝑉𝐹𝐴𝑂
⁄ )𝑂
= −3𝑋𝑜+4𝑋1−𝑋2
2∆(𝑉𝐹𝐴𝑂
⁄ )
Interior points: (𝑑𝑋
𝑑𝑉/𝐹𝐴𝑂)
(𝑉𝐹𝐴𝑂
⁄ )𝑖
= 1
2∆(𝑉𝐹𝐴𝑂
⁄ )[𝑋(𝑖+1) − 𝑋(𝑖−1)]
Last point: (𝑑𝑋
𝑑𝑉/𝐹𝐴𝑂)
(𝑉𝐹𝐴𝑂
⁄ )7
= 1
2∆(𝑉𝐹𝐴𝑂
⁄ )[𝑋5 − 4𝑋6 + 𝑋7]
As an example, the rate at point 1 can be calculated as:
(𝑑𝑋
𝑑𝑉/𝐹𝐴𝑂)
(𝑉𝐹𝐴𝑂
⁄ )𝑖
= 1
2∆(𝑉𝐹𝐴𝑂
⁄ )[𝑋(𝑖+1) − 𝑋(𝑖−1)]
= 1
2×3.2495[0.0724 − 0] = 11.14 × 10−3𝑚𝑜𝑙/𝐿. 𝑚𝑖𝑛
To obtain the overall rate of reaction, the logarithmic mean was used for every two
adjacent points until a final value was obtained. For instance, for points 1 and 2, the log-
mean rate was determined as:
𝑙𝑜𝑔 − 𝑚𝑒𝑎𝑛 𝑟𝑎𝑡𝑒, 𝑟𝑙.𝑚 =𝑟2−𝑟1
𝑙𝑛(𝑟2𝑟1
)=
13.16×10−3−11.14×10−3
𝑙𝑛(13.16×10−3
11.14×10−3) = 1.212 × 10−2𝑚𝑜𝑙/𝐿. 𝑚𝑖𝑛
The overall rate of reaction was thus obtained as 1.809 × 10−2𝑚𝑜𝑙/𝐿. 𝑚𝑖𝑛
Derivatives of 𝑋𝐶𝑂2 versus V/𝐹𝐴𝑜 curves
Another method used was the derivative of 𝑋𝐶𝑂2 versus V/𝐹𝐴𝑜 curves to which a
polynomial fit was used in determining the rate. The polynomial equation was then
differentiated with respect to V/𝐹𝐴𝑜 after which rates were determined at selected points
215
and a log-mean was used in obtaining the overall rate of reaction. A typical polynomial
curve fit is shown below:
Differentiating the 3rd degree polynomial equation gives:
= -3×10-6x2 + 0.0018x + 0.0018
After substituting V/𝐹𝐴𝑜 at various points and determining the overall rate of reaction using
the log-mean (just like in the first method), a value of 1.820 × 10−2𝑚𝑜𝑙/𝐿. 𝑚𝑖𝑛 is
obtained. The percent deviation between the rates from both methods is obtained as 0.61%.
Hence, any of the methods can be used to obtain experimental rates. However, for the
second method, care must be taken in selecting the order of polynomial as higher orders
can generate both positive and negative slopes which are a source of error in determining
the rates at various points.
y = -1E-06x3 + 0.0009x2 + 0.0018x + 0.0086R² = 0.9815
0
0.1
0.2
0.3
0.4
0.5
0.6
0 5 10 15 20 25
𝑋𝐶𝑂
2
V/𝐹𝐴𝑜 (min.L/mol)
216
Appendix C2: Rate of reaction based on weight of catalyst
The experimental rates were calculated using the method of Derivatives of 𝑋𝐶𝑂2 versus
𝑊/𝐹𝐴𝑜 curves. The curves were generated using Excel Solver Add-in Software. The plots
were fitted to logarithmic curves (Fig 4.3.3.2-1) of which the differential gave the rates of
reaction for each catalyst weight. A typical kinetic data showing the rate calculated from
experimental runs is shown in Table C2-1.
