Post-Combustion CO2 Capture from wet Flue Gas by Temperature

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Post-Combustion CO2 Capture from wet Flue Gas by Temperature Swing Adsorption Max Hefti, and Marco Mazzotti Ind. Eng. Chem. Res., Just Accepted Manuscript • DOI: 10.1021/acs.iecr.8b03580 • Publication Date (Web): 17 Oct 2018 Downloaded from http://pubs.acs.org on October 25, 2018

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Industrial & Engineering Chemistry Research

Post-Combustion CO2 Capture from wet Flue Gas by Temperature Swing Adsorption Max Hefti and Marco Mazzotti∗ ETH Zurich, Institute of Process Engineering, Sonneggstrasse 3, CH-8092 Zurich, Switzerland E-mail: [email protected] Phone: +41 44 632 2456. Fax: +41 44 632 11 41 Abstract We present an analysis of a novel temperature swing adsorption (TSA) process with condensers capable of treating wet flue gas reaching 90 % CO2 -recovery and 95 % purity (on a dry basis). In the first part, the characterization of the binary CO2 /water vapor adsorption equilibrium on zeolite 13X is presented, quantifying residual CO2 adsorption at different levels of water adsorption. On this basis, we propose an empirical and analytical isotherm model able to capture the competition between CO2 and water vapor. In the second part, the isotherm model is used in a process simulator to assess the performance of the proposed TSA process in detail. The strict specifications on the CO2 -product could be reached by employing a layered-bed configuration, where a portion of the zeolite 13X bed is replaced by activated alumina. Further, the process is optimized by parametric analysis with respect to productivity and energy consumption while using the specifications as constraints. It is shown that reasonable performance can be obtained, comparable to the scenario where a drying-step precedes the cyclic adsorption process, but achieving this in a single process step. Moreover, the critical effect of the significant mass transfer resistance of water vapor on zeolite

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13X is quantified. Due to a spread of reported mass transfer coefficients of water vapor on zeolite 13X, the process is assessed for three representative values, showing that comparable performance can be obtained for all cases considered by varying the length of the guard-layer. The robustness of the process is further underlined by the good performance for varying concentrations of water vapor in the feed.

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1

Introduction

Recently, adsorption based separation processes aimed at CO2 -capture have received significant attention. Contrary to amine-based scrubbing processes, which represent the currently most advanced CO2 -mitigation option from large industrial sources, adsorption-based processes benefit from the non-volatility of the sorbent material. Indeed, this circumvents one of the main issues encountered in amine-based processes, namely, the solvent slip due to volatility. On the other hand, the process performance using solid sorbents is often heavily influenced by the presence of moisture in the feed. Numerous studies 1–7 dealing with the capture of CO2 by adsorption from a variety of streams have appeared, and promising results regarding product purity and recovery have been achieved. For example, Haghpanah et al. 4 modeled a VSA process for post-combustion capture assuming a CO2 /nitrogen feed and using zeolite 13X sorbent; they achieved a CO2 purity exceeding 95 % at recovery greater than 90 %. Merel et al. 1 performed cyclic TSA experiments using a CO2 and nitrogen mixture as a feed and zeolite 5A as sorbent material; they achieved high purity (≥ 94 %) at a recovery exceeding 80 %. In these studies, it is assumed that the feed to the adsorption unit has been pre-treated in a dryer, thus removing water entirely. Keeping in mind the scale at which CO2 capture processes will have to be operated, pre-drying will contribute significantly to both capital costs and operating costs. In a previous study 8 , it was demonstrated that the contribution of the pre-drying step may amount up to 30 % of the energy penalty. Likely, the overall costs could be reduced if the predrying step could be avoided and the feed entered the capture process as a moist stream. The combination of drying and CO2 capture into a single process has been investigated by only few researchers 9,10 . It is worth noting that even the case where the CO2 product were collected as a wet stream, i.e. containing water vapor, could still be preferable to having an upstream drying step. Instead of drying the entire stream fed to the capture unit, only the product stream would have to be processed. In fact, this would resemble the situation encountered in amine scrubbing processes, where the CO2 -product stream is saturated with water vapor at the exit temperature of the stripper or of the subsequent water wash.

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Drying of the feed stream could alternatively be integrated into the adsorption process by using a layered-bed configuration, as routinely employed in industrial processes, e.g. in air separation units by PSA/VSA by Air Products 11 . Various solid desiccants reaching very low dew-points (1 ppm H2 O) exist, e.g. these include activated alumina, silica gel and zeolites 4A or 5A 12 . The main objective of this study is to describe and to analyze an adsorption process that is capable of accepting wet flue gas, of separating CO2 from N2 , possibly producing a wet CO2 product, and to quantify the impact of the presence of moisture on the process performance. This article is structured as follows. In the next two sections, the experimental methods are briefly explained and pure component water vapor and binary CO2 /water vapor adsorption data on zeolite 13X are presented. Based thereupon, a simple and explicit isotherm model is proposed to describe the binary data, which is then used in the process calculations. In the second part, a novel TSA cycle with condensers is introduced that is capable of coping with a wet feed CO2 /nitrogen stream. A guard layer consisting of activated alumina is used to remove some of the water vapor present in the feed at the tail of the adsorption bed. It is shown that this cycle is capable of reaching high purity and high recovery at reasonable energy consumption.

