Optimization Study of CO 2 Gas Absorption with NaOH Absorbent Continuous System in Raschig Ring Packing Column Using Box–Behnken Design

: Increasing CO 2 gas emissions results in climate change by increasing air temperature and worsening environmental problems. It is necessary to control CO 2 gas in the air to overcome this. This research aims to optimize the absorption of CO 2 gas in the air with 0.1 M NaOH absorbent in the column of the Raschig ring stufﬁng material using the response surface methodology (RSM). This research was conducted using a continuous system of three independent variables by varying the contact time (10–80 min), the ﬂow rate of NaOH absorbent (2–5 L/min), and the ﬂow rate of CO 2 gas (1–5 L/min). The response variables in this study were the absorption rate (L/min) and mass transfer coefﬁcient, while the air ﬂow rate was constant at 20 L/min. Air and CO 2 gas mix before absorption occurs and ﬂow into the Raschig ring packing column so that contact occurs with the NaOH absorbent. Mass transfer of CO 2 gas occurs into the NaOH absorbent, resulting in absorption. The results showed that the effect of contact time (min), the ﬂow rate of NaOH absorbent (L/min), and CO 2 gas ﬂow rate individually and the interaction on CO 2 absorption rate and mass transfer coefﬁcient were very signiﬁcant at a p -value of 0.05. Chemical absorption of CO 2 also occurred due to the reaction between CO 2 and OH- to form CO 32 − and HCO 3 − , so the pH decreased, and the reaction was a function of pH. Optimization using Design Expert 13 RSM Box–Behnken Design (BBD) yielded optimal conditions at an absorption time of 80 min, NaOH absorbent ﬂow rate of 5 L/min, CO 2 gas ﬂow rate of 5 L/min, absorption rate of CO 2 gas of 3.97 L/min, and CO 2 gas mass transfer coefﬁcient of 1.443 mol/min m 2 atm, with the desirability of 0.999 ( ≈ 100%).


Introduction
Air pollution and climate change have become major challenges for sustainable development related to CO 2 emissions [1]. Environmental degradation caused by various human activities, especially CO 2 emissions, is responsible for many disasters around the world, such as prolonged droughts, fires, tsunamis, and floods [2]. Increased CO 2 emissions cause severe environmental problems, such as climate change and melting glaciers [3,4], and are predicted to continue to increase, reaching a peak in 2030 [5]. Various alternative ways of CO 2 control proposed for the development include converting CO 2 into chemicals [6,7]. They comprehensively explored the factors that contribute to CO 2 uptake by nanofluids, mainly addressing the role of base fluids and the reasons for their choice was reported by (Aghel et al., 2022) [8]. Utilization of CO 2 is for catalytic conversion [9], electrocatalytic

Materials
NaOH (Merck), HCl (Merck), phenolphthalein indicator, methyl orange, distilled water, and CO 2 gas in cylinders purchased by order from PT Aneka Gas in Medan City, North Sumatra Province, Indonesia.

Experimental
The equipment used included a filling absorption column consisting of a glass column, packing material (packing) Raschig ring type glass, absorbent pump, air compressor, regulator, and flow meter for absorption. CO 2 gas cylinders were used, complete with pressure regulators and supporting equipment, namely pH meters, Dosimat 632, beakers, measuring cups, and pipettes. The working method was changing the pressure drop (P) in dry and wet conditions; filling in flooded conditions; filling absorbed and non-absorbed gas in glass; and using chemical means by varying the flow rate of CO 2 gas and air, then mixing them. Two gas variations in the flow rate of 0.1 M NaOH absorbent, height, and diameter of the packing ring on a fixed column were used. The response variables were the absorption rate and mass contraction coefficient. The experimental design tested the effect of each variable, the effect of interaction, and optimization using Design Expert 13, Response Surface Methodology, Box-Behnken Design (RSM-BBD), and subtype random. A series of equipment using an absorption column was located in the Chemical Engineering Laboratory, Faculty of Engineering, Syiah Kuala University. The schematic procedure of the CO 2 gas absorption process using 0.1 M NaOH absorbent in the packing Raschig ring column is shown in Figure 1.

