Numerical Investigations of CO2 Sorption and Recovery Process from

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Numerical Investigations of CO2 Sorption and Recovery Process from Wet Flue Gas by Using K2CO3/Al2O3 in a Fixed Bed Yang Yang You, Xiang Jun Liu, and Tang Lin Liu Energy Fuels, Just Accepted Manuscript • DOI: 10.1021/acs.energyfuels.7b03190 • Publication Date (Web): 06 Dec 2017 Downloaded from http://pubs.acs.org on December 7, 2017

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Numerical Investigations of CO2 Sorption and Recovery Process from Wet Flue Gas by Using K2CO3/Al2O3 in a Fixed Bed Yang Yang You, Xiang Jun Liu*, Tang Lin Liu School of Energy and Environmental Engineering, University of Science & Technology Beijing, Beijing 100083，China

ABSTRACT:

Fixed-bed sorption technology is a promising option for

separating CO2 from flue gas, and potassium-based Al2O3 (K2CO3/Al2O3) is a potential sorbent in the presence of H2O. This paper studies the stepwise reaction mechanism of CO2/H2O sorption on K2CO3/Al2O3, and the expressions of sorption equilibrium and kinetics are proposed and verified by experimental data. A comprehensive set of mathematical models of separation and recovery CO2 from wet flue gas in a fixed bed of K2CO3/Al2O3 is established. The CO2 separation and recovery process from wet flue gas in the fixed bed are numerically studied. Detailed results of H2O/CO2 sorption and desorption in the fixed bed during pressure/vacuum swing cycles are revealed, and the optimum operating parameters are suggested. Results show that carbon dioxide recovery can be further enhanced using a vacuum temperature swing adsorption (VTSA) process or by adding a pre-wetting step before sorption process. Keywords: K2CO3/Al2O3, CO2 capture, wet flue gas, fixed bed

1

ACS Paragon Plus Environment

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1. INTRODUCTION Global warming caused by CO2 emission1 has been a widespread concern in recent years, and most CO2 is produced by the combustion of fossil fuels. CO2 capture and storage (CCS) 2 from flue gas has been widely studied. Among various CCS approaches, CO2 capture by pressure/vacuum swing adsorption (P/VSA) methods using fixed bed technologies is a promising option for separating CO2 from flue gas because of its relatively low operating and capital costs. Adsorbent plays an important role in the separation process because the properties of adsorbent directly determine the CO2 adsorption capacity and performance. Many researchers have investigated CO2 separation and recovery from flue gas by P/VSA methods using zeolite 13X, zeolite 5A, activated carbon, silica gel, and other adsorbents. Krishnamurthy et al.3 studied the performance of zeolite 13X in the capture and concentration of CO2 from dry flue gas with a basic four-step VSA cycle in a single bed, in which purity and recovery rates can reach 95.9% and 86.4%, respectively. Liu et al.4 studied the performance of zeolite 5A in the capture and concentration of CO2 from dry flue gas with vacuum pressure swing adsorption process, which includes steps for rinse and pressure equalization, which can obtain 85% CO2 with a recovery of 79%, and its simulated results were in good agreement with experimental results. Nikolaidis et al.5 evaluated three available potential adsorbents (zeolite 13X, activated carbon, and Mg-MOF-74) in a two-bed P/VSA system for CO2 capture from dry flue gas by numerical simulation. Among the three adsorbents, zeolite 13X performs best in terms of purity and recovery, whereas 2


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Mg-MOF-74 can obtain high productivity. In its process optimization, zeolite 13X and Mg-MOF-74 were selected for the study on minimizing energy consumption at nearly atmospheric feed pressures. The minimum target of 90% in CO2 purity and 90% in CO2 recovery is met, whereas zeolite 13X requires low energy consumption. Balsamo et al. 6 studied the CO2 capture capacity of two particle size classes of the commercially activated carbon, the relationships between sorbent microstructural properties and CO2 capture thermodynamics, and dynamics characteristics under typical flue gas conditions. The currently used adsorbents perform well in capturing CO2 from dry flue gas. However, real flue gas streams usually contain 8%–12% water vapor, and the presence of water vapor significantly reduces the CO2 adsorption capacity for those adsorbents, which complicates the separation operations and thus increases the capturing cost of CO2 from flue gas. The emergence of potassium-based load adsorbents makes it possible for directly capturing CO2 from wet flue gas. K2CO3/Al2O3 reacts with CO2 and H2O in the flue gas at low absorption temperatures, which range from room temperature to 90 °C7. Sharonov et al.8 studied the chemical kinetic characteristics of the reaction of K2CO3/Al2O3 with CO2 and obtained carbonation reaction series. Lee et al.9 completed the relevant test that aims to ensure the superior performance of the potassium-based load-type adsorbent in the reactor of the fixed bed. Seo10 utilized a small bubbling fluidized bed system to study the influence of steam pretreatment before the reaction on the carbonic acid reaction of sodium and potassium-based 3