2

Experimental

2.1

Materials and methods

The zeolite 13X sample consists of spherical pellets with a diameter ranging from 1.6 to 2 mm (ZeoChem, Switzerland); it belongs to the same batch as the sample used in our previous study 13 , where the adsorption equilibrium of CO2 and N2 as well as of their mixture was characterized. The pure component water adsorption measurements were carried out in a custom-built experimental setup as shown in Figure 1. At its core is a Rubotherm magnetic suspension balance (MSB) (Rubotherm, Germany), which is located in a circulation loop. Helium gas is used as an inert and is moisturized by bubbling it through a water tank, the temperature of which is controlled by a dedicated thermostat (Julabo, Germany). The adjustment of this temperature allows to set the partial pressure of water vapor in the gas phase. The dew point temperature of the gas phase is measured

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with a chilled mirror sensor (Michell Instruments, France). A more detailed description of the measurement principle is reported in a previous work 14 . Note that the excess adsorbed amount of water is obtained; however, all pure component water vapor adsorption measurements were done at ambient pressure. Hence, a negligible difference between absolute and excess adsorption is assumed below. While binary N2 and CO2 measurements have been reported in a previous work 13 , binary data of the co-adsorption of CO2 and water vapor on zeolite 13X is less readily available in literature, hence this system was characterized experimentally. The same setup was used to perform the binary CO2 /H2 O measurements according to the following protocol: The zeolite 13X sample was pre-loaded with water at a high loading. Then, the water tank was bypassed so as the amount of water in the system is constant and CO2 is introduced incrementally; the adsorbed amount of CO2 is obtained via a mass balance. This procedure was repeated after evacuating the system until the desired loading is obtained and helium was re-introduced at 1 bar. As it is of relevance for the measurement protocol, it is worth mentioning that there are two works on binary CO2 /H2 O adsorption on zeolite 13X with contrasting observations: Wang and LeVan 15 measured the CO2 /H2 O equilibrium using static experiments and reported a negligible change of the water loading upon increasing the CO2 partial pressure. They then proceeded with the assumption of constant water loading to measure CO2 adsorption at various water loadings. In contrast, Li et al. 16 performed breakthrough experiments and reported a slight reduction of the water capacity in the presence of CO2 . In our system, we established pure water equilibrium at high loading and continuously monitored the relative humidity upon increasing the CO2 partial pressure. The resulting change in the water loading was less than 0.1 %, similar to the results by Wang and LeVan 15 . Hence, we proceeded with this assumption and measured CO2 adsorption at lower water loadings where we were not always able to monitor the dew point due to the limitation of our dew point sensor.

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vacuum

M S B

TI

TI

H2O

gas

PI-H

rH-o rH-n

inner loop

PI-L

pump

Figure 1: Schematic of the static setup. All the piping and the valves are wrapped with heating wire and insulated. The gray-shaded areas indicate the locations of the thermostats. Abbreviations: rH-o, capacitive relative humidity sensor; TI, temperature indicator (thermocouple); rH-n, chilled mirror dew point sensor; PI-L, pressure indicator for pressures up to 3 bar; PI-H, PI for pressures up to 300 bar; MSB, magnetic suspension balance.

2.2 2.2.1

Adsorption isotherms on zeolite 13X Single component

The pure component adsorption equilibria of CO2 and N2 on zeolite 13X over a broad range of temperature and pressure have been reported in a previous work 13 . The pure component water vapor adsorption equilibrium data vs. the relative humidity at 25, 45 and 65◦ C are shown in Figure 2. The isotherms at the three temperatures collapse onto a single curve when shown against relative humidity x, which is defined as the ratio of the partial pressure of water vapor pw and the vapor pressure pvap at temperature T , i.e. x = pw /pvap (T ). Due to its low Si/Al ratio, zeolite 13X is hydrophilic, and it exhibits a rather large uptake capacity of water vapor, exceeding 16 mol/kg. The chilled mirror sensor was not able to measure the dew point when very low. At low water loadings, the interaction of water vapor and the zeolite is through a superposition of interactions between Na+ –H2 O and H2 O–H2 O 17,18 . In the plateau region above relative humidity of roughly 0.15, the additional water adsorbed is predominantly interacting with

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other H2 O molecules, and the network of adsorbed water molecules grows. When the relative humidity approaches unity, the adsorbed phase concentration increases due to clustering of the water molecules in the center of the super-cages of the zeolite framework 17,19 . A hysteresis loop was measured upon desorption of water vapor, as indicated by the open symbols in Figure 2. It is, however, very narrow and hardly visible on the scale of the adsorbed amount.

25 adsorption, n [mol/kg]

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


H2O adsorption on zeolite 13X

20

is work 25, 45, 65°C th

15 10 5 0 0

0.2

0.4

0.6

0.8

1

relative humidity, x [-] Figure 2: Pure component water adsorption and desorption data at three temperatures on zeolite 13X. The filled symbols correspond to adsorption measurements while the open symbols correspond to desorption measurements. Symbols: 25◦ C – , 45◦ C – , 65◦ C – .

p

2.2.2

q

f

Binary mixtures

The data of the excess adsorption of CO2 at 45◦ C and at six different water loadings, ranging from dry conditions to a water loading of 16.4 mol/kg, is shown in Figure 3 for the entire range of CO2 partial pressure investigated, i.e. up to 10 bar in Figure 3a, and a zoom up to 1 bar in Figure 3b. The circles in Figure 3 indicate the pure CO2 isotherms taken from our previous study 13 , while the other symbols represent the binary data. As expected, the CO2 adsorption capacity is reduced by the presence of pre-adsorbed water. The uptake capacity of CO2 with increasing water loading decreases monotonically, though not linearly (see below). This suggests that CO2 and H2 O compete for the same adsorption sites; evidence for this has been reported by Stevens