Table C2-1. Experimental runs at 30oC absorber inlet, 60 ml/min amine flowrate
catalyst weight,
W (g)
Conversion,
X
Inlet CO2
flowrate, FAO
(mol/min)
W/FAO
(min.g/mol)
Rate
(mol/g.min)
×10-4
50 0.562 0.0948 527.20 1.227
100 0.611 0.0952 1050.03 0.616
150 0.632 0.0965 1552.87 0.416
Appendix C3: Determination of exit flowrates
The rates of reaction at the exit of the reactor are based on the exit concentrations or
flowrates of reactants. As such, the exit flowrates of reactants were determined and were
fit to a power law model together with the reaction rates. The actual flowrates were
subtracted from the equilibrium flowrates to obtain the exit flowrates, FA and FB. The exit
gas side CO2 mole fraction at equilibrium was determined by performing a balance around
217
the reactor as shown in equation C.1. Table C3-1 shows the parameters in a typical run
which are used for the calculation.
Table C3-1. Typical experimental run data
Parameter Value
Lean loading, αL 0.33
Rich loading, αR 0.59
Equilibrium loading, αe 0.62
Inlet CO2 gas concentration, y1 15%
Amine volumetric flowrate, �̇� 60 ml/min
Gas flowrate, FG 15 slpm
Amine concentration, CAM 4 mol/L (2:2)
The material balance is in the form:
𝐿′ (𝑥2
1−𝑥2) + 𝑉′ (
𝑦1
1−𝑦1) = 𝐿′ (
𝑥1
1−𝑥1) + 𝑉′ (
𝑦2
1−𝑦2) (C.1)
Where L’ – inert liquid (water) molar flowrate
V’ – inert gas (N2) molar flowrate
y1 – inlet CO2 composition in gas
218
y2 – exit CO2 composition in gas
x1 –exit CO2 composition in liquid
x2 – inlet CO2 composition in liquid
The liquid side CO2 compositions, x1 and x2 are determined from the lean and equilibrium
loadings respectively. Taking a basis of 1 L of solution:
Mass of BEA, m = number of moles, n × Molecular Weight, M.W
= 2 × 117.19 g/mol = 234.38 g
Mass of AMP = 2 × 89.14 g/mol = 178.28 g
𝑣𝑜𝑙𝑢𝑚𝑒 𝑜𝑓 𝐵𝐸𝐴 = 𝑚
𝜌=
234.38 𝑔
0.891 𝑔/𝑐𝑚3 = 263.05 𝑐𝑚3
𝑣𝑜𝑙𝑢𝑚𝑒 𝑜𝑓 𝐴𝑀𝑃 = 178.28 𝑔
0.934 𝑔/𝑐𝑚3 = 190.88 𝑐𝑚3
Hence, volume of water = 1000 – (263.05 + 190.88) = 546.07 cm3 = 546.07 g
Moles of water, n = 𝑚
𝑀.𝑊=
546.07𝑔
18 𝑔/𝑚𝑜𝑙= 30.34 𝑚𝑜𝑙𝑒𝑠
Moles of CO2 in lean solvent = Lean loading × Amine concentration
= 0.33 × 4 = 1.32 moles
Hence total moles of lean solvent = 4 + 30.34 + 1.32 = 35.66
Mol fraction of CO2 in lean solvent = inlet CO2 composition in liquid, x2 = 1.32
35.66= 0.037
Doing the same for x1 yields;
x1 = 0.0674
219
L’ = concentration of water × solvent volumetric flowrate
= 30.34 mol/L × 0.06 L/min = 1.8204 mol/min
V’ = 85% of total molar gas flowrate, since CO2 comprises 15% of total gas flowrate
Total volumetric gas flowrate, Gv = 15 slpm
Total molar gas flowrate, Gm = 𝑡𝑜𝑡𝑎𝑙 𝑣𝑜𝑙𝑢𝑚𝑒𝑡𝑟𝑖𝑐 𝑔𝑎𝑠 𝑓𝑙𝑜𝑤𝑟𝑎𝑡𝑒
𝑚𝑜𝑙𝑎𝑟 𝑣𝑜𝑙𝑢𝑚𝑒 𝑜𝑓 𝑔𝑎𝑠
= 15 𝐿/𝑚𝑖𝑛
24.46544 𝐿/𝑚𝑜𝑙= 0.613 mol/min
V’ = 0.85 × 0.613 mol/min = 0.521 mol/min
Substituting values into equation C.1 and solving for y2 gives:
1.8204 (0.037
1 − 0.037) + 0.521 (
0.15
1 − 0.15) = 1.8204 (
0.0674
1 − 0.0674) + 0.521 (
𝑦2
1 − 𝑦2)
y2 = 0.054
From this, the equilibrium molar flowrate is calculated as:
𝑚𝑜𝑙𝑒 𝑓𝑟𝑎𝑐𝑡𝑖𝑜𝑛 ×𝑡𝑜𝑡𝑎𝑙 𝑣𝑜𝑙𝑢𝑚𝑒𝑡𝑟𝑖𝑐 𝑔𝑎𝑠 𝑓𝑙𝑜𝑤𝑟𝑎𝑡𝑒
𝑚𝑜𝑙𝑎𝑟 𝑣𝑜𝑙𝑢𝑚𝑒 𝑜𝑓 𝑔𝑎𝑠=
0.054×15
24.46544= 0.0331𝑚𝑜𝑙/𝑚𝑖𝑛
Subtracting this equilibrium flowrate from the actual flowrate obtained at gas exit from
the experimental run gave an exit CO2 flowrate, FA = 0.0317 mol/min.