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sorbents. Seo revealed that pumping in water vapor to a fluidized bed reactor for pretreatment of the adsorbent can improve carbonate reaction performance. Zhao1 experimentally investigated the reaction principles through reaction products and relevant reactions in the technological aspects that use potassium sodium-based solid absorbent for CO2 emission. The results show that the hydration and carbonation reactions first occur for K2CO3 with the structure of monoclinic crystal and hexagonal crystal. Current studies mostly focus on the performance of K2CO3/Al2O3 on capturing CO2 using a fluidized bed or bubbling bed technologies. Only several applications in a fixed bed in the case of CO2 at low concentration have been reported.12 Further studies on the application and development of a reliable theoretical model are needed for K2CO3/Al2O3 in capturing CO2. This study proposed the expressions of CO2/H2O sorption equilibrium on K2CO3/Al2O3 based on the stepwise reaction mechanism of water and carbon dioxide with K2CO3/Al2O3. A comprehensive set of the mathematical models of separation and recovery CO2 from wet flue gas in the fixed bed of K2CO3/Al2O3 is established. Detailed CO2 capture characteristics and the performance of K2CO3/Al2O3 are revealed. Results show that the CO2 recovery can be further enhanced using a VTSA process or by adding a pre-wetting step before the sorption process.

4


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2. SORPTION

EQUILIBRIUM

OF

H2O/CO2

ON

K2CO3/Al2O3 2.1. Sorption Equilibrium Model. The hydration and carbonation reactions realize the sorption of CO2 under moist conditions. The model involves two steps13 in which the hydration reaction creates active sites for carbonation reaction to sorb CO2. Hydration: K2CO3(s) +1.5H2O(g) ⇔ K2CO3 ⋅1.5H2O(s)

(1)

Carbonation: K2CO3 ⋅1.5H2O(s) +CO2(g) ⇔ 2KHCO3(s) + 0.5H2O(g)

(2)

The combined reaction equation is expressed as follows:

K2CO3(s) + H2O(g) +CO2(g) ⇔ 2KHCO3(s)

(3)

The D-A adsorption isotherm equation14 is employed to calculate the number of active sites in the hydration reaction. n    ps    qas = qm ⋅ xK2CO3 ⋅ exp  −  D ⋅ ln     ,    p1    

(4)

where qas is the number of active sites, [mol/kg]; qm is the maximum reaction amount of H2O with 1 kg K2CO3 in eq 3, [mol/kg], whose value is 7.246 mol/kg;

xK2CO3 is the load percentage of K2CO3 in Al2O3, [%]; ps is the saturation water vapor pressure, [Pa]; and pl is the water vapor partial pressure, [Pa]. n is 1.3 in the calculations. D is the parameter that associates with the temperature in a linear function and is expressed as eq 5, and A is a constant, [1/K].

D = AT

(5)

The Langmuir model15 is used to describe the sorption of CO2 on the active sites, that is, 5


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ka p2 (θ1 − θ2 ) = kd p10.5θ2 ,

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(6)

where p2 is the partial pressure of CO2, [Pa]; θ1 and θ 2 respectively indicate the coverage rate of the active site and potassium bicarbonate, [%]; ka , [Pa0.5], and kd , [Pa], are the positive and reverse reaction rates, respectively. The sorption isothermal equation of CO2 with K2CO3/Al2O3 is obtained as eq 7.

qCO2 = qas

ka ⋅ p2 θ2 = qas . 0.5 kd p1 + ka ⋅ p2 θ1

(7)

We substitute eq 4 to eq 7, and the sorption amount of CO2, [mol/kg], is expressed as follows:

qCO2

n    ps    K ⋅ p2 = qm ⋅ xK2CO3 ⋅ exp  −  D ⋅ ln     ⋅ 0.5 ,   p1    p1 + K ⋅ p2   

(8)

where K =ka / kb is equilibrium constant, [Pa−0.5], which can be expressed by16

 ∆H  K = K0 exp  − 2  ,  RT 

(9)

where K 0 is the sorption equilibrium constant, [Pa−0.5], and ∆H 2 is the isosteric heat of sorption of CO2, [J/mol]. Combining the hydration and carbonation reaction equations, the total sorption amount H2O is

qH2O,ad = qH2O,hy − qH2O,re ,

(10)

n    ps    qH2O,hy = 1.5 ⋅ qm ⋅ xK2CO3 ⋅ exp  −  D ⋅ ln     , and    p1    

(11)

qH2O,re = 0.5⋅ qCO2 ,car ,

(12)

where qH2O,ad is the sorption amount of H2O, [mol/kg]; qH2O,hy and qCO2 ,car are the 6


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reaction amount of H2O in the hydration and carbonation reaction, respectively, [mol/kg]; and qH 2O,re represents the amount of H2O reduced in the carbonation reaction, [mol/kg]. Finally, the sorption amount of H2O is given by n    ps      Kp qH2O,ad = qm ⋅ xK2CO3 ⋅ exp  −  D ⋅ ln     ⋅ 1.5 − 0.5 ⋅ 0.5 2  .   p1 + Kp2   p1     

(13)