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et al. 20 using infrared spectroscopy measurements. These authors suggest further that significant amounts of pre-adsorbed water inhibits the formation of carbonates, which are observed for pure CO2 adsorption. Nonetheless, it is worth noting that for a water loading up to 7.3 mol/kg (and possibly beyond) the CO2 uptake capacity at 1 bar partial pressure is still higher than 1 mol/kg. Figure 4a shows the adsorption of CO2 in form of isobars vs. water loading; the experimental points of each isobar are connected by a dashed line to guide the eye. The isobar at 0.12 bar is representative for the partial pressure of CO2 in the feed of a coal fired power plant (as considered in this work), while 1 bar corresponds to the prevailing CO2 partial pressure during the regeneration step in the process investigated below. The isobar at 10 bar is shown to illustrate the trend at higher pressures, though this pressure is not relevant for post-combustion CO2 capture by TSA. At 0.12 bar the strongest decrease in the CO2 adsorption occurs at low loading, i.e. the amount of CO2 adsorbed at water loading 2 mol/kg is halved with respect to dry conditions. Such behavior has been observed in literature; Wang and LeVan 15 reported that the CO2 capacity dropped by 30 % when the water loading was 1 mol/kg. Similarly, Brandani and Ruthven 21 reported a strong inhibition of CO2 adsorption in the presence of small amounts of water vapor on zeolite NaLSX. In Figure 4b the residual CO2 loading defined as the CO2 adsorption under wet conditions normalized by the amount of CO2 adsorbed at the same partial pressure of CO2 under dry conditions is shown in a logarithmic scale. At each water loading investigated, the residual CO2 loading increases with the CO2 partial pressure. The residual CO2 loading at the lowest water loading (2 mol/kg) averaged over the entire range of pressures is approximately 66 %, while it reduces to 48 %, 30 % and 6 % at water loadings of 4.4 mol/kg, 7.3 mol/kg and 12.2 mol/kg, respectively. Notably, when the zeolite is almost saturated with water vapor, e.g. at 16.4 mol/kg loading, it loses its uptake capacity for CO2 almost entirely, the residual CO2 capacity being only 0.3 %. The binary CO2 isotherms shown in Figure 3 are less steep at low CO2 partial pressures than the pure component isotherm, suggesting that not only the CO2 uptake capacity is adversely affected by the presence of water vapor, but also its affinity towards the zeolite. Indeed, the Henry’s constant of CO2 with increasing water loading decreases exponentially. A similar result has been obtained by Brandani and Ruthven 21 for CO2 on zeolite NaLSX. These authors proposed that adsorbed water reduces the strength of the electric field surrounding the cations on the zeolite, and, as a

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consequence, its interaction with the quadrupole of the CO2 molecule is weakened, thus reducing the affinity for CO2 . 7 (a) 45°C 6

dry

5

2mol/kg

4

adsorption, n CO [mol/kg] 2


7

4.4

3

7.3

2 1 0 0.0

12.2 16.4

2.5

5.0

7.5

(b) 45°C 6 5 4 3 2 1 0 0.0

10.0

0.2

0.4

pCO [bar]

0.6

0.8

1.0

pCO [bar]

2

2

Figure 3: Experimental data of the CO2 adsorption on zeolite 13X at varying loading of water vapor (nw ) at 45◦ C up to 10 bar CO2 partial pressure (a) and up to 1 bar (b). Dashed lines in (a) connect the experimental points to guide the eye, while the solid lines in (b) correspond to the fit obtained using the model described in section 3.1.The numbers in the graph indicate the water loading nw : 0 mol/kg – , 2.0 mol/kg – ×, 4.4 mol/kg – 4, 7.3 mol/kg – +, 12.2 mol/kg – O, 16.4 mol/kg – . Pure component CO2 adsorption data were taken from a previous work 13 .

E

100%

7 (a) 45°C 2

6

2

5 4 3

(b)

50%

residual loading, n wet /n dry CO CO


1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


1bar

10bar

2 0.12bar 1

p CO

2

10%

1%

0.1%

0 0.0 2.0 4.4

7.3

12.2

16.4

2.0

water loading, n w [mol/kg]

4.4

7.3

12.2

16.4

water loading, n w [mol/kg]

Figure 4: (a) Isobars at 0.12 bar, 1 bar and 10 bar CO2 partial pressure as a function of the water loading. (b) Residual CO2 loading versus water loading. For each water loading, the partial pressure increases from the left bar to the right bar. The exact values are 0.12, 0.32, 0.58, 1.0, 1.92, 5.0 and 10.0 bar. Note that for the water loading 16.4 mol/kg only values at 0.32, 0.5 and 1.0 bar were measured.

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3

Modeling

3.1

Adsorption isotherms

Adsorption processes depend heavily on the description of the adsorption equilibria of the components present in the feed gas. Here, the flue gas is assumed to consist of a mixture of CO2 , N2 and water vapor. The adsorption models presented below rely on data measured in our laboratory (zeolite 13X) as well as on literature data (activated alumina F-200). A comparison of the pure component equilibria of CO2 and N2 and of water vapor on these two sorbents for exemplary conditions is shown in Figure 5a and 5b, respectively.

