Post-combustion CO 2 capturing by KOH solution: An experimental and statistical optimization modeling study

Abstract

A pilot-scale bubble column contactor has been utilized for carbon dioxide chemisorption from simulated flue gas in the temperature range 30°C to 50°C. The influence of the most important operating parameters has been investigated. A total of 25 experiments were designed using the response surface methodology (RSM) and were then carried out in the bubble contact column. The results revealed that the liquid volume in the column, the alkaline concentration, and the temperature had a positive effect, while the gas hold-up had a negative effect on the CO₂ removal efficiency. A statistical model has been developed using the RSM D-optimal experimental design method. To achieve the highest CO₂ chemisorption, several operating conditions have been optimized. The model predicted that the maximum percentage of carbon dioxide removal would be 86.64%, and under the same operating conditions the experimental removal efficiency was 87.12%.

Keywords

green-house gas capture efficiency 86%KOH solution chemisorption bubble column contactor

Introduction

Carbon dioxide is considered the main and the most abundant greenhouse gas, with its emissions substantially escalating every year.¹ Consequently, climate change, global warming, acid rain, human and other species health issues result from rising greenhouse gas concentrations in the atmosphere.² Effective processes capable of reducing carbon dioxide emissions such as CCS (CO₂ Capture and Storage) to achieve the Kyoto Protocols must be applied as preventative measures to mitigate excessive emissions.¹ CCS is “the process involving the separation of carbon dioxide from industrial sources, its transportation to storage sites, and finally, its long-term maintenance”.³

The technologies used to capture carbon dioxide include various chemical and physical adsorption, unit operations including absorption,^4,5 adsorption,^6–9 algal sequestration,^10,11 membrane separation,^12,13 cooling distillation,¹⁴ and chemical absorption.^15,16 One of the classical techniques involves calcium looping based on the application of calcium oxide.¹⁷ In recent years extensive research has been carried out developing and testing a wide range of adsorbent materials for CO₂ capture^18,19 and ranging from adsorbents derived from waste materials²⁰ to more sophisticated graphene-based adsorbent materials.²¹ Several other adsorbents have been tested including biochars,²² activated carbon,²³ metal organic frameworks,²⁴ MOFs, and nanomaterials.²⁵ More recently, hybrid systems are being developed^26,27 and processed to comply with real sustainability and meet the concept of a circular economy. The physical absorption of carbon dioxide is evaluated using Henry's law in which CO₂ absorbed under high pressure and low temperatures, is released by decreasing the system pressure and raising the temperature. In this method, carbon dioxide can be absorbed without engaging in any chemical reaction.^28,29 Whereas chemical absorption consists of reacting carbon dioxide and a chemical solvent to form a weak cationic intermediate compound. This separation method has a relatively high yield in terms of the carbon dioxide captured, and the solvent is usually recovered for reuse by applying heat.³⁰

One of the most significant concerns in the chemical absorption process is the selection of a suitable solvent. The solvents traditionally used in chemical absorption can be divided into organic and inorganic groups, each of which has advantages and limitations. Organic solvents mainly include ammonia,^14,31,32 amine salts,^33,34 amines, e.g., monoethanolamine (MEA), diethanolamine (DEA), and methyldiethanolamine (MDEA)^28,35,36 and amino acids, e.g., L-alanine, taurine and sarcosine.³⁷ Donaldson and Nguyen¹³ examined the reaction between the first, second and third types of amines with carbon dioxide and showed that triethylamine had less catalytic activity and acted as a weak base producing free OH. Sakwattanapong et al.³⁰ explained the limitations of utilizing amines for CO₂ capturing as a function of the reboiler heat duty (RHD) and showed that MEA required the highest RHD, followed by DEA and MDEA. Song et al.³⁸ studied the CO₂ absorption-desorption cycles into-and-from the aqueous potassium salts of sixteen amino acids and found that the net cycle capacity and faster CO₂ desorption rates were functions of the intermolecular distance between the amino functional group, the carboxyl groups and the bulkier substituted ones.