Calculation Principles Used
Y o is the mole fraction of CO 2 gas that is not absorbed; for the ideal gas fraction volume, it is the same as the mole fraction. From the incoming gas, the gas (air) flow rate enters (F 2 ), and the CO 2 flow rate enters (F 3 ) so that the mole fraction of gas entering [42]: If the Fa of CO 2 gas is absorbed (L/s), then From Equations (2) and (3), we obtain: To convert the absorbed CO 2 flow rate, Fa(L/s) to Ga(gmol/s) [43][44][45][46]:  [42,43] The overall mass transfer coefficient, which controls the rate at which reactants and products are moved between the gas and liquid phases, is a crucial metric to compute in the conversion of CO 2 . This parameter impacts the mass transit rate of CO 2 from the gas phase to the liquid phase and the rate of CO 2 absorption into a liquid solvent in the context of CO 2 conversion.
The general equation used for absorption is presented in Equation (6): where: Y * = the mole fraction of the gas in equilibrium with the liquid at some point in the column Y = bulk mole fraction A = column cross-sectional area H = height of the infill material in the column a = specific area of the stuffing material/unit volume of the stuffing material The right-hand side is difficult to determine, so it can be determined more thoroughly as follows: N = k og (a.A.H) log average driving force pressure drop [46][47][48][49][50].
where: N = absorption rate (gmol/s) A = column cross-sectional area H = column height AH = column volume a.A.H = mass transfer area So that: where: p i = partial pressure of incoming CO 2 gas p o = partial pressure of outgoing CO 2 gas

Determination of Absorption of CO 2 Based on Chemical Reactions
The CO 2 is absorbed by the standard NaOH solution, and the normality of the solution will be affected. A mixture of carbonates and bicarbonates can be determined by titration with standard acid solutions using phenolphthalein and methyl orange indicators. The carbonate ion is usually titrated as a base with a strong acid, resulting in a reaction as shown in Equations (8) and (9). In Table 3, ions formed at various temperatures are enumerated. Phenolphthalein has a pH range of 8.0 to 9.6, which is a suitable indicator for the first endpoint, while methyl orange has a pH range of 3.1 to 4.4, which is suitable for the second endpoint. Therefore, mixtures of carbonate and bicarbonate or carbonate and hydroxide can be titrated with standard HCl to both endpoints. Table 4 depicts the correlation between titration volume and carbonate titrations. Statistical design of experiments (DOE) is an effective method for devising experiments that, after data analysis, yield valid and objective conclusions. Two main applications of experimental setup were evaluated to identify the variables that affect the experiment and its optimum conditions [51]. The regression and graphical analysis of the data were performed using Design Expert 13.0.11.0 (Stat-Ease Inc., Minneapolis, MN, USA). The Box-Behnken design (BBD) is the most common RSM design. To obtain optimal levels of CO 2 gas absorption and mass transfer coefficient, RSM was used to analyze the response patterns and determine the optimal combination of variables expected to produce optimal conditions. This study involved three variables labeled X 1 (absorption time), X 2 (absorption flow rate of 0.1 M NaOH), and X 3 (absorption concentration) (CO 2 gas flow rate). This experiment's experimental design is outlined in Table 1. CO 2 is the absorption flow rate, and CO 2 is the gas mass transfer coefficient, denoted by Y 1 and Y 2 , respectively. The relationship between classified and actual variables is expressed as Equation (10) for statistical analysis.
where, x i represents the independent variable or its dimensionless value, X 1 is the independent real value, X 2 is the independent real value at the center point, and ∆X is the step change value. The elimination of lead is the dependent variable or the response. In addition, the behavior of the system is described by the following second-order polynomial model, Equation (11).
From the data in Table 5, it can be seen that there is an increase in CO 2 absorption rate and CO 2 gas mass transfer coefficient with absorption time and CO 2 gas flow rate. Table 6 displays BBD and the response of various parameters to distinct absorption conditions.

ANOVA in the Regression Model
The data in Table 5 was taken into account for ANOVA and multiple regression analyses in the Box-Behnken design using polynomial model Equation (12). The results are shown in Tables 7 and 8.   Table 7 shows the report contains a summary of the criteria and constraints used to generate the optimal solution for the process; all the criteria were applied to find the optimal setting. A solution is a search of all the solutions given to see which one best meets the specified criteria. The CO 2 absorption design and optimization model in this study is suitable for use as an alternative in the chemical industry or industries that emit a lot of CO 2 gas into the air, such as the cement industry, exhaust gas sources, natural gas burners, natural gas turbines, fuel-fired power plants, and coal, to absorb CO 2 gas before it is discharged into the air by adjusting the amount as needed. For example, the CO 2 gas produced is adjusted to the CO 2 absorption capacity and the scale ratio according to the needs of the desired CO 2 absorption capacity. The research model can be used as a pilot plant for CO 2 absorption before being discharged into the air as an alternative in the future to reduce CO 2 emissions into the air, which can cause global warming [28][29][30][31][32][33][34][35][36][37][38][39][40].