3.1.1

Zeolite 13X

Standard approaches such as the extended Sips equation as used for CO2 and N2 overestimate the extent of adsorption of CO2 in the presence of H2 O dramatically. Other approaches to describe multicomponent adsorption equilibria are available, e.g. real adsorbed solution theory 22 , the Virial excess mixture coefficient model 15 or the multisite occupancy model 23 . However, these models are not explicit and require an iterative procedure to calculate the adsorbed amounts, and as a result, they come at a significant computational cost when used in a process simulator. For process simulations having an explicit description of the adsorption isotherms is highly desirable. To the best of our knowledge there is no “off the shelf” explicit isotherm model that yields a satisfactory description of the binary CO2 and H2 O adsorption data. It is worth noting that we did not succeed in describing our mixture data using a dual site Langmuir approach, in particular the CO2 adsorption data at the highest loading, as used by Krishnamurthy et al. 10 to fit the data by Wang and LeVan 24 . Hence, we have developed and applied a simple and explicit isotherm model that captures the behavior observed in the experiments. Based on the binary experiments above we assume that the adsorption of water vapor is not influenced by the presence of CO2 , thus the amount of water vapor adsorbed from a mixture is assumed to be identical to that adsorbed by water vapor at the same partial pressure, according to its pure component isotherm. An isotherm model capturing the features of pure component water

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vapor adsorption as described above is the Guggenheim–Anderson–de Boer (GAB) model:

nw (x) =

n∞ w Hw x (1 − kx) (1 + (Hw − k)x)

with x =

p H2 O pvap (T )

(1)

where Hw describes the affinity towards the empty adsorption sites (presumably the cations on the zeolite), whereas k accounts for the formation of the water clusters. Moreover, the fact that the data collapse onto a single curve when shown against relative humidity suggests that, on average, the temperature dependence can be accounted for through the vapor pressure of water, consistent with literature data 25,26 . Indeed, this three-parameter isotherm is able to describe the adsorption data satisfactorily at the three temperature levels investigated, as shown in Figure 5b; the values obtained by performing the maximum likelihood estimation 13 with the pure component data at 25 ◦C, 45 ◦C and 65 ◦C are n∞ w = 15.42 mol/kg, Hw = 96.80 and k = 0.13. As the hysteresis loop is narrow, we do not account for it in the isotherm model, contrary to the case of activated carbon 14 . The binary measurements of CO2 and water vapor presented above revealed that not only the uptake capacity of CO2 was adversely affected, but also its affinity. Thus, the isotherm model should incorporate both these effects. One way to achieve such behavior is to introduce a dependence on the water loading, nw . In our previous study 13 , we have shown by multicomponent adsorption experiments that the binary adsorption of CO2 and N2 below 3 bar follows closely the prediction of the extended Sips model, hence we used this as a basis and introduced the dependence on nw in the following simple manner: c(T ) n∞ i (T, nw ) (bi (T, nw )pi ) c(T ) , c(T ) 1 + bCO2 (T, nw )pCO2 + bN2 (T, nw )pN2 n∞ T ∞ ∞ ∞ i (T ) ni (T, nw ) = , with ni (T ) = nref,i exp χi −1 , 1 + αnw Tref Qb,i , bi (T, nw ) = bi (T ) exp (−βnw ) , with bi (T ) = b0,i exp RT

ni p, T, nw = where and

(2)

where p = pCO2 , pN2 and i is either CO2 or N2 . Hereby it was assumed that the water vapor affected N2 in a similar way as CO2 ; the effect of such rather arbitrary assumption is negligible because the adsorption of N2 is anyhow very low in the presence of CO2 even when water vapor is absent.

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Equation (2) exhibits the desired characteristics: Importantly, the isotherm reduces to the correct binary Sips isotherm when water vapor is absent, i.e. for nw = 0 mol/kg. Secondly, the capacity n∞ i (T, nw ) reduces with increasing water loading, as observed in the data shown in Figure 3a. Finally, the affinity constant bi (T, nw ) is defined so as to decrease exponentially with increasing water loading, inspired by the observation of the exponential dependence of the Henry’s constant on nw . The specific functional forms used for n∞ i (T, nw ) and bi (T, nw ) are empirical; although others are plausible as well, we do not believe that the data available allow discriminating among different possible functional forms. The parameters n∞ ref,i , χi , b0,i , Qb,i correspond to the pure component parameters taken from our previous study 13 . In addition, equation (2) has two fitting parameters, i.e. α and β, which are assumed to be temperature-independent and were estimated by performing the maximum likelihood estimation 13 with the binary CO2 /H2 O data up to 2 bar. The data at higher pressures were not considered because they are not relevant for the process investigated in this work. Moreover, this allowed to improve the fit within the range of interest. Note that we obtained the parameters from fitting the excess adsorption directly. This is reasonable for pressures up to 2 bar; in addition, in this way, no assumptions with regard to the adsorbed phase density were required (the reader is referred to existing literature for a discussion on this topic 13,27,28 ). The estimated values of the parameters are α = 1.63 and β = 8.1, and the corresponding fits are shown as solid lines in Figure 3b. As expected, the model is able to describe the trends, i.e. the reduction in the capacity as well as in the affinity. The quality of the description of the binary data is reasonable. To obtain a more accurate description, however, more parameters or a different model would be necessary. Nonetheless, we do make use of this model because of its good description of the binary data and of its simplicity.

3.1.2

Activated alumina F-200

The adsorption equilibrium of CO2 , N2 and water vapor on activated alumina F-200 has been characterized by Li et al. 29 . Figure 6 shows the CO2 adsorption data measured by these authors.