2.2. Fitting and Verification of Sorption Equilibrium. The sorption equilibrium model is used to fit the experimental data measured by Zhao.17 In Zhao’s thermogravimetric experiment system, the simulating flue gas that is composed of CO2, H2O, and N2 was sorbed with K2CO3/Al2O3 at a pressure of 0.1 MPa. The load percentage of K2CO3 in Al2O3 is 28.5%. The mass of the adsorbent is 100 mg, and the average size is 0.02 mm. Zhao used this experiment to investigate the effects of H2O/CO2 concentration and reaction temperature on carbonation. Experimental temperature is maintained at 338 K in the study of the effects of H2O/CO2 concentrations on carbonation. One set of experimental data is obtained by maintaining CO2 partial pressure at 15.0 kPa while increasing H2O partial pressure from 3.0 kPa to 21.0 kPa. The other set of experimental data is obtained by maintaining H2O partial pressure at 15.0 kPa while increasing CO2 partial pressure from 5.0 kPa to 20.0 kPa. The fitting results are shown in Figures 1 and 2, and the fitting parameters are listed in Table 1. The fitting errors are expressed as the root mean squared error (RMSE) and the average relative error (Rave), which are calculated as follows: 7


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1 N

RMSE=

R ave =

1 N

N

∑(y

exp

− ycal ) 2 and

(14)

,

(15)

i =1

N

yexp − ycal

i =1

yexp

∑

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where N is the number of experiment data points, yexp is the value of the experiment data, and ycal is the value of the simulation result.

Figure 1. Influence of H2O concentration in the reaction (p2=1.5×104 Pa)

Figure 2. Influence of CO2 concentration in the reaction (p1=1.5×104 Pa) Table 1. Fitting parameters of CO2/H2O sorption equilibrium at 338 K Parameters

D

K (Pa−0.5)

RMSE

Rave

Value

0.5310

0.04821

0.0032

0.0368

In the study of the effects of the reaction temperature on carbonation, the gas component is kept as 15% CO2, 15% H2O, and 70% N2, and the temperature ranges 8


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from 333 K to 353 K. The fitting results obtained by the model are illustrated in Figure 3. The fitting parameters of A, K0, and ∆H 2 , which are related to temperature, are shown in Table 2. The results describe the influence of temperature on carbonation.

Figure 3. Influence of temperature in the reaction (p1 =p2=1.5×104 Pa) Table 2. Fitting results of temperature-related parameters of A, K0, and ∆H 2 Parameters

A (1/K)

K0 (Pa−0.5)

∆H 2 (J/mol)

RMSE

Rave

Value

1.361e-3

34.19

18490

0.0077

0.0578

Through the proposed CO2/H2O sorption equilibrium model and the obtained fitting parameters, the predicted sorption isotherms of CO2 at different H2O concentrations under the conditions of 338 K and 1 bar are shown in Figure 4. The existence of water shows positive effects on the process of CO2 sorption on K2CO3/Al2O3.

9


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Figure 4. Sorption equilibrium isotherms of CO2 at different H2O concentrations (T=338 K)

3. MATHEMATICAL MODELS OF H2O/CO2 SORPTION IN FIXED BED AND MODEL VALIDATION 3.1. VSA Process. A fixed bed of K2CO3/Al2O3 is exposed to a flow of feed flue gas for a period to sorb water and carbon dioxide. The pressure that changes periodically promotes gas separation in VSA. VSA technology has advantages over a short cycle, flexible operation, and low energy consumption. This study mainly designed the process of VSA in five stages: prepressing, sorption, vacuum, vacuum maintenance, and purging. The pressure in the bed rises to sorption pressure, and then the sorption stage begins. After sorption, the pressure drops to the vacuum pressure and keeps the vacuum pressure for a certain period. Finally, pure N2 is used to purge the bed at the purge pressure. A typical pressure curve used in this study is shown in Figure 5.

10


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Figure 5. Variation of bed pressure in a VSA cycle

The expressions of pressure in the stage of prepressing and vacuum are given by eqs 16 and 17, respectively.

ppre = ph + ( pu − ph )(1 − t / tpre ) 2

(16)

pvac = pl + ( ph − pl ) (1 − (t − tpre − tad )/ t vac ) , 2

(17)

where ppre , ph , pvac , pl , and pu respectively indicate the pressure at the stage of prepressing, sorption, vacuum, vacuum maintenance, and purging. tpre, tad, and tvac respectively indicate the duration of the stage of prepressing, sorption, and vacuum.

3.2. Mass and Energy Conservation Equation. A mathematical model is developed to numerically study the sorption and desorption of H2O/CO2 in a fixed bed of K2CO3/Al2O3. The following assumptions are established: (1) The fluid is regarded as piston flow for the axial dispersion. (2) The model is simplified as a one-dimensional model. The gradients of the concentration, velocity, and temperature in the radial direction of the fixed bed are ignored. (3) The axial pressure drop of the bed is ignored.