The most common inorganic solvents for CO₂ capturing are alkaline solutions such as ammonia, potassium carbonate, potassium hydroxide and others to a lesser extent. Qin et al.³¹ used ammonia as the carbon dioxide absorbent and achieved a higher CO₂ absorption rate along with increasing ammonia concentration and temperature. Experiments proved that the CO₂ reaction with ammonia and water was much slower than some amine systems such as MEA, piperazine (PZ) and diethylenetriamine (DETA). The study by Puxty et al.³² on ammonia as a chemical absorbent of carbon dioxide lead to the higher adsorption capacity and lower adsorption rate compared to those of MEA. Herskowits et al.³⁹ applied sodium hydroxide solutions to capture carbon dioxide in a two-phase impinging jet absorber. Knuutila et al.⁴⁰ proved that the low solubility of the alkaline salts in water caused more limitations to mass transfer and subsequently a lower reaction rate; which is one of the debatable points against utilizing these types of solvents. Peng et al.⁴ compared the absorption performance of amine solution, ammonia solution and, alkali solution as three common types of absorbents in terms of system corrosion, absorbent renewability, capturing efficiency, operating cost and, CO₂ absorption capacity. Whereas the bubble column is one of the essential reactors for slurry (liquid-gas-solid) reactions, it is used for the chemisorption processes. The simple structure, high heat and mass transfer rates, low maintenance cost, and high efficiency suggested these three-phase reactors were the most important ones both on industrial and the laboratory scales. Chen et al.⁴¹ found that gas bubble size and distribution were intensively affected during the physiochemical absorption of carbon dioxide in alkaline solution. Li et al.⁴² investigated CO₂ chemisorption by Mg(OH)₂ solution in the bubble reactor column. To study the absorption performance, they evaluated several determining operating parameters, which included the concentration of the alkaline solution, the inlet gas flow velocity, and the operating temperature. Han et al.⁴³ captured the CO₂ by Ca(OH)₂ solution in a Pyrex reactor and this study revealed that the CO₂ absorption capacity of the absorbent decreased by increasing the concentration of calcium hydroxide. Darmana et al.⁴⁴ proposed a 2-D mathematical model by taking into account the full evolution of the hydrodynamics and all chemical components involved in the reaction of CO₂ with the alkaline NaOH solution in the bubble column reactor.

Chen et al.⁴¹ utilized sodium hydroxide solution in a bubble column reactor for CO₂ chemisorption. Moreover, a Taguchi experimental design method was used to acquire the optimized conditions for the pH of the solution, gas flow rate, liquid flow rate, and temperature. Whereas K₂CO₃/KHCO₃ like Na₂CO₃/NaHCO₃ could capture CO₂ in the low-temperature range (125°C–225°C) even if the CO₂ gas pressures were in the range of 0.1 bar to 30 bar in the post-combustion to pre-combustion zones.⁴⁵ Consequently, in the present study, a pilot bubble column reactor has been utilized for the chemisorption of carbon dioxide by KOH solution. One of the major concerns in using KOH for CO₂ capturing was the more promising aspects of potassium carbonate production in comparison with sodium carbonate–from NaOH absorption.⁴⁶ Furthermore, the produced K₂CO₃ and KHCO₃ could be used as a dry fire-fighting agent and fertilizer, respectively. The novelty of this work lies in using a pilot-scale slurry reactor and proving its long-term feasibility to absorb CO₂ from simulated flue gas. The effect of operating parameters, including the alkaline concentration in the column, CO₂ gas hold-up, operating temperature, and the liquid volume considering the carbon dioxide capturing efficiency have been investigated.

Statistical modeling

Response surface methodology (RSM) optimisation

The experimental design is by the RSM-D-Optimal method to study the influence of the operating parameters on the CO₂ capturing yield. Moreover, a quadratic polynomial regression model was developed to forecast the interactions of the various parameters on the CO₂ chemisorption as follows:

Y = β_{0} + \sum β_{i} x_{i} + \sum β_{i i} x_{i}^{2} + \sum β_{i j} x_{i} x_{j}

(1)

where β_i, β_ii, and β_ij are the linear, square, and interaction regression coefficients, respectively, and x_i and x_j are the independent variables.