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5

CO2, N2 adsorptionn 13X CO 2 o

25

4 3 2 1

CO2 on AA

30°C Li et al. (2009) N2 on 13X 45°C Hefti et al. (2015)

0 0

0.2

0.4

H2O adsorption

45°C Hefti et al. (2015)

adsorption, n [mol/kg]

adsorption, n [mol/kg]

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


0.6

0.8

20 zeolite 13X

15

25, 45, 65°C this work AA

10

20, 25, 30°C Li et al. (2009)

5

20°C 25°C 30°C

0

1

0

0.2

pressure, p [bar]

0.4

0.6

0.8

1

relative humidity, x [-]

(a)

(b)

Figure 5: (a) Pure component adsorption isotherms of CO2 and N2 and (b) of water vapor on zeolite 13X and activated alumina (AA). Note that the water vapor adsorption is shown against relative humidity because the isotherms of zeolite 13X and AA collapse onto a single curve for different temperatures. Symbols in subfigure (b): 20◦ C – , 25◦ C – , 30◦ C – , 45◦ C – , 65◦ C – . Open symbols denote desorption measurements.

s

p

u

q

f

The solid lines represent the Langmuir isotherm fit using their parameters given by:

nCO2 =

nref s(T )pCO2 1 + s(T )pCO2

(3)

where s(T ) follows the same dependence on temperature as reported in equation (2). It should be noted that the CO2 data by Li et al. 29 were measured at 273.15 K and 303.15 K. In the process simulations shown below we need to extrapolate this temperature window significantly, thus a comparison with measurements presented at a higher temperature as presented by Rege et al. 30 was made. These authors measured the CO2 uptake up to 343 K, and their data are shown as diamonds in Figure 6. The prediction made by the Langmuir model using the parameters by Li et al. 29 is shown as a dashed line; the agreement of prediction and data at 343 K is reasonable, even though the model underestimates the CO2 uptake significantly at low partial pressure. The adsorption of N2 on AA was measured by Li et al. 29 and Rege et al. 30 . In both works very little N2 adsorption was reported. Therefore, negligible adsorption of N2 on AA is assumed in this work.

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Water vapor adsorption isotherms were also reported in Li et al. 29 , and a reasonable description using the GAB-isotherm given by: nw,ref r1 pw (1 − r2 pw ) (1 − r2 pw + r1 pw ) Ei with ri = ri,0 exp RT

nw =

(4)

was obtained. The adsorption data from these authors vs. relative humidity are shown in Figure 5b along with their description provided by equation (4). It is worth noting that there exists a small hysteresis loop in the adsorption of water vapor on AA. Due to the lack of data, however, it was not possible to include this into the description of the equilibrium 31 . Finally, Li et al. 29 modeled the binary adsorption of CO2 and H2 O by an explicit isotherm model, termed realistic interactive LBET model (RLBET):

nw =

nw,ref r1 pw (1 + rCO2 pCO2 ) (1 − r2 pw )[1 − r2 pw + r1 pw + r1 pw rCO2 pCO2 + spCO2 (1 − r2 pw )]

nCO2 =

nref spCO2 (1 − r2 pw ) + nref,cw r1 pw rCO2 pCO2 1 − r2 pw + r1 pw + r1 pw rCO2 pCO2 + spCO2 (1 − r2 pw )

(5)

(6)

The only parameter that was fitted to describe the competition is rCO2 . The values for the parameters are those from Li et al. 29 . Equations (5) and (6) are used in the scope of this work to describe the competitive adsorption of CO2 and water vapor on activated alumina.

3.2

Mass transfer

For CO2 on both zeolite 13X and activated alumina F-200 the same mass transfer coefficient was used as in our previous study 8 . The mass transfer coefficient of N2 was chosen so as to be inline with literature 7,32 ; all values are reported in Table 1. Less straightforward was choosing a mass transfer coefficient for water vapor on zeolite 13X. In fact, the reported values of mass transfer coefficients for water vapor adsorption on zeolite 13X, kH2 O , exhibit a major spread in available literature. Ribeiro et al. 33 presented breakthrough experiments and extracted values for the film mass transfer coefficient as well as for the homogeneous diffusivity (Dh ), which is used to determine

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2 CO2 adsorption, n [mol/kg]

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


CO2 on AA

1.5 0°C Li et al. (2009)

1

30°C Li et al. (2009)

0.5

0) al. (200 (2009) Rege et °C 0 7 f Li et al. o : l e d o data m y iction b line: pred

0 0

0.2

0.4

0.6

0.8

1

CO2 pressure, p [bar] Figure 6: CO2 adsorption equilibrium data of Li et al. 29 and Rege et al. 30 . The Langmuir fits using the parameters of Li et al. 29 at 0◦ C and 30◦ C are shown as solid lines, while the dashed line represents the model prediction at 70◦ C.

the macropore diffusion resistance. According to their results, the film diffusion resistance was negligible, and the mass transfer of water vapor to zeolite 13X is dominated by the macropore diffusion resistance. They used the widely known Glueckauf 34 approximation to determine kH2 O : 1 kH2 O

=

d2p 4ΩDh

(7)

where dp corresponds to the particle size, and the geometric factor Ω is equal to 15 in the case of spherical particles. Ryu et al. 35 measured water vapor uptake curves on zeolite 13X using the gravimetric method and compared a variety of models to describe the kinetics of the uptake, thus concluding that the LDF model (expressing kH2 O by equation (7)) gave a good description of the uptake curves. Ahn and Lee 36 studied the water vapor-zeolite 13X system in the context of an air drying process. They, too, determined the value of kH2 O considering macropore and film-diffusion limitations. A summary of the values for the homogeneous diffusivity (Dh ) along with the relevant references is given in Table 2; these values were then used to determine kH2 O for an average particle size of 2 mm as reported in the last column of Table 2. It stands out that the values of kH2 O determined by uptake measurements of Ryu et al. 35 are considerably higher than those estimated from the