11


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(4) The bed wall is assumed adiabatic. (5) N2 adsorption on K2CO3/Al2O3 is neglected. (6) The gases involved in the process obey the ideal gas law. The mass conversation equation for component i is expressed as

∂ci ∂ ( uci ) ∂  ∂ci  ρ b ∂ qi + −  DL =0, + ∂t ∂x ∂x  ∂x  ε ∂t

(18)

where ci is the average molarity of component i, [mol/m3]; i represents H2O when its value is 1 and represents CO2 when it is 2; u is the interstitial velocity, [m/s]; ε is the bed porosity; ρb is the bulk density of adsorbent in the bed, [kg/m3]; and DL is the axial dispersion coefficient, [m2/s]. The sorption rate ∂ q / ∂ t can be determined by the linear driving force model given by

∂ qi = ki qi* − qi , ∂t

(

)

(19)

where qi* represents the equilibrium sorption capacity of H2O and CO2, [mol/kg], which are calculated by eqs 8 and 13. k is the mass transfer coefficient, [1/s]. The estimated values of the mass transfer coefficients of the water vapor and CO2 are 6.805e-3 1/s and 8.245e-3 1/s, respectively. The overall mass balance equation is expressed as

∂c ∂ ( uc ) ∂  ∂c  ρ + −  DL  + b ∂t ∂x ∂x  ∂x  ε

∑ j

∂q j ∂t

=0.

(20)

The interstitial velocity can be determined as ∂u u ∂T  1 ∂p 1 ∂T  ρ b RT − + − + ∂x T ∂x  p ∂t T ∂t  εp

∑ j

∂q j ∂t

= 0.

(21)

The energy balance equation is expressed as 12


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ρb ∂T ∂ 2T ρ   ∂T + ρg c p ,gu − λax 2 = b  ρg c p ,g + c p ,s  ∂x ∂x ε ε   ∂t

∑ ( ∆H

+ c p ,g M gT

j

j

∂q j

) ∂t

+

dp , (22) dt

where ρg is the density of the gas phase, [kg/m3]; cp,g and cp,s are the specific heat of the gas and solid phases, respectively, [J·kg−1·K−1]; λax is the axial thermal conductivity, [W·m−1·K−1]; ∆H is the isosteric heat of sorption, [J/mol]; and Mg is the molar mass of the gas phase, [kg/mol].

3.3. Boundary and Initial Conditions. The boundary and initial conditions of each stage in the process of calculation are listed in Table 3.

Table 3. Boundary and initial conditions

Process Prepressing

Sorption

Vacuum

Vacuum Maintenance

Purging

C

ci

ci

x =0

= ci.ad.0

x =0

= ci.ad.0

∂ci ∂x ∂ci ∂x ∂ci ∂x

=0 x =0

=0 x =0

x =0

T

∂ci ∂x ∂ci ∂x ∂ci ∂x ∂ci ∂x

=0 x= L

=0 x= L

=0 x =L

=0 x =L

= 0 ci x=0 = ci.pur.0

u

T x=0 = Tpre

∂T ∂x

x=L

T x=0 = Tad

∂T ∂x

x=L

∂T ∂x

∂ci ∂x

x =L

∂T ∂x

x=L

=0 x =0

∂T ∂x

x =0

∂T ∂x

x =0

=0

=0

u x =L = 0

=0

u x=0 = u0

=0

u x =L = 0

=0

u x =L = 0

= 0 T x=L = Tpur

u x=L = −upur

Initial conditions

ci ( x,0) = 0; qi ( x,0) = 0;T ( x) = 333K

3.4. Model Validation. The model is further validated by simulating the breakthrough process discussed by Jaiboon.18 His breakthrough experiment operated 13


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in a fixed bed with a height of 0.14 m and a diameter of 0.025 m. The fixed bed is packed with K2CO3/Al2O3. The load percentage of K2CO3 is 35%, the mass of adsorbent is 60 g, and the average size is 0.15 mm. The feed gas consists of 10% CO2 and 15.5% H2O sorbed at 333 K and 1 atm with the velocity of 0.01 m/s. The simulation results in Figure 6 show that the breakthrough curve is in good agreement with the experimental data.

Figure 6. Breakthrough curve of CO2 on K2CO3/Al2O3

4. CALCULATION RESULTS OF VSA PROCESS 4.1. H2O and CO2 Sorption and CO2 Recovery Characteristics. The VSA process is performed in a fixed bed. The parameters of the bed and K2CO3/Al2O3 particles and flue gas are listed in Table 4. The basic working conditions are adopted from previous research on 5A molecular sieve trapping dry flue gas.19 The feed gases composed of 15% CO2 and 15% H2O are sorbed at the temperature of 333 K and the pressure of 1.35 bar with the feed flow rate of 0.14 Nm3/h. The pressure of feed gas is balanced with 70% N2. The vacuum pressure is 0.08 bar. Moreover, the bed is purged by pure N2 at the temperature of 333 K and the pressure of 0.15 bar in the purge stage. 14


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The P/A ratio is 0.05.