The statistical significance of the variable parameters can be assessed using the analysis of variance statistical package (ANOVA). Moreover, the suitability of the model can be examined by the lack of fit analysis and the determination coefficient value R².

CO₂ chemisorption theory

The chemisorption theory of gases indicates several sequential physical/chemical steps. It commences with physical absorption of the gas (CO₂ in this study) in the liquid (the alkaline solution in the present study)^46–49 shown in equation (2):

{CO}_{2} (g) \to {CO}_{2} (aq)

(2)

Because of the high KOH alkalinity, it completely ionizes in pure water. Therefore, aqueous carbon dioxide undergoes chemical reaction with OH⁻ and forms the products, bicarbonates, HCO₃⁻(aq), and carbonates, CO₃⁻²(aq) according to the following reactions in equations (3) and (4):

{CO}_{2} (aq) + {OH}^{-} (aq) \leftrightarrow {HCO}_{3}^{-} (aq)

(3)

{HCO}_{3}^{-} (aq) + {OH}^{-} (aq) \leftrightarrow {CO}_{3}^{- 2} (aq)

(4)

In this system, all reactions are reversible and exothermic. Zhao et al.⁴⁵ concluded that at low temperature and high carbon dioxide concentration, the most stable phase is MHCO_3, and it is converted to M₂CO₃ at high temperature with the uptake of more CO₂. When the aqueous CO₂ produced in the solution reacts with OH⁻, then the solution pH level suddenly decreases at a very fast reaction time. The produced carbonate level reduces, and the bicarbonate concentration is enhanced at low solution pH values.

Materials and methods

In this study, a slurry bubble column reactor with a height of 2.57 m and an inner diameter of 15 cm along with a gas distributor with 98 pores with a size of 4–5 µm at the bottom of the column used. The column is equipped with a temperature thermocouple and the concentration of carbon dioxide at the inlet gas flow is balanced with nitrogen. The inlet gas flow rate was controlled in the range of 1–3 L/min to obtain a gas hold-up of 1–4 cm in the column. The CO₂ concentration of the outlet gas was measured by a carbon dioxide detector manufactured by Kimo Company, France, model AQ 110, and was determined at specified time intervals. The process schematic of the CO₂ absorption pilot plant using KOH is presented in Figure 1 showing the slurry bubble column, the gas sparger and the CO₂ and nitrogen cylinders.

Figure 1.

Process schematic of the CO₂ absorption pilot plant using KOH.

Design of experiment

The impact of effective parameters including the volume of the alkaline solution inside the column, gas hold-up (in terms of increasing height inside the tower), the KOH solution concentration and operating temperature have been investigated. The experimental conditions are summarized in Table 1.

Table 1.

Range of operating parameters in the present study.

Parameter	Min.	Max.
Potassium Hydroxide Concentration (mol/L), C₀	0.005	0.01
Gas hold-up (cm), H	1	4
Temperature (°C), T	30	50
Liquid volume (L), V	15	25

The experiments were designed based on Design-Expert program 8.0.5 trial version. Table 2 presents the values of the independent numerical variables for every run in the present study.

Table 2.

Experimental design based on RSM-D-optimal method.

Run	A: solution volume, L)	B: alkaline concentration C₀ (mol/L)	C: gas hold up H (cm)	D: Temperature T (°C)	CO₂ removal efficiency, %E (%)
1	15	0.0050	4.0	50	71.2
2	25	0.0075	1.0	30	80.1
3	15	0.0050	2.5	30	68.1
4	25	0.0100	1.0	50	86.6
5	25	0.0100	4.0	50	83.0
6	25	0.0050	4.0	30	80.0
7	20	0.0050	1.0	30	72.5
8	15	0.0075	2.5	40	72.1
9	20	0.0050	2.5	40	74.5
10	25	0.0050	4.0	30	74.6
11	15	0.0075	1.0	50	77.5
12	15	0.0050	1.0	40	72.6
13	15	0.0100	1.0	30	74.4
14	25	0.0050	2.5	50	81.0
15	25	0.0100	2.5	30	80.2
16	20	0.0075	14.0	50	76.0
17	25	0.0050	1.0	40	80.6
18	20	0.0075	4.0	40	74.5
19	15	0.0100	2.5	50	77.3
20	25	0.0100	1.0	50	87.12
21	20	0.0050	1.0	50	79.4
22	15	0.0100	4.0	30	69.4
23	20	0.0100	2.5	50	71.2
24	25	0.0075	2.5	40	79.5
25	20	0.0075	4.0	30	68.5