Fitting the Model
Analysis of variance (ANOVA) and multiple regression analysis were employed to evaluate the effects of individual and interaction factors using Design Expert 13. Box-Behnken design is the most frequently used RSM design, and the model equation is applied to predict the optimum CO 2 gas absorption flow rate (Y 1 ) and CO 2 gas mass transfer coefficient (Y 2 ).
The final equation in terms of coded factors is presented in Equation (13): The final equation in terms of actual factors is presented in Equation (14): The model equation was applied to predict the optimum CO 2 gas mass transfer coefficient (Y 2 , k og ).
The final equation in terms of coded factors is shown in Equation (15): The final equation in terms of actual factors is shown in Equation (16): where Y 1 is the predicted CO 2 gas absorption flow rate response, and Y 2 is the CO 2 gas mass transfer coefficient. Meanwhile, X 1 , X 2 , and X 3 are independent variables for absorption time, absorption flow rate, and CO 2 gas flow rate, respectively. Based on the equation, it was shown that the influence of absorption times (X 1 ), absorption flow rate (X 2 ), and CO 2 gas flow rate affected the CO 2 absorption rate and CO 2 gas mass transfer coefficient. These effects can be observed from the intercept and coefficients of the three optimization equations. Figure 2 illustrates the influence of interactive variables. Figure 2a displays the experimental and predicted data plot. The value predicted by the design response surface equation has a high degree of accuracy (R 2 = 0.97) and has an intercept of 1.00663. The distribution point spread above the prediction line demonstrates this. To obtain a respectable model, we must examine the normal probability value (%). As shown in Figure 2b, the proposed equation model is appropriate for predicting the CO 2 gas absorption flow rate (Y 1 ) and CO 2 gas mass transfer coefficient (Y 2 ) when using absorbent NaOH 0.1 M. The value predicted by the design response surface equation is precise (R 2 = 0.94) and has an intercept of 1.25048. The correlation of the variable effects on variable responses can be seen in Figures 2-6. In Figure 2, NaOH is wholly neutralized at the phenolphthalein endpoint, Na2CO3 is half neutralized, and HCO3 − has not responded. From the phenolphthalein endpoint to the methyl symbol endpoint, the bicarbonate is neutralized. Therefore, only a few drops of titrant will be required for the NaOH to change from pH 8 to 4, which will be corrected with a blank indicator. As shown in Table 4, v1 is the volume of acid in millimeters used from the start of the titration to the phenolphthalein endpoint, and v2 is the volume from pH [51,52], and the reaction is according to the following criteria. If the pH value < 4.5, then C CO _ P − value − C H . If the pH value is between 4.5-8.3, then C HCO = P − value. If the pH value is between 8.3-9.5, then C HCO = M − value − 2xP − value. Suppose the pH value is >9.5. Then C HCO is calculated from Equation (2). Figure 3a,b shows the 3-D optimization of the effect of absorption time (minutes), the flow rate of 0.1 M NaOH absorbent (L/min), and the flow rate of CO2 gas mixed with air (L/min) on the absorption rate of CO2 gas in the Raschig packing tower ring.   Figure 4a shows the effect of absorbent flow rate (X2, L/min) and CO2 gas flow rate (X3, L/min) on the CO2 absorption flow rate. The absorption rate of CO2 gas increases until it reaches optimum conditions, which are reached at a value of 4.1292. Figure 4b shows the effect of absorbent flow rate (X2, L/min) and CO2 gas flow rate (X3, L/min) on desirability. Desirability can be increased by choosing the proper criteria in planning the constraints to achieve the best optimal conditions. The best condition is achieved at the desired value of 0.99999.   Figure 5a shows the effect of absorbent flow rate (X2, L/min) and CO2 gas flow rate (X3, L/min) on the CO2 absorption flow rate. The CO2 absorption flow rate continues to increase so that optimum conditions are reached at 4.13 L/min. Figure 5b shows the desired optimization of the effects of absorption time (minutes), the flow rate of 0.1 M NaOH absorbent (L/min), and the CO2 gas flow rate (L/min) on the mass transfer coefficient of CO2 gas in the tower packing Raschig ring. Based on the analysis and optimization of 3-D plots, the optimum conditions for the CO2 uptake rate are 1.44656 L/min, and the mass transfer coefficient for CO2 gas is 1.44656 mol/min m 2 atm.  Figure 5a shows the effect of absorbent flow rate (X2, L/min) and CO2 gas flow rate (X3, L/min) on the CO2 absorption flow rate. The CO2 absorption flow rate continues to increase so that optimum conditions are reached at 4.13 L/min. Figure 5b shows the desired optimization of the effects of absorption time (minutes), the flow rate of 0.1 M NaOH absorbent (L/min), and the CO2 gas flow rate (L/min) on the mass transfer coefficient of CO2 gas in the tower packing Raschig ring. Based on the analysis and optimization of 3-D plots, the optimum conditions for the CO2 uptake rate are 1.44656 L/min, and the mass transfer coefficient for CO2 gas is 1.44656 mol/min m 2 atm.  Figure 6a shows the effect of the absorbent flow rate of 0.1 M NaOH (X2, L/min) and CO2 gas flow rate (X3, L/min) on the mass transfer coefficient of CO2 gas. The greater the flow rate of the absorbent and the flow rate of CO2 gas, the higher the mass damping value, and the faster the mass locking occurs due to the driving force difference in CO2  on a design to determine constraints that produce the best-desired desire. The optimum desirability value is 0.9999 (≈1). Numerical optimization and desirability ramps are shown in Figures 7 and 8, respectively.   In Figure 2, NaOH is wholly neutralized at the phenolphthalein endpoint, Na 2 CO 3 is half neutralized, and HCO 3 − has not responded. From the phenolphthalein endpoint to the methyl symbol endpoint, the bicarbonate is neutralized. Therefore, only a few drops of titrant will be required for the NaOH to change from pH 8 to 4, which will be corrected with a blank indicator. As shown in Table 4, v 1 is the volume of acid in millimeters used from the start of the titration to the phenolphthalein endpoint, and v 2 is the volume from the phenolphthalein endpoint to methyl orange.
During the absorption of CO 2 gas, a reaction occurs between CO 2 and OH − because the pH value decreases, and the reaction proceeds according to the following criteria. If pH = 11.5, the reaction is: If pH = 10, the reaction is: If pH = 11, the reaction is: After absorption of CO 2 gas, a mixture of OH − , CO 3 − , and HCO 3 − ions occurs in the solution [25,34]. Sample titration using HCl whose molarity is known (HCl standard) will obtain two equivalence points. In the first step, OH − reacts as a whole, whereas HCO 3 − reacts only in the second step, and CO 3 2− splits in both. Therefore, direct calculation of the concentration is not possible but can be calculated if the p-value and m-value have been determined. The p-value (phenolphthalein price) is the volume of titration used to titrate 1 mol/L HCl for 1000 mL so that the color of the phenolphthalein indicator changes (or to a pH of 8. = M − value − 2 × P − value + C OH − . CO 2 absorption is a function of pH; the reaction that occurs is a function of pH; the increasing absorption of CO 2 , which continues to increase, is a function of pH, sol-ubility, thermal, and longitudinal diffusion; the mechanism of mass contraction is the driving force in the form of differences in CO 2 concentrations and the partial pressure of each component and total pressure; the formula used is pH dependent, as it is determined by pH [51,52], and the reaction is according to the following criteria. If the pH value < 4.5, then C CO 2_ 3 P − value − C H + . If the pH value is between 4.5-8.3, then C HCO − 3 = P − value. If the pH value is between 8.3-9.5, then C HCO − 3 = M − value − 2 × P − value. Suppose the pH value is >9.5. Then C HCO − 3 is calculated from Equation (2). Figure 3a,b shows the 3-D optimization of the effect of absorption time (minutes), the flow rate of 0.1 M NaOH absorbent (L/min), and the flow rate of CO 2 gas mixed with air (L/min) on the absorption rate of CO 2 gas in the Raschig packing column ring. Figure 3a shows the effect of absorption time (X 1 , min) and absorbent flow rate (X 2 , L/min) on CO 2 gas absorption flow rate (Y 1 , L/min). The effect of the two independent variables on the response variable (CO 2 gas absorption) increased, and optimal conditions were reached at 4.13 L/min. Figure 3b shows the desired optimization of the effect of absorption time (minutes), the flow rate of 0.1 M NaOH absorbent (L/min), and air-mixed CO 2 flow rate (L/min) on the absorption rate of CO 2 gas in the Raschig ring packing column. The effects of absorption time (X 1 , min) and CO 2 gas flow rate (X 2 , L/min) on CO 2 gas absorption rate (Y 1 , L/min) increased until it reached the optimum condition of 4.13 (L/min). Figure 4a,b show the 3-D optimization of the effect of absorption time (minutes), the flow rate of 0.1 M NaOH absorbent (L/min), and CO 2 gas flow rate (L/min) on the mass transfer coefficient of CO 2 gas in the Raschig ring packing column. Figure 4a shows the effect of absorbent flow rate (X 2 , L/min) and CO 2 gas flow rate (X 3 , L/min) on the CO 2 absorption flow rate. The absorption rate of CO 2 gas increases until it reaches optimum conditions, which are reached at a value of 4.1292. Figure 4b shows the effect of absorbent flow rate (X 2 , L/min) and CO 2 gas flow rate (X 3 , L/min) on desirability. Desirability can be increased by choosing the proper criteria in planning the constraints to achieve the best optimal conditions. The best condition is achieved at the desired value of 0.99999. Figure 5a shows the effect of absorbent flow rate (X 2 , L/min) and CO 2 gas flow rate (X 3 , L/min) on the CO 2 absorption flow rate. The CO 2 absorption flow rate continues to increase so that optimum conditions are reached at 4.13 L/min. Figure 5b shows the desired optimization of the effects of absorption time (minutes), the flow rate of 0.1 M NaOH absorbent (L/min), and the CO 2 gas flow rate (L/min) on the mass transfer coefficient of CO 2 gas in the column packing Raschig ring. Based on the analysis and optimization of 3-D plots, the optimum conditions for the CO 2 uptake rate are 1.44656 L/min, and the mass transfer coefficient for CO 2 gas is 1.44656 mol/min m 2 atm. Figure 6a shows the effect of the absorbent flow rate of 0.1 M NaOH (X 2 , L/min) and CO 2 gas flow rate (X 3 , L/min) on the mass transfer coefficient of CO 2 gas. The greater the flow rate of the absorbent and the flow rate of CO 2 gas, the higher the mass damping value, and the faster the mass locking occurs due to the driving force difference in CO 2 gas concentration in the absorbent and air. Optimal mass absorption conditions are achieved at 1.44656 mol/min m 2 or mol/min m 2 atm. Figure 6b is the effect of 0.1 M NaOH absorbent flow rate (X 2 , L/min) and CO 2 flow rate (X 2 , L/min) on optimal desirability based on a design to determine constraints that produce the best-desired desire. The optimum desirability value is 0.9999 (≈1). Numerical optimization and desirability ramps are shown in Figures 7 and 8, respectively.   Numerical optimization bar graph (Pareto graph), The bar graph is a graphical view of each optimal solution. The optimal factor settings are shown: absorption time (X 1 ), absobent flow rate (X 2 ), CO 2 flow rate (X 3 ), CO 2 absorption rate (Y 1 ), and CO 2 gas mass coefficient (Y 2 ).   Figure 9 shows the 3-D optimization of the effect of absorption time (min) and pH on the formation of HCO3 − and CO3 2− as a result of the reactions between 2OH -+ CO2 and CO3 2− + CO2 + H2O2 + HCO 3− , conditions under which the optimum was achieved at 154.994 mol/L HCO3 − and 105.664 mol/L CO3 2− . This shows that absorption also occurs chemically, according to pH. This reaction occurs at a pH of 9.5-11, forming CO3 2− and HCO3 2− due to the reaction of OH − and CO2, whose products can be used to meet the needs of cosmetics and food ingredients.  This shows that absorption also occurs chemically, according to pH. This reaction occurs at a pH of 9.5-11, forming CO 3 2− and HCO 3 2− due to the reaction of OH − and CO 2 , whose products can be used to meet the needs of cosmetics and food ingredients. Figure 9 shows the 3-D optimization of the effect of absorption time (min) and pH on the formation of HCO3 − and CO3 2− as a result of the reactions between 2OH -+ CO2 and CO3 2− + CO2 + H2O2 + HCO 3− , conditions under which the optimum was achieved at 154.994 mol/L HCO3 − and 105.664 mol/L CO3 2− . This shows that absorption also occurs chemically, according to pH. This reaction occurs at a pH of 9.5-11, forming CO3 2− and HCO3 2− due to the reaction of OH − and CO2, whose products can be used to meet the needs of cosmetics and food ingredients.    Figure 10 shows the numerical optimization bar graph (Pareto graph) for desirability. The bar graph is a graphic display for each optimal solution. Optimal factor settings are shown with red bars, and optimal response predicted values are shown in blue. Optimum conditions for the desirability of each factor are, respectively, absorption time (X 1 , min), absorbent flow rate (X 2 , L/min), and CO 2 gas flow rate mixed with air = 0.99, CO 2 absorption desire rate (Y 1 , L/min), and mass transfer coefficient CO 2 gas (Y 2 , mol/min m 2 atm) = 0.999 each; and combined desire = 0.99.    Figure 11 is the desirability ramp for numerical optimization of the 3-D optimization of the effect of absorption time (minutes) and pH on the formation of HCO 3 − and CO 3 2− as a result of the reaction between 2OH − + CO 2 → CO 3 2− + H 2 O and CO 3 2− + CO 2 + H 2 O → 2 HCO 3 − , optimal conditions achieved, i.e., absorption time = 15.3097 (X 1 , min), pH = 11.52 (X 2 ), CO 3 2− = 105.664 mol/L, HCO 3 2− = 154.994 mol/L, a total of CO 2 = 76.9359 L, and desirability = 0.91. Figure 11 is the desirability ramp for numerical optimization of the 3-D optimization of the effect of absorption time (minutes) and pH on the formation of HCO3 -and CO3 2− as a result of the reaction between 2OH − + CO2 → CO3 2− + H2O and CO3 2− + CO2 + H2O → 2 HCO3 − , optimal conditions achieved, i.e., absorption time = 15.3097 (X1, min), pH = 11.52 (X2), CO3 2− = 105.664 mol/L, HCO3 2− = 154.994 mol/L, a total of CO2 = 76.9359 L, and desirability = 0.91.  Table 9 illustrates the numerical optimization. Constraints are designed according to appropriate criteria to produce reliable validity and high accuracy by looking at the influence and correlation between each independent variable and the response variable to produce the correct constraints and high desirability.  Table 9 illustrates the numerical optimization. Constraints are designed according to appropriate criteria to produce reliable validity and high accuracy by looking at the influence and correlation between each independent variable and the response variable to produce the correct constraints and high desirability.
where, n is the number of responses in the measure; if all the important values are the same, the simultaneous objective function reduces to the normal form for desirability. For the goal of maximum, the desirability will be defined by the following formulas: For absorption time criteria, X 1 (10-80 min) maximum goals: optimum X 1 = 80 min absorption flow rate; X 2 (2-5 L/min) maximum goals: optimum X 2 = 5 L/min, CO 2 gas flow rate, X 3 (2-5 L/min): optimum X 3 = 5 L/min on absorption flow rate Y 1 = 3.967 L/min and desirability = 0.999999 ≈ 1. Desirability ramp for numerical optimization of three goals, i.e., the absorption time, X 1 (10-80 min), absorbent flow rate, X 2 (2-5 L/min) CO 2 gas flow rate, X 3 (2-5 L/min), on mass transfer coefficient (Y 2, mol/min m 2 atm) as the response variable. Optimum condition: X 1 = 5 L/min, X 2 = 5 L/min, X 3 = 5 L/min, Y 2 = 1.442 mol/min m 2 atm and desirability = 0.999999 ≈ 1 Table 10 presents desirability function optimization. Analysis of variance (ANOVA) for responses to CO 2 gas absorption flow rate (Y1) indicates that effects of individual factors (absorption time, absorption flow rate, and CO 2 gas flow rate) are significant for degree of confidence ≥ 95% (p-value ≤ 0.05). The RSM model selected is a quadratic model, R2 = 0.97, CV = 7.4, and the model is very significant. Analysis of variance (ANOVA) for the response variable CO 2 gas mass transfer coefficient (Y 2 ) showed the influence of individual factors and significant interaction for the degree of confidence ≥ 95% (p-value ≤ 0.05), except for the interaction effect of X 1 X 2 and X 2 X 3 , which was not significant. Therefore, the RSM model was chosen as a quadratic model with R 2 = 0.94 and CV = 4, and the model is significant.

Conclusions
This study investigated CO 2 gas absorption with NaOH absorbent continuous system in Raschig ring packing column using Box-Behnken design. Based on the results and discussion, the optimization conditions assumed a maximum point for desirability. Experiments were performed based on absorption time, the absorption flow rate of 0.1 M NaOH, and the CO 2 gas flow rate. The results showed that the absorption of CO 2 gas in the air was optimized by using 0.1 M NaOH absorbent in the column of the Raschig ring stuffing material using the response surface methodology (RSM), with an absorption rate of 4 L/min, a mass transfer coefficient of 1.4425 mol/min m 2 atm, and desirability 0.999 ≈1.