Exit amine flowrate (FB)
The exit amine (free amine) flowrate was determined based on the difference between the
equilibrium loading and rich loading. Using the data in Table C3-1;
220
𝐹𝐵 = �̇�𝐶𝐴𝑀(𝛼𝑒 − 𝛼𝑅)
= 60𝑚𝑙
𝑚𝑖𝑛×
1𝐿
10000𝑚𝑙× 4𝑚𝑜𝑙/𝐿(0.62 − 0.59)
𝐹𝐵 = 7.2 × 10−3𝑚𝑜𝑙/𝑚𝑖𝑛
221
APPENDIX D: Non-Linear Regression (NLREG) code for Power law model
A: Irreversible reaction
222
223
B: Reversible reaction
224
225
APPENDIX E1: Regression results for Conversion Correlation
226
APPENDIX E2: Regression results for Catalyst properties statistical analysis
227
APPENDIX F: Calculations for Preliminary Economic Analysis
Item Cost (CAD $)/gram
BEA 64.02
AMP 87.53
MEA 71.29
MDEA 47.12
Mg(OH)2 0.117
HZSM-5 0.13
KOH 0.972
Structured packing (Sulzer LDX) 372.83
Carbon tax 5×10-5
Cost of 1 gram of 1% K/MgO catalyst
Converting mol% to wt%:
1 mol% = 𝑀.𝑊. 𝑜𝑓 𝐾
(𝑚𝑜𝑙 𝑓𝑟𝑎𝑐𝑡𝑖𝑜𝑛×𝑀.𝑊 𝑜𝑓 𝐾)+(𝑚𝑜𝑙 𝑓𝑟𝑎𝑐𝑡𝑖𝑜𝑛×𝑀.𝑊 𝑜𝑓 𝑀𝑔𝑂)
= 39
(0.01 × 39) + (0.99 × 40.3)× 0.01 = 0.97 𝑤𝑡%
Hence weight of K = 0.0097 × 1𝑔 = 0.0097𝑔
Weight of MgO = 0.9903 × 1𝑔 = 0.9903 𝑔
228
For K;
KOH → K + OH
Moles of KOH = moles of K = 𝑚
𝑀𝑊=
0.0097
39= 2.487 × 10−4 𝑚𝑜𝑙𝑒𝑠
Hence weight of KOH required = 2.487 × 10−4 × 56.1 = 0.014 𝑔
For MgO;
Mg(OH)2 → MgO + H2O
Moles of Mg(OH)2 = moles of MgO = 0.9903
40.3044= 0.0246𝑚𝑜𝑙𝑒𝑠
Hence weight of Mg(OH)2 required = 0.0246 × 58.3197 = 1.433 𝑔
Therefore,
Cost of catalyst = [(0.117𝐶𝐴𝐷
𝑔× 1.433𝑔) + (0.972
𝐶𝐴𝐷
𝑔 × 0.014𝑔)] = 0.18 𝐶𝐴𝐷
Calculations on yearly basis
1 year = 365 days = 8760 hours
Carbon tax, (𝐶𝐴𝐷 $
𝑦𝑒𝑎𝑟)=
𝐶𝐴𝐷 $
𝑡𝑜𝑛𝑛𝑒×
1 𝑡𝑜𝑛𝑛𝑒
1000 𝑘𝑔× 𝐶𝑂2 𝑒𝑚𝑖𝑡𝑡𝑒𝑑 (
𝑘𝑔
ℎ𝑟) × 8760 ℎ𝑜𝑢𝑟𝑠
Cost of catalyst, (𝐶𝐴𝐷 $
𝑦𝑒𝑎𝑟) =
𝐶𝐴𝐷 $
𝑔× 𝑐𝑎𝑡𝑎𝑙𝑦𝑠𝑡 𝑤𝑒𝑖𝑔ℎ𝑡 (𝑔) × 2
Cost of solvent, (𝐶𝐴𝐷 $
𝑦𝑒𝑎𝑟) =
𝐶𝐴𝐷 $
𝑔× 𝑐𝑎𝑡𝑎𝑙𝑦𝑠𝑡 𝑤𝑒𝑖𝑔ℎ𝑡 (𝑔) × 2
Annual Cost = [𝑇𝑜𝑡𝑎𝑙 𝑐𝑜𝑠𝑡 (𝐶𝐴𝐷
$
𝑦𝑒𝑎𝑟)
𝐶𝑂2 𝑐𝑎𝑝𝑡𝑢𝑟𝑒𝑑 (𝑘𝑔
𝑦𝑒𝑎𝑟)]
229
230
Table F1. Breakdown of annual operating cost for different solvent systems
Cost (CAD $/yr)
System Reboiler duty (W) Steam
structured packing
Carbon tax HZSM-5 Solvent
Total cost
CO2 captured (kg/yr) Cost (CAD $)/kg CO2
MEA 144.17 99.30 6711 83.53 0 47.17 6940.99 433.01 16.03