The CO₂ removal efficiencies were determined based on the following equation at the end of the 30 min column operation:

E (%) = \frac{C_{in, C O_{2}} - C_{out, {CO}_{2}}}{C_{in, C O_{2}}} \times 100

(5)

Results & discussion

To study the chemical and physical absorption processes for CO₂ removal in the bubble column reactor, the effect of process operating parameters including the concentration of the alkaline solution, gas hold-up, volume of fluid inside the tower and operating temperature have been investigated.

Effect of the alkali concentration on the CO₂ removal efficiency

The absorption efficiency of CO₂ increases as the concentration of the KOH solution, C_o, increases. The general trend is shown in Figure 2 the model curve showing the trend in how the CO₂ removal efficiency increases with increasing alkali solution concentration. The experimental design of experiment (DOE) point relating to increasing C₀ is presented.

Figure 2.

Effect of the alkali solution concentration, B:C₀, on the CO₂ removal efficiency, %E, predicted by DOE software model. Fixed conditions: V =20 L; H=2.5 cm; T=40°C.

The DOE point relating to increasing C₀ is presented.

However, improving the absorption efficiency by increasing the concentration of the chemical solution is not a definite prospect, since it also relies on other kinetic factors such as reversible equilibrium and the mass transfer process in the gas-liquid reaction phase. Regarding the chemical dynamics, increasing the alkaline concentration causes the reaction (equation 2) to move in the right direction, which improves the reaction rate and elevates the CO₂ absorption efficiency. In Figure 3, the influence of alkaline solution concentration is illustrated for one set of fixed conditions, namely, V = 20 L; H = 2.5 cm; T = 40°C.

Figure 3.

CO₂ removal efficiency (%E) with alkali concentration (T = 30°C, liquid volume = 15 L).

The figure shows the effect of alkali concentration on the CO₂ removal efficiency at three hold-up values of 1.0, 2.5 and 4.0 cm and their removal efficiency values at a liquid volume of 15 L and a temperature of 30°C. The points surrounded by a circle are the experimental data values and the remaining points are model generated values. Further correlations are shown in the Supplementary data file by Figures S1 and S2 for the effect of alkaline solution concentration data values at 40°C and 50°C, respectively.

Effect of the gas hold-up on CO₂ removal efficiency

In the present investigation, the effect of gas flow rate on CO₂ chemisorption removal has been examined by controlling the gas hold-up in terms of the liquid volume rising in the column. The single experimental point for the data in Figure 4 is shown on the solid line model plot and the two outliers are the +/−5% limits. The fixed conditions for the model output in Figure 4 are C₀ = 0.0075 mol/L; V = 20 L; T = 40°C.

Figure 4.

The effect of gas hold-up, H, on the CO₂ removal efficiency, %E, predicted by DOE software model. Fixed conditions: V = 20 L, C₀ = 0.0075 mol/L; T = 40°C.

As seen in Figure 5, by increasing gas hold-up from 1cm to 4cm, the removal efficiency of CO₂ was decreased. The higher gas hold-up leads to a decrease in the residence time of reactants in the column. The results suggest that chemical reaction was a more critical step in the CO₂ capturing process and carbon dioxide solubility in water, as well as KOH ionization, but were not rate or capacity limiting steps for CO₂ chemisorption.

Figure 5.

CO₂ removal efficiency (%E) with alkali concentration (T = 50°C, Liquid volume = 20 L).

Further, correlations are shown in the Supplementary data file by Figures S3 and S4 for the hold-up data values at 30°C and 40°C respectively. As seen in the figures, by increasing gas hold-up from 1 cm to 4 cm, the removal efficiency of CO₂ was decreased at all temperatures.

Effect of operating temperature on the CO₂ removal efficiency

To study the influence of parameters on the adsorption performance, the experiments took place at three different temperatures of 30, 40, and 50°C. The results showed that increasing the temperature was an effective way to improve the absorption efficiency as represented by Figure 6.

Figure 6.

Effect of temperature, T, on the CO₂ removal efficiency, %E, predicted by DOE software model. Fixed conditions: V =20 L; C0 = 0.0075mol/L; H = 2.5cm.

As the temperature increased, the dissolution rate of KOH and the chemical reaction rate increased, but the physical absorption of CO₂ in solution decreased. This stage of the project revealed that the chemical reaction is more effective than physical absorption process of CO₂ in the alkaline solution.

The fixed conditions for this study in Figure 6 were C₀ = 0.0075 mol/L; H = 2.5 cm; V = 20 L. The effect of the three temperatures on the removal of CO₂ and alkali concentration is shown in Figure 7.

Figure 7.

Effect of alkali concentration, C₀ (mol/L) on CO₂ removal efficiency (%E) with different temperatures V = 20; H = 2.5 cm.

As expected from the model output there is an increase in efficiency with increasing temperature. The figure does suggest that there is a fractional difference in the removal efficiencies going from 30°C to 40°C and then from 40°C to 50°C. The relative removal efficiencies appear to decrease in the higher temperature range. This may be due to an increase in the rate of the reversible reaction 2. Two other sets of results showing the influence of temperature are presented in Figure S5 and S6 in the Supplementary information.

Effect of fluid volume on the CO₂ removal efficiency

To evaluate this parameter, liquid amounts of 15, 20, and 25 L were examined. It was found that as the fluid volume rises, the gas hold-up time in the column is increased, causing a faster chemical reaction and a better absorption performance.

The increasing trend in % removal efficiency with increasing solution volume predicted by the model is shown in Figure 8 under the fixed conditions: C₀ = 0.0075 mol/L; H = 2.5 cm; T = 40°C.

Figure 8.

Effect of the fluid volume parameter on the CO₂ removal efficiency, %E, predicted by DOE software model. Fixed Conditions: C₀ = 0.0075 mol/L; H = 2.5 cm; T = 40°C.

The effect of the liquid volume variation on the removal of CO₂ and temperature is shown in Figure 9. As expected from the model output there is an increase in efficiency with increasing liquid volume. The figure shows the three temperature plots at the three volumes and the relationship with volume looks almost linear – the volume differences in both cases – from 15 L to 20 L and then from 20 L to 25 L are both 5 L suggesting a close to linear dependence on volume. The fixed conditions are C₀= 0.0075 mol/L. H = 2.5 cm. One other set of results showing the effect of different volumes on the removal efficiency is presented in Figure S7 in the Supplementary information under conditions: C₀ = 0.0050 mol/L; H = 1.0 cm. Another other set of results showing the effect of alkali concentration on the removal efficiency is presented in Figure S8 in the Supplementary information under conditions: T = 50°C; V = 25 L.

Figure 9.

CO₂ removal efficiency (%E) with temperature at different liquid volumes (C₀ = 0.0075 mol/L, H = 2.5 cm).

The effect of the volume variation on the removal of CO₂ and temperature is shown in Figure 9. As expected from the model output there is an increase in efficiency with increasing liquid volume. The figure shows the three temperature plots at the three volumes and the relationship with volume looks quite linear – the volume differences in both cases – from 15 L to 20 L and then from 20 L to 25 L are both 5 L suggesting a linear dependence on volume. The fixed conditions are C₀= 0.0075 mol/L. H = 2.5 cm. One other set of results showing the effect of different volumes on the removal efficiency is presented in Figure S7 in the Supplementary information under conditions: C₀ = 0.0050 mol/L; H = 1.0 cm. Another other set of results showing the effect of alkali concentration on the removal efficiency is presented in Figure S8 in the Supplementary information under conditions: T = 50°C; V = 25 L.