15



Page 16 of 39

breakthrough experiments by Ribeiro et al. 33 . The value used by Ahn and Lee 36 is closer to the one by Ribeiro et al. 33 than to that of Ryu et al. 35 . The results of fixed-bed experiments reported by Ribeiro et al. 33 were used to estimate the mass transfer coefficient for water vapor on activated alumina (Table 1); this value was held constant in the simulations below. Table 1: Material related parameters. zeolite 13X activated alumina F-200 material density [kg m ] 2359 2910 particle density [kg m−3 ] 1085 1280 bed density [kg m−3 ] 708 835 particle diameter [mm] 2 2 heat capacity sorbent [J (kg K)−1 ] 920 1260 heat of adsorption CO2 [kJ/mol] 37a 27.5c heat of adsorption N2 [kJ/mol] 18.5a heat of adsorption H2 O [kJ/mol] 43.3a 55c −1 mass transfer CO2 [s ] 0.15 0.15 mass transfer N2 [s−1 ] 0.5 – mass transfer H2 O [s−1 ] section 3.2 3.6 × 10−3 for CO2 and N2 obtained via the van’t Hoff equation 39 using the pure component Sips isotherm parameters of Hefti et al. 13 ; for H2 O the Wagner equation 40 was used to calculate the vapor pressure taken from Li et al. 29 −3

a

c

Table 2: Overview of the values for the homogeneous diffusivity, and calculated mass transfer coefficients for particle size 2 mm. reference

Dh [×10−11 m2 s−1 ]

method

kH2 O [×10−4 s−1 ]

Ryu et al. 35 46.2–66.8 uptake measurementsa 69–100 12 Ahn and Lee 36 9.7 Ruthven 15 33 Ribeiro et al. 5.5 breakthrough experiments 8.3 a Ryu et al. 35 reported values for Dh at temperatures between 298–318 K. Hence, the range including the lowest and the highest values is indicated here.

3.3

Column model

A one-dimensional detailed model of the adsorption column is used in this work. An extensive description as well as a discussion about its accuracy in describing a TSA cycle by comparison to experiments have been presented in previous works 2 . For the sake of completeness, we restate the most important assumptions: • radial gradients of concentration, velocity and temperature are neglected,

16


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• the solid and fluid phases are in thermal equilibrium, • the linear driving force (LDF) model for mass transfer applies, • the isosteric heat of adsorption, the molar heat capacities, the viscosity and the heat and mass transfer coefficients are constant, • longitudinal gradients of the heat exchange fluid are neglected. The model was extended to incorporate the ability to accommodate different layers within the column. Each layer consists of a fraction of the adsorption column with specific physical parameters (particle density, material density, solid heat capacity) and thermodynamic properties (isotherm, heat of adsorption, mass transfer coefficients). Applying the finite volume method, the differential algebraic equations (PDAEs) describing mass and energy balances were discretized in space into 30 equally sized cells 37 . The WENO 4 flux limiter scheme was used to determine the fluxes at the cell boundaries within the column. This method can also be applied to a layered-bed configuration. The fluxes at the cell boundary that comprises the interface of two adjacent layers is approximated containing properties of both layers. A more detailed description of how the finite volume method is implemented can be found elsewhere 4,37 . The PDAEs are solved for one column sequentially until a cyclic steady state (CSS) is reached, with the appropriate boundary conditions reflecting the sequence of steps and the choice of operating conditions. CSS is considered to be reached 2 when the relative change in the internal composition and temperature profiles between the current and the previous cycle is less than 10−5 . The error in the overall mass balance and in the product composition of each product stream has to be less than 1 % 38 .

3.4

Performance indicators

Since this work aims at post-combustion capture, carbon capture and storage (CCS) specifications were assigned, namely that the purity and the recovery are equal to or larger than 95 % and 90 %, respectively 10 . It is, however, not sufficient to consider the specifications alone because the expenditures are governed by and large by the productivity and the energy consumption. Hence,

17



Page 18 of 39

we consider four performance indicators to assess and compare the process considered in this work, i.e. the purity of the CO2 product (Φ), the CO2 recovery (r), the productivity (Pr) and the thermal energy consumption of the process (eth ), which are defined below:

Φ=

P NCO

2

(8)

P NCO + NNP 2

r=

2

P NCO

2

(9)

F NCO

2

Pr =

eth =

Z

1 P NCO

2

P NCO

2

(10)

Vbed tcycle tcycle

max(0, Q˙ in ) dt

(11)

0

P where NCO is the amount of CO2 produced from one column during one cycle and collected in 2

F the target product, NNP is the amount of N2 collected in the same target product, and NCO is the 2

2

amount of CO2 fed to the process during one cycle. Note that the purity Φ according to equation (8) is calculated on a dry basis, i.e. the water content in the CO2 product is not considered. The productivity is expressed per volume of a single adsorption column (Vbed ) and cycle time (tcycle ), i.e. the sum of the individual step times; we did not account for idle times which arise from the scheduling, therefore we provide only the upper limit of the achievable productivity. The specific thermal energy consumption of the TSA unit is determined by integrating the heat flow into one column (Q˙ in ) during a cycle. In this work, the process performance is assessed for the dimensions and model parameters summarized in Tables 1 and 3 by extensive parametric analysis, exploring a wide range of operating conditions, more specifically the times of the individual steps of the TSA cycle. Representing the resulting energy consumption vs. productivity allows to identify two regions, i.e., one, for which feasible operating conditions exist, and another, for which no such conditions exist. The regions are separated by a set of points, commonly referred to as pareto frontier. No better operating points than those on the pareto frontier are obtained within the range investigated. Note that along a