MEA+HZSM-5 143.86 99.08 6711 77.18 39 47.17 6973.43 589.20 11.84
MEA+MDEA 167.64 115.46 6711 81.77 0 71.87 6980.11 508.34 13.73
MEA+MDEA+HZSM-5 164.14 113.05 6711 75.12 39 71.87 7010.04 699.49 10.02
BEA+AMP 251.17 173.00 6711 58.87 0 67.49 7010.35 910.46 7.70
BEA+AMP+HZSM-5 250.91 172.81 6711 48.71 39 67.49 7039.01 1163.62 6.05
231
Table F2. Breakdown of annual operating cost of BEA/AMP system for variation in process parameters
Cost (CAD $/year)
Parameter Condition Reboiler duty (W) Steam
Structured packing
Carbon tax K/MgO HZSM-5 Solvent
Total cost
CO2 captured (kg/yr)
Cost (CAD $)/kg CO2
Absorber Catalyst weight
(g)
0 306.56 211.14 6711 48.71 0 39 67.49 7077.34 1163.62 6.08
50 306.56 211.14 4847 43.23 18.13 39 67.49 5225.82 1243.56 4.20
100 306.56 211.14 4847 40.95 36.25 39 67.49 5241.67 1374.02 3.81
150 306.56 211.14 4847 38.76 54.38 39 67.49 5257.61 1443.42 3.64
170 306.56 211.14 4847 37.41 61.63 39 67.49 5263.50 1452.33 3.62
Desorber bed temperature (oC)
75 222.22 153.05 6711 82.52 0 39 67.49 7053.07 610.68 11.55
85 306.56 211.14 6711 48.71 0 39 67.49 7077.34 1163.62 6.08
95 347.22 239.15 6711 41.61 0 39 67.49 7098.25 1385.97 5.12
Solvent Flowrate (ml/min)
50 214.03 147.41 6711 74.28 0 39 67.49 7039.19 740.21 9.51
60 306.56 211.14 6711 48.71 0 39 67.49 7077.34 1163.62 6.08
70 383.33 264.02 6711 47.13 0 39 67.49 7128.64 1295.37 5.50
Solvent concentration (mol/L AMP)
1 517.45 356.39 6711 71.09 0 39 64.48 7241.96 777.22 9.32
1.5 419.73 289.09 6711 65.04 0 39 65.23 7169.36 888.26 8.07
2 306.40 211.03 6711 48.71 0 39 67.49 7077.23 1163.62 6.08
2.5 232.50 160.13 6711 42.35 0 39 66.72 7019.21 1278.72 5.49
Amine inlet temperature (oC)
20 347.22 239.15 6711 44.50 0 39 67.49 7101.14 1276.87 5.56
30 306.56 211.14 6711 48.71 0 39 67.49 7077.34 1163.62 6.08
40 265.89 183.13 6711 74.85 0 39 67.49 7075.48 610.68 11.59
gas flowrate (slpm)
10 306.56 211.14 6711 45.81 0 39 67.49 7074.45 1165.84 6.07
15 306.56 211.14 6711 48.71 0 39 67.49 7077.34 1243.56 5.69
20 306.56 211.14 6711 42.35 0 39 67.49 7070.99 1332.38 5.31
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