Statistical modeling

Development of the quadratic equation

A quadratic equation has been developed to investigate the influence of operating parameters on the CO₂ absorption process. The equation enables us to predict the effect of the parameters either individually or in terms of their interaction with one another. The negative coefficients indicate the decreasing effect of the parameters on the removal of carbon dioxide, and the positive ones indicate the positive effect. The general form of the equation is expressed as:

\begin{aligned} % {CO}_{2} removal = & 75.94 + 4.07 V + 2 C_{0} - 1.68 H \\ + 2.92 T + 0.1997 (V \times H) + 0.302 (C_{0} \times H) \\ + 0.3810 (T \times H) + 0.4082 {(H)}^{2} + 0.5082 T^{2} \end{aligned}

(6)

The negative coefficient values indicate the negative effect on carbon dioxide removal efficiency. The suitability of the model was evaluated by an F-Value test and a P-Value test; the results are presented in Table 3. The F-Value was 138.7, and the P-Value obtained from the model was less than 0.0001. A P-Value of less than 0.05 indicates the suitability of the selected model for predicting the carbon dioxide removal yield.

Table 3.

ANOVA analysis results for the quadratic model.

Source	Sum of squares	Degree of freedom	Mean square	F-value	P-value
Model	650.3	10	72.25	138.7	<0.0001	Significant
A-V	329.2	1	329.2	632.0	<0.0001	Significant
B-C₀	71.71	1	71.71	137.7	<0.0001	Significant
H-hold up	48.40	1	48.40	92.91	<0.0001	Significant
D-T	152.5	1	152.5	292.8	<0.0001	Significant
AC	0.5609	1	0.5609	1.08	0.3159	Not Significant
BC	1.22	1	1.22	2.34	0.1466	Not Significant
CD	2.05	1	2.05	3.93	0.0661	Not Significant
C2	0.7661	1	0.7661	1.47	0.2440	Not Significant
D2	0.9339	1	0.9339	1.79	0.2005	Not Significant
Residual	7.81	14	0.5210
Lack of fit	2.80	9	0.2796	0.2786	0.9595	not Significant
Pure error	5.02	5	1.00
Cor total	658.1	24

The Adequate Precision tool determines the signal-to-noise ratio, and this ratio is above 4 and a precision fitting of 42.04, which indicates the presence of a suitable signal for the model. The agreement between the experimental data result values and the model predicted values are shown in Table 4 and comprise four terms, namely, the standard deviation, the adjusted R², the Predicted R² and the adequate precision values.

Table 4.

The modified regression terms for the model.

Parameters	Value
Std. Dev.	0.7218
Mean	76.29
C.V. %	0.9461
R²	0.9881
Adjusted R²	0.9810
Predicted R²	0.9654
Adeq Precision	42.024

Table 4 and Figure 10 illustrate that there is a satisfactory correlation for the experimental and the optimized models’ predicted data values of the CO₂ removal yield with a very high correlation value of R²= 0.9881.

Figure 10.

CO₂ removal percentage (actual vs. model prediction).

Table 5.

Potassium product species and applications.

Component	Appearance	Density (g/cm³)	Solubility in water at 20°C (g/100mL)	Uses
K₂CO₃	white solid	2.43	112	For soap, glass, and china production; mild drying agent; fire suppression
KHCO₃	white crystal	2.17	22.4	Reagent; adding in club soda to improve taste; buffering agent in medicines; additive in winemaking

Interaction effect of operating parameters on the CO₂ removal yield

The three-dimensional outputs presented in Figures 11 to 13 show the response level of the quadratic polynomial equation with consideration of two fixed and two variable parameters.

Figure 11.

The effect of interaction between gas hold-up and alkaline solution concentration parameters on the CO₂ removal efficiency.

Figure 12.

The effect of interaction between gas hold-up and fluid volume parameters on the CO₂ removal efficiency.

Figure 13.

The effect of interactions between operating temperature and gas hold-up parameters on the efficiency of CO₂ removal.

In these graphs, the effect of the gas hold-up, temperature, alkaline solution concentration, and fluid volume have been investigated. These results demonstrate that the percentage of CO₂ removal has increased in the case of a low gas hold-up. Moreover, the interactive effect of gas hold-up on the CO₂ removal yield was relatively small and could be neglected. For a change in operating conditions - with rising temperature, an increasing concentration of the alkaline solution, and increasing the volume of fluid in the column, the yield of CO₂ removal increased.