18


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pareto frontier the improvement of one indicator can only occur at the expenses of the other, thus representing, in our case, the trade-off between energy consumption and productivity. Table 3: Model parameters: setup dimensions and properties of the feed. Parameter Value Column geometry length 1.2 m internal radiusa 15 × 10−3 m external radiusa 16 × 10−3 m heat capacity wall 4 × 106 J/(m3 K) heat transfer fluid/wall 100 W/(m2 K) heat transfer wall/bed stagnant 20 W/(m2 K) heat transfer wall/bed convective 20 W/(m2 K) cooling temperature (Tcool ) 300 K heating temperature (Theat ) 440 K condenser temperature (THEX ) 293 K Feed temperature 303 K pressure 1.3 bar flow rate 3.5 × 10−4 m3 /s a These dimensions correspond to those of a shell and tube type heat exchanger, where the adsorbent is packed within the tubes

4

Design and development of a TSA process

4.1

TSA cycle

In a previous work 8 we analyzed in detail a simple 4-step TSA cycle (see Figure 7) consisting of an adsorption, a heating and a cooling step, aimed at recovering CO2 from the flue gas of a coal-fired power plant after the moisture is removed in an upstream drying step. There, for the sake of comparison with MOF-materials for which only limited nitrogen adsorption data were available in literature, we neglected nitrogen adsorption. Under those conditions, the 4-step cycle was shown to fulfill CCS specifications. Here, a more complex system is investigated. A ternary feed mixture to the TSA unit is considered, i.e. consisting of CO2 , nitrogen and water vapor; hence to fulfill the specified purity and recovery a more sophisticated cycle is necessary. A promising option is the 6-step cycle 41,42 shown in Figure 8, which exhibits three additional “features” as compared to the 4-step cycle: • The first addition consists of the internal recycle, i.e. the connected columns during the purge (P) and the recycle (R) step. On the one hand, the motivation for the internal recycle

19



is based on the observation that the gas phase is rich in CO2 after the regeneration. Hence, this portion is re-used in the recycle step to enrich the adsorbed phase in CO2 . On the other hand, the outlet of the recycle step is used as a purge to remove residual CO2 after the regeneration step, thus preventing CO2 losses. • The second addition is a double heating step, where the CO2 -rich portion withdrawn during the first heating step is mixed with the feed. This has two advantages. First, it increases the molar fraction of CO2 in the feed to the adsorption step (A) and second, it allows collecting the CO2 product at high purity during the second heating step (HII ). On the downside, such addition reduces productivity. • To deal with the water vapor in the recycle streams, the 6-step cycle features two condensers, which constitute the third addition. The outlet of the purge step (Ps) contains significant amounts of water vapor because the column is still at an elevated temperature after the second heating step. Since this stream enters the recycle step, which is at low temperature, water vapor would condense close to where the feed enters, hence, a condenser is used to reduce the amount of water vapor. A condenser temperature of 293 K is assumed, and the resulting stream contains water vapor at the partial pressure corresponding to the vapor pressure at this temperature. Before re-entering the process, the stream is moderately heated (by 2 K) to avoid relative humidity of 1. A second condenser treating the outlet stream of the first heating step (HI ) is used. It is further assumed that the liquid stream leaving a condenser consists of pure water, dissolution of the other gaseous components being neglected.

20


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waste

C

H

A

Ps

CO2

feed

Figure 7: 4-step TSA cycle considered in Hefti et al. 8 consisting of the following steps: adsorption (A), heating (H), closed cooling (C) and pressurization (Ps).

waste

A

R

HFP

feed

HSP

CO2/H2O

P

C

H2O

H2O Figure 8: 6-step TSA cycle consisting of the following steps: adsorption (A), recycle (R), double heating (HFP/SP ), purge (P) and open cooling (C).

21



5

Process analysis

In the following analysis, using the adsorption cycle proposed in Figure 8, we show that there exist operating conditions that allow to treat wet flue gas while fulfilling the specifications, i.e. recovery ≥ 0.90 and purity ≥ 0.95. Process performance in terms of productivity and energy consumption is quantified by varying the step times and the length of the alumina layer, LAA , whose value is a priori unknown. The total length of the column was kept constant at 1.2 m. No constraints on the concentration of water vapor when it breaks through the activated alumina layer were imposed, as is sometimes done when dealing with layered beds 10 . The case of a moist flue gas from a coal fired power plant is considered, i.e. a CO2 /N2 stream (12:88 v/v on a dry basis) containing water vapor corresponding to 95 % relative humidity at feed conditions (yH2 O ≈ 3.1 % on a volume basis), which is fed at a temperature of 303 K. Two further scenarios varying the content of water vapor in the feed are discussed in section 5.2. In the results presented below, to achieve a reasonable productivity, the step times of the heating and cooling steps were limited to 3000 s. A preliminary sensitivity analysis revealed that a reasonable duration of the connected purge/recycle steps was 25 s, yielding good performance for a wide range of operating conditions; hence, it was fixed at this value. As discussed in section 3.2 a range of values for the mass transfer coefficient of water vapor on zeolite 13X, kH2 O , is reported in the literature. As a consequence, since its value has a strong impact on the overall performance, it is appropriate to analyze the process for different values of kH2 O . We start the analysis with a representative value of 10−3 s−1 ; then the process performance for a higher and an even lower value of kH2 O , i.e. 7 × 10−3 s−1 and 6 × 10−4 s−1 , will be analyzed. Figure 9a illustrates the process performance of the proposed 6-step cycle in the productivityenergy consumption plane for different configurations of the bed. Considering the scenario where the activated alumina layer is 6 cm first, a cloud of operating points that satisfy the specifications, but are not optimal, is shown. This cloud is delimited by an envelope of connected points, i.e. the operating conditions that give the best performance and is referred to as pareto frontier. For readability the point clouds are omitted for all other configurations, where only the pareto frontiers are shown.