Table 4. Parameters of fixed bed and K2CO3/Al2O3 particles and flue gas Parameter Filling height L, m Diameter of bed db, m Voidage ε Bulk density ρb, kg/m3 Particle weight m, kg Specific heat of particle Cp.s, J/(kg·K) Particle diameter dp, m Specific area ap, m2 Specific heat of flue gas Cp,g, J/(kg·K) Axial dispersion coefficient DL, m2/s Molar mass M, kg/mol Density ρg, kg/m3 Axial thermal conductivity λax, W/(m·K) Isosteric heat of sorption of H2O ∆H1 , J/mol Isosteric heat of sorption of CO2 ∆H 2 , J/mol Mass transfer coefficients of H2O k1, 1/s Mass transfer coefficients of CO2 k2, 1/s

Value 0.37 0.025 0.324 870 0.158 784 1.8e-3 138.96 1005 2.375e-6 29e-3 1.293 0.75 50000 18490 6.805e-3 8.245e-3

Through the sorption/desorption simulations based on the basic working conditions, the cycle duration of Run 1 is set as follows: prepressing 15 s, sorption 285 s, vacuum 60 s, vacuum maintenance 120 s, and purging 120 s. The operating parameters of Run 1 are summarized in Table 5.

Table 5. Operating parameters of Run 1 Run

tcycle (s)

Tad (K)

Tpur (K)

YCO2 (%)

YH2O (%)

Qv (Nm3/h)

Ph (bar)

Pl (bar)

Pu (bar)

P/A

1

600

333

333

15

15

0.14

1.35

0.08

0.15

0.05

The variation of total loading amount is shown in Figure 7. Calculation reaches cycle steady state when the time reaches 600 min (60th cycle). We pick up the results at the 100th cycle for research.

15


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Figure 7. Variation of total loading amount of H2O and CO2

Figure 8 (a) shows the temperature distribution of the bed at the end of the sorption, vacuum maintenance, and purging duration. The temperature of the top of the bed rises to 88.9 °C at the end of the sorption because of the heat released in the sorption stage. The temperature declines in the desorption stage, and the temperature of the bottom of the bed (34.2 °C) is lower than that of the top (65.2 °C) at the end of vacuum maintenance because the heat is absorbed in the stage of desorption and because desorption gas comes out of the bottom. In the purge stage, the temperature of the purge gas is higher than that of the bed. Thus, the temperature distribution curve around the top shows a downward part.

(a) 16


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(b)

(c) Figure 8. Parameter distribution of bed in 100th cycle: (a) temperature, (b) gas concentrations of H2O and CO2, and (c) loading amount of H2O and CO2.

Figures 8(b) and 8(c) show the distribution of gas concentrations and the loading amounts of H2O and CO2 in the bed. At the end of the sorption, the concentrations of the gas reaches the feed concentrations, and the total loading amounts reach the maximum. After the vacuum and the vacuum maintenance stage, the total loading amounts are reduced, and the values of the bottom are higher than those of the top because the gases flow from the bottom of the bed. The concentrations are higher at the end of the vacuum maintenance stage because of the desorption process. Purge gas

17


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flows from the top of the bed at the stage of purging. The concentrations and total loading amount continues to decrease at the end of purging, especially around the top of the bed. Figure 9 indicates the variation of the total loading amount in the 100th cycle. The loading amount of H2O and CO2 respectively increased to 0.296 and 0.225 mol at the end of the sorption step and decreased to 0.251 and 0.167 mol at the end of the purge step.

Figure 9. Variation of H2O and CO2 loading amount in one cycle

Figure 10 shows the gas concentration variation at the top of the bed in the pressurization and sorption duration of the 100th cycle. The concentrations of the top of the bed are low at the initial time because the feed gas flows from the bottom and into the bed. The CO2 concentration slightly increases during the first 0.5 minutes of the cycle because CO2 has not been much sorbed in the initial half-dry bed. As the sorption proceeds, the bed sorbs more H2O and CO2, and the sorbent reaches the saturation state gradually, which results in more feed gas escaping out of the bed from the top. The H2O and CO2 concentrations at the end of the sorption reach 16.6% and

18


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9.5%, respectively.

Figure 10. H2O and CO2 concentration at top of bed during pressurization and sorption steps

Figure 11 shows the gas concentration variations at the bottom of the bed in the desorption duration of the 100th cycle. The desorption process includes the stage of vacuum, vacuum maintenance, and purging. In the vacuum and vacuum maintenance stage, the top of the bed is in a closed state, and the gas flows from top to bottom. With the pressure drop, H2O and CO2 desorb from the sorbent, the concentrations of the gases at the bottom increase gradually, and the H2O and CO2 concentrations reach 53.1% and 46.9%, respectively. At the end of the vacuum stage, the pressure change slows down. The H2O concentration starts to decrease, and the CO2 concentration increases slowly because the difference of sorption heat results in that the CO2 desorption is easier than that of H2O. Moreover, the desorption of water requires a two-step reaction, and the desorption of CO2 requires a one-step reaction according to eqs 1 and 2. At the end of the vacuum maintenance stage, the concentration of H2O reduces to 31.8%, and the concentration of CO2 increases to 68.3%. In the purge stage, N2 begins to enter the bed. The H2O and CO2 concentrations decrease suddenly, and

19


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the concentrations at the bottom reduce gradually.

Figure 11. H2O and CO2 concentration at bottom of bed during desorption and purge steps

To evaluate the merits of the sorption process, the product dry purity, [%]; recovery rate, [%]; and the productivity, [kg/kg/h] of a VSA process, which are defined by eqs 23, 24, and 25, can be investigated after the process reaches a steady state. Dry purity and recovery are the ratios of the CO2 amount in product gas to the total amount of product gas, which is without H2O, and the amount of CO2 in feed gas within a cycle, respectively. Productivity is the amount of CO2 sorbed by the unit mass of adsorbent per hour.

Dry purity =

∫

t vac + tma

0

∫

tvac + tma

0

∫ Recovery =

tpur

0 tpur

(1 − c1 ) u x =0 dt + ∫

0

t vac + tma

0

c2 u x =0 dt + ∫

tpur

0

∫

tpre + tad

0

Productivity =

c2 u x =0 dt + ∫

(∫

tvac + tma

0

c2 u x =0 dt (1 − c1 ) u x =0 dt

c2 u x =0 dt

,

, and

(23)

(24)

c2 u x =0 dt

c2 u x = 0 dt + ∫

tpur

0

c2 u x =0 dt ) SM 2

mtcycle / 3600

,

(25)

where tcycle is the duration of a cycle in the VSA process, [s]; tma and tpur respectively indicate the duration of the stage of vacuum maintenance and purging, [s]; S is the 20


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cross-sectional area of the bed, [m2]; M2 is the molar mass of CO2, [kg/mol]; and m is the mass of adsorbent filled with the fixed bed, [kg]. The calculated product purity, recovery rate, and productivity of Run 1 are shown in Table 6. The working conditions of Run 1 are similar to the 5A molecular sieve trapping dry flue gas in the work of Liu19, and the performance rates of the 5A molecular sieve trapping dry flue gas are 70.5% (dry purity), 46.2% (recovery), and 0.09 kg/kg/h (productivity). The results shown in Table 6 indicate that the performance of Run 1 is comparable with that of the 5A molecular sieve trapping dry flue gas. The VSA process shows that separation and recovery of CO2 from the wet flue gas using the fixed bed of K2CO3/Al2O3 is feasible.

Table 6. Recovery performance of Run 1 Run

Dry purity (%)

Recovery (%)

Productivity (kg/kg/h)

1

84.4

78.5

0.30

4.2. Effect of Operating Parameters on Performance of VSA. This section mainly focuses on the influence of various operating parameters on the VSA process to determine optimal operating parameters.

4.2.1. Effect of Vacuum Pressure on Performance of VSA. In the calculations of Run 2 to Run 6, the operating conditions are the same as Run 1, except the vacuum and purge pressure. The relevant parameters and computation results are shown in Table 7.

Table 7. Pressure parameters and separation performance Run 2

pl

pu

(bar)

(bar)

Dry purity (%)

Recovery (%)

Productivity (kg /kg/h)

0.08

0.3

83.3040

72.4777

0.2769 21


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3

0.2

0.3

75.1617

44.1302

0.1688

4

0.3

0.3

67.1158

37.2055

0.1431

5

0.4

0.4

59.4663

24.0554

0.0921

6

0.5

0.5

51.6513

17.2572

0.0661

As reported in Table 7, the low vacuum pressure improves the efficiency of the sorption process. The dry purity, recovery rate, and productivity increase with the decrease of the vacuum pressure. With the vacuum pressure increasing from 0.08 bar to 0.3 bar, the dry purity drops from 83.3% to 67.1%, and recovery drops from 72.5% to 37.2%. When the pressure of the vacuum and purge rises to 0.5 bar, dry purity and recovery fall to 51.7% and 17.3%, respectively. In conclusion, the results of Run 2 show improved separation performance, and vacuum pressure is initially determined as 0.08 bar.

4.2.2. Effect of Cycle Time on Performance of VSA. The recovery rate remains relatively low under the conditions of Run 2. The reason is that the long cycle time makes the gas escape out of the bed. The cycle time parameters of Runs 2, 7, 8, and 9 are shown in Table 8, and the unlisted operating parameters are the same as those of Run 2.

Table 8. Cycle time parameters Run 2 7 8 9

tcycle (s) 600 480 360 300

Tpre (s) 15 12 9 6

tad (s) 285 228 171 144

tvac (s) 60 48 36 30

tma (s) 120 96 72 60

tpur (s) 120 96 72 60

22


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Figure 12.

Dry purity and recovery rate of different cycles

Figure 12 indicates the separation and recovery rates obtained from Runs 7 to 9. The recovery rate reaches the maximum when the cycle time is 5 min and when the dry purity is at a minimum because a large amount of gas escapes from the bed when the sorption time increases. Moreover, the dry purity reaches the maximum when the cycle time is 8 min and the recovery rate is low. We can obtain the optimal cycle time when dry purity (83.81%) and recovery rate (83.37%) reach a high level at the same time from the figure. The optimal cycle time is 360 s.

4.2.3. Effect of Purge Ratio on Performance of VSA. This section mainly discusses the effect of purge ratio on the performance of VSA. The following operating parameters in calculations are the same as those of Run 8, except purge ratio. The results of dry purity and recovery rate in a stable cycle under different purge ratios are shown in Figure 13, and the collection time is 180 s. With the increase of purge ratio, the recovery increases while dry purity decreases. When the purge ratio is 0.6, the recovery can reach a high level of 94.5% while the dry purity is relatively low because the large purge ratio brings excessive nitrogen into the bed.

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Figure 13. Dry purity and recovery under different purge ratios

The collection time should be controlled reasonably to obtain a high dry purity in the case of a large purge ratio. The recovery is at the highest when the purge ratio is 0.6, but the process with a large purge ratio consumes excessive energy. Thus, we chose the process with the purge ratio of 0.4 to study the effect of collection time on dry purity and recovery rate. The calculation results on the effect of collection time on dry purity and recovery rate are shown in Figure 14. The highest purity is almost 95% and the recovery rate is approximately 67.7% when the collection time is 108 s. With the increase of collection time, the dry purity of the recovered gas decreases while the recovery rate increases up to 93.5% when the collection time is 180 s.

24


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Figure 14. Effect of collection time on dry purity and recovery of P/A=0.4

In engineering practice, the gas should be collected only under vacuum and vacuum maintenance stages to obtain high purity. The large purge ratio can be used to obtain a high recovery rate.

4.2.4. Effect of CO2 Concentration on Performance of VSA. This section mainly investigates the effect of CO2 concentration on separation and recovery. The calculation conditions are the same as those of Run 8 except the CO2 concentration.

Figure 15. Effect of CO2 concentration on separation and recovery performance

Figure 15 shows that recovery is 92.8% and dry purity is 69.3% when the concentration of CO2 is 6%. Moreover, recovery reduces to 70.8% and dry purity rises to 86.3% when the concentration of CO2 is 21%. Dry purity and productivity increase 25


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with the increase of CO2 concentration. Recovery decreases because more CO2 escapes out of the bed with the increase of CO2 concentration. Therefore, when the concentration proportion of H2O and CO2 in feed flue gas is between 1 and 1.5, high dry purity, recovery rate, and productivity can be obtained simultaneously.

5. CALCULATION RESULTS OF IMPROVED VSA PROCESS According to the preceding discussions, we obtain the best operation conditions at pl

=0.08 bar, p u =0.3 bar, and tcycle=360 s. The concentration proportion of H2O and

CO2 in the feed gas is between 1 and 1.5. In the practical engineering production, the operation conditions are always changing, which results in an unsatisfactory result. Moreover, the operation of vacuum consumes a large amount of energy. Two improvement operations in the sorption process are discussed in this section.

5.1. Effect of Pre-wetting Operation on Performance of VSA. The process of pre-wetting with saturated wet nitrogen at 333 K is added before the sorption stage to improve the performance of VSA. The following calculations are based on the operation conditions: YH2O=YCO2=10% and P/A=0.4. The unlisted parameters are the same as those of Run 8.

26


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(a)

(b) Figure 16. Performance of recovered gas under different pre-wetting times: (a) dry purity (collection time 108 s) and (b) recovery (collection time: 180 s).

Figure 16(a) shows that the dry purity of gas collected in vacuum and vacuum maintenance stages increases with the increase of the pre-wetting time. When the pre-wetting time reaches 0.9 min, dry purity is 91.5%, and dry purity increases slightly when the pre-wetting time is over 0.9 min. With the increase of pre-wetting time, a large amount of water is sorbed, which results in a large amount of CO2 being sorbed according to the mechanism of the stepwise reaction. An inflection point occurs in the recovery curve of Figure 16(b). The recovery reaches the maximum of 91.02% when the pre-wetting time is 0.9 min. 27


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With the continuation of pre-wetting operation, the heat released in the sorption of water causes the rise of bed temperature. The high temperature reduces the equilibrium sorption amount of CO2. Therefore, the optimal pre-wetting time is 0.9 min. Based on the optimal pre-wetting time, the dry purity and recovery results of the pre-wetting process under different H2O concentrations are shown in Figure 17. When the concentration proportion of H2O and CO2 is less than 1, the pre-wetting operation has a positive impact on the increasing dry purity and recovery rate. The ability of pre-wetting operation to improve the separation performance is limited when the concentration proportion of H2O and CO2 exceeds 1. The values of the dry purity and the recovery of the process that contains the pre-wetting operation are similar to those of the non-pre-wetting operation when the concentration of CO2 exceeds 10%. Consequently, the pre-wetting operation should be considered when the concentration proportion of H2O and CO2 is less than 1.

(a)

28


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(b) Figure 17. Performance of recovered gas under different H2O concentration conditions: (a) dry purity (collection time 108 s) and (b) recovery (collection time: 180 s)

5.2. Effect of Heat Enhancement Operation on Performance of VSA. VTSA technology simultaneously uses the vacuumizing and heating operation to improve the performance of the sorption process. The operating parameters of VTSA and VSA technology at the same conditions are listed in Table 9. YH2O=15%, YCO2=10%, and the unlisted parameters are the same as those of Run 8.

Table 9. VTSA and VSA operating parameters Process

VTSA

VSA

pl

(bar) 0.08 0.2 0.3 0.4 0.5 0.08 0.2 0.3 0.4 0.5

p u (bar)

0.3 0.3 0.3 0.4 0.5 0.3 0.3 0.3 0.4 0.5

Theating (K) 383 383 383 383 383 -

Tcooling (K) 333 333 333 333 333 -

Figure 18 shows the throughputs of H2O and CO2 calculated by VTSA and VSA, respectively. The throughput of H2O under the VSA process sharply decreases from 0.031 mol to 0.006 mol as the vacuum pressure increases from 0.08 bar to 0.5 bar. 29


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The throughput of H2O under the VTSA process slightly decreases from 0.043 mol to 0.033 mol. The trend of the change of throughput of CO2 is similar to that of H2O. In the condition of high vacuum pressure, the throughputs of H2O and CO2 of VTSA process is greater than that of the VSA process. The heat enhancement has a significant impact on the throughputs of H2O and CO2.

(a)

(b) Figure 18. Comparison of throughputs of (a) H2O and (b) CO2 in VTSA and VSA processes

Figure 19 shows the results of dry purity, recovery rate, and productivity in the VTSA and VSA processes, which decrease with the increase of vacuum pressure. The effect of increasing vacuum pressure on performance in the VTSA process is minimal

30


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compared with that in the VSA process. Thus, the recovery of VTSA at the pressure of 0.5 bar is 60%, whereas the recovery of VSA at the pressure of 0.2 bar is 52%. The dry purity of VTSA at the pressure of 0.5 bar is 72%, and the dry purity of VSA at the pressure of 0.2 bar is 68%. The reason is that the existence of thermal desorption operation increases the throughputs of H2O and CO2. Thus, the VTSA process can take advantage of the high vacuum pressure to reduce the high energy consumption from the vacuum pump.

(a)

(b)

31


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(c) Figure 19. Comparison of recovery performance between VTSA and VSA: (a) dry purity, (b) recovery, and (c) productivity

6. CONCLUSION This study presents an investigation of separating CO2 in the presence of H2O from flue gas using a fixed bed that is loaded with K2CO3/Al2O3. The thermodynamic and dynamic mathematical models of H2O and CO2 sorption on K2CO3/Al2O3 are established based on the stepwise reaction mechanism of CO2/H2O with K2CO3/Al2O3, and the models are verified by experimental data. In the numerical simulation of specific VSA conditions, the CO2 separation characteristics and performance that use K2CO3/Al2O3 are enhanced compared with that of 5A based on previous experimental data. By simulating the effects of operating parameters on the recovery performance of VSA, the optimal operating conditions are summarized as follows. The purge pressure is 0.3 bar, the vacuum pressure is 0.08 bar, and the sorption cycle duration is 6 min. Moreover, the presence of water is in favor of the sorption of carbon dioxide according to the stepwise reaction mechanism, and the concentration proportion of H2O and CO2 in the feed flue gas is advised to be larger than 1. 32


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In further research, two recommended operation conditions are proposed based on the principles of low energy consumption and easy operation. Under the condition that the concentration of water in the feed gas is low and the concentration proportion of H2O and CO2 is less than 1, the dry purity and recovery rate under the conditions of pre-wetting operation with wet nitrogen are larger than that under the conditions of the non-pre-wetting process. Thus, a pre-wetting step is added before the sorption process. Given the large energy consumption caused by the vacuum pump in the VSA process, the VTSA process can utilize high vacuum pressure, which can reduce energy consumption. The VTSA process at high vacuum pressure can reach the recovery effect of the VSA process at slow vacuum pressure.

AUTHOR INFORMATION Corresponding Author * Telephone: +86 10 62333792. E-mail: [email protected].

Notes The authors declare no competing financial interest.

ACKNOWLEDGEMENTS This work was supported by National

Key

R&D

Program

of

China

（No. 2016YFB0601102）.

33


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18-26. (16) Ruthven, D. M. Principles of adsorption and adsorption processes. Wiley, 1984; pp 49-52. (17) Zhao, C. W.; Chen, X. P.; Zhao. C. S. K2CO3/Al2O3 for capturing CO2 in flue gas from power plants. Part 1: Carbonation behaviors of K2CO3/Al2O3. Energy & Fuels

2012, 26(2), 1401-1405. (18) Jaiboon, O. A.; Chalermsinsuwan, B.; Mekasut, L.; Piumsomboon, P. Effect of flow patterns/regimes on CO2 capture using K2CO3 solid sorbent in fluidized bed/circulating fluidized bed. Chemical Engineering Journal 2013, 219, 262-272. (19) Liu, Z. Adsorption process for CO2 capture from flue gas of coal-fire power plant. Ph.D. Thesis, East China University of Science and Technology, May 2012.

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Numerical Investigations of CO2 Sorption and Recovery Process from

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