Experimental optimization

The empirical optimization of the process parameters in the pre-specified range was undertaken to achieve the maximum CO₂ removal. The optimization results showed that the maximum percentage of carbon dioxide removal is 86.64%, which was performed for the fluid volume equivalent to 2 5 L, 0.01 M concentration, a gas hold-up of 1 cm, and at a temperature of 50°C. This result is shown in Figure 14. Under these operating conditions, experiments conducted resulted in a CO₂ removal efficiency of 87.1%, and an error of 0.48% compared to the model value revealed the reliability of the driven model.

Figure 14.

The operating parameters are at the optimal point.

Product output opportunities

In this research, the major goal is to eliminate the CO₂ from the flue gas of an industrial stack. In this venue, no KOH recovery either exists or is in order. In other words, the KOH is dissociated into K⁺ and OH⁻ where the K⁺ interacts with the HCO³⁻ and CO₃⁻² so that KHCO₃ and K₂CO₃ shall precipitate. Thus, there are no KOH species to recover and the potential products and their applications from this CO₂ stripping process are shown in Table 5.

Moreover, with the change of dissolved CO₂ concentration in the solution as well as change of the solution temperature (i.e., exothermic reactions) different products are formed. Ultimately, since the inlet CO₂ concentration is kept high, the process most probably acts reversibly. It is noteworthy that, the irreversible signs indicated in equations (2) and (3) are for the precipitation interactions.

Conclusion

A bubble column reactor was successfully designed to investigate the effects of the process operating parameters, such as fluid volume inside the tower, gas hold up, alkaline solution concentration, and temperature for chemical/physical absorption of CO₂. The excellent correlation between the model prediction and the experimental results was presented in Figure 6. The optimal experimental conditions of CO₂ removal by an alkaline slurry of potassium hydroxide have been achieved. The design of the experimental approach was carried out using the RSM-D-Optimal method to predict optimal CO₂ removal conditions and investigate the interaction effects of the process operating parameters. The results proved that CO₂ removal efficiency was enhanced by increasing the volume of fluid in the column, increasing the concentration of absorbent and the temperature in the low gas hold-up region. Increasing the temperature improved the dissolution of KOH. The results of the optimization study were in excellent agreement with the experimental validation results.

On the other hand, carbonate sediments, which reduce the alkalinity of adsorbent, are subsequently created, and by increasing the concentration of the absorbent, the amount and rate of carbonate sedimentation also increased. The slurry in the tower became covered by sediment, which in turn, reduced the removal efficiency. With a rise in the volume of fluid inside the tower, the time of CO₂ gas storage in the slurry and, consequently, the chemical reaction rate increases. Thus, the removal efficiency is higher because the volume of fluid increases according to the capacity of the tower. On the other hand, changes in the gas hold-up do not have a significant effect on removal efficiencies. Investigating the amount of CO₂ converted to carbonate with the analysis of the residual fluid in the column is on the next agenda of this research team.

Supplemental Material

sj-docx-1-eae-10.1177_0958305X241230944 - Supplemental material for Post-combustion CO₂ capturing by KOH solution: An experimental and statistical optimization modeling study

Supplemental material, sj-docx-1-eae-10.1177_0958305X241230944 for Post-combustion CO₂ capturing by KOH solution: An experimental and statistical optimization modeling study by Shokooh Ghavamipour, Leila Vafajoo, Gilava Pourhossein, Prakash Parthasarathy and Gordon McKay in Energy & Environment

Footnotes

Declaration of conflicting interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The authors of this manuscript would like to express their gratitude to the INSF for partially funding this research work under contract number 98018784.

ORCID iD

Gordon McKay

Supplemental material

Supplemental material for this article is available online.

Correction (March 2024):

Second affiliation in this article has been updated.

Shokooh Ghavamipour holds an MSc degree in Chemical Engineering from Department of Chemical and Polymer Engineering at Islamic Azad University, South Tehran Branch in 2019. With a strong interest in carbon capture and utilization, she currently works as an expert at Green Technology Developers Company in Tehran, Iran, using her expertise to drive advancements in CO₂ capturing technologies.

Leila Vafajoo is an associate professor in Department of Chemical and Polymer Engineering at Islamic Azad University, South Tehran Branch. Her academic journey includes the completion of her BSc and MSc degrees at the distinguished Sharif University of Technology in 1994 and 1996, respectively. Subsequently, she earned her PhD from Amirkabir University of Technology (Tehran Polytechnique) in 2001. Her extensive research portfolio is dedicated to the development, characterization, and physiochemical evaluation of adsorbents and catalysts designed for CO₂ capturing, as well as the treatment of industrial wastewater. Moreover, her scholarly pursuits encompass the mathematical modeling of chemical and environmental processes, alongside the innovation of lab-on-chip pollutant detection systems. Her multidisciplinary work significantly contributes to addressing pressing global challenges in environmental sustainability and process engineering.

Gilava Pourhossein is a chemical engineer specializing in CO₂ capturing technology. She earned her MSc degree in Chemical Engineering from Department of Chemical and Polymer Engineering at Islamic Azad University, South Tehran Branch in 2019. Since 2018, she has been working as an expert at Green Technology Developers Company in Tehran, Iran, where she focuses on developing and implementing CO₂ capturing solutions.

Prakash Parthasarathy holds a PhD degree in Chemical Engineering. Since 2018, he has been a postdoctoral researcher at Hamad Bin Khalifa University (HBKU), Qatar Foundation (QF), Qatar. Previously, he worked as a postdoctoral researcher at Yonsei University in South Korea. Prior to entering the field of research, he was a lecturer at Sriram Engineering College, India, an energy engineer at the Confederation of Indian Industry (CII), India, a management trainee at ACC Cements, India, and a graduate engineer trainee at Shasun Chemicals and Drugs Limited, India. He is a member of the Research Board at Sultan Qaboos University in Oman. He has authored several books, book chapters, and up to 53 journal papers.

Gordon McKay has over 37 years' academic experience and 10 years in the process engineering industry. He served as reader at Queens University, UK; professor at Jordan University, Jordan; senior process specialist at AMEC-Foster Wheeler, Ireland; professor and head of Chemical and Biomolecular Engineering Department at Hong Kong University of Science and Technology, Hongkong. Currently, he holds the position of professor in the Division of Sustainable Development at Hamad Bin Khalifa University (HBKU), Qatar since 2015. His Scopus h-index is 105, and his Google Scholar h-index is 125. He has authored 630 research journal articles and has received a total of 88,500 citations as of date. He is the author of the second most cited article in Thomson-Reuters' Chemical Engineering category, with 18,143 citations.

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Supplementary Material

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Post-combustion CO 2 capturing by KOH solution: An experimental and statistical optimization modeling study

Abstract

Keywords

Introduction

Statistical modeling

Response surface methodology (RSM) optimisation

CO2 chemisorption theory

Materials and methods

Design of experiment

Results & discussion

Effect of the alkali concentration on the CO2 removal efficiency

Effect of the gas hold-up on CO2 removal efficiency

Effect of operating temperature on the CO2 removal efficiency

Effect of fluid volume on the CO2 removal efficiency

Statistical modeling

Development of the quadratic equation

Interaction effect of operating parameters on the CO2 removal yield

Experimental optimization

Product output opportunities

Conclusion

Supplemental Material

sj-docx-1-eae-10.1177_0958305X241230944 - Supplemental material for Post-combustion CO2 capturing by KOH solution: An experimental and statistical optimization modeling study

Footnotes

Declaration of conflicting interests

Funding

ORCID iD

Supplemental material

Correction (March 2024):

Appendix

References

Supplementary Material

CO₂ chemisorption theory

Effect of the alkali concentration on the CO₂ removal efficiency

Effect of the gas hold-up on CO₂ removal efficiency

Effect of operating temperature on the CO₂ removal efficiency

Effect of fluid volume on the CO₂ removal efficiency

Interaction effect of operating parameters on the CO₂ removal yield

sj-docx-1-eae-10.1177_0958305X241230944 - Supplemental material for Post-combustion CO₂ capturing by KOH solution: An experimental and statistical optimization modeling study