22


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To show the effect of the length of the activated alumina segment, pareto frontiers for two additional lengths are shown. When the fraction of activated alumina is 6 cm and 30 cm a similar minimal energy consumption of 5.25 MJ/kgCO2 is obtained. The productivity is slightly higher for 30 cm (41.4 kgCO2 /(m3 h)) than for 6 cm (38.7 kgCO2 /(m3 h)). When the fraction of activated alumina is in between, e.g. 14 cm, the energy consumption can be reduced by an additional 10 %, resulting in 4.85 MJ/kgCO2 ; the improvement in productivity is marginal, namely 41.9 kgCO2 /(m3 h). A physical explanation for the behavior of the process performance can be obtained by analyzing the profiles of the adsorbed phase concentration along the column at cyclic steady state (see Figure 9b). Such profiles are shown for the adsorption step (step A in Figure 8) for the same configurations of the bed as indicated in Figure 9a. For each configuration, conditions corresponding to the operating point with the lowest energy consumption on each pareto frontier were chosen. The fraction of activated alumina is shown as shaded area in Figure 9b, while the remaining fraction of the bed contains zeolite 13X. For each configuration, three profiles of CO2 and H2 O corresponding to different points in time during the adsorption step (N2 profiles are not visible on the scale used, hence they are not shown). The thin solid lines correspond to profiles at the beginning of the step, the dashed lines to profiles calculated at intermediate points in time, and the thick lines are profiles at the end of the step. It can readily be observed that the bed is divided into a wet region, i.e. where water vapor is adsorbed, and a dry region, i.e. where it is not. The transition between these regions occurs within a narrow zone of the bed, i.e. where the adsorbed amount of water vapor drops and that of CO2 increases. As a result of the strong competition between water vapor and the other species, the adsorbed phase in the wet region consists of water vapor almost entirely. Because of this, separation between CO2 and nitrogen takes place only along the dry region. The performance of the separation can be improved by containing the water front in a narrow fraction of the bed, hence by maximizing the dry region. Note that due to the adsorption properties there is no notable separation between CO2 and nitrogen in the activated alumina fraction. Comparing the three, it is apparent why the intermediate case, i.e. LAA = 14 cm, performs best: The fraction of the bed available for CO2 /nitrogen separation is the highest, i.e. more than 80 %. In the LAA = 6 cm case, significantly more water is present in the zeolite layer, and less than 78 % of the bed is available

23



for CO2 /nitrogen separation. On the other hand, only 75 % of the bed is available for the same separation for LAA = 30 cm. This analysis shows that the best performance is obtained when part of the water is allowed to break through the alumina layer and be contained in the zeolite fraction.

1.2

9 kH 2O =

zeolite 13X

10-3 s-1

1.0

7 AA(30cm)/13X

AA(6cm)/13X

5

AA(14cm)/13X

axial position [m]

Energy consumption, etot [MJ/kgCO2]

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 24 of 39

0.8

0.6

CO2

CO2

0.4 LAA: 30 cm

0.2

3

purity ≥ 0.95 recovery ≥ 0.90 0

0.0

20 40 Productivity, Pr [kgCO2/(m3h)]

60

H 2O

LAA: 14 cm

γ-Al2O3

LAA: 6 cm

0

7.5

15 0

7.5

15 0

7.5

15

nads [mol/kg]

(a)

(b)

Figure 9: (a) Specific energy consumption vs. productivity for kH2 O = 10−3 s−1 for different configurations of the adsorption bed. (b) Internal profiles of the adsorbed phase concentration for the adsorption step (step A in Figure 8) at cyclic steady state. The fraction of activated alumina is shown as shaded area, while the remaining fraction of the bed contains zeolite 13X. For each configuration three profiles are shown for CO2 and H2 O corresponding to different points in time during the duration of the adsorption step (N2 profiles are not visible and hence are not shown). The thin solid lines correspond to profiles at the beginning of the step, the dashed lines to intermediate times and the thick lines are profiles at the end of the step.

5.1

Role of mass transfer

Next we investigate the critical role of the mass transfer coefficient of water vapor on zeolite 13X, kH2 O , by repeating the analysis above for a lower and a higher value of kH2 O , namely 6 × 10−4 s−1 and 7 × 10−3 s−1 . These values were chosen on the basis of the discussion in section 3.2.

24


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In Figure 10 the process performance for the three values of kH2 O are shown, increasing from left to right. For each kH2 O , pareto frontiers of the layered-bed configuration leading to the best performance are shown. A summary of the numerical values for the performances at the outer-most points of the pareto frontiers are reported in Table 4. The fact that for all three cases considered feasible operating points at comparable performance are obtained shows that the layered-bed configuration of the TSA cycle at hand provides a robust approach to run the separation process. Altering the length of the activated alumina fraction allows to compensate for possible uncertainties in the mass transfer rate of water vapor. Indeed, the lowest energy consumption of each case considered varies within only about 0.5 MJ/kgCO2 . Again, the lesser spread of the water front within the zeolite fraction of the bed explains the slight improvement of the minimal energy consumption when the mass transfer is higher. For the same reason, maximum productivity increases from 40 kgCO2 /(m3 h) when kH2 O = 6 × 10−4 s−1 to 50 kgCO2 /(m3 h) when kH2 O = 7 × 10−3 s−1 ; these observations show that a high mass transfer rate for water vapor is desired. In the limiting case when there is no mass transfer limitation, the performance is determined by the thermal properties of the system (heat transfer rates and heat of adsorption) and the uptake capacity of the adsorbent. Table 4: Overview of the process performance obtained for three values of the mass transfer coefficient of water vapor on zeolite 13X, reporting the minimal energy consumption and maximum productivity in dimensions MJ/kgