kinetic studies on catalyst-aided absorption and desorption …

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


Figure 4.25 Validation of temperature profile along desorber for 5M MEA by


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


Figure 4.28. CO2 absorption efficiency of MEA, MEA- MDEA and BEA-AMP with and


Figure 4.29. CO2 cyclic capacity of MEA, MEA- MDEA and BEA-AMP with and


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


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


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


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


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


this work

AAD = 0.45%

77

Figure 4.25 Validation of temperature profile along desorber for 5M MEA by


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)


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


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


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


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


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


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


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)


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


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)


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


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


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


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


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


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


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


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)


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


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


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)


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)


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 (%)


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


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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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


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


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


(𝑉𝐹𝐴𝑂

⁄ )𝑖

= 1


⁄ )[𝑋(𝑖+1) − 𝑋(𝑖−1)]

Last point: (𝑑𝑋


(𝑉𝐹𝐴𝑂

⁄ )7

= 1


⁄ )[𝑋5 − 4𝑋6 + 𝑋7]

As an example, the rate at point 1 can be calculated as:

(𝑑𝑋


(𝑉𝐹𝐴𝑂

⁄ )𝑖

= 1


⁄ )[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

223

B: Reversible reaction

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)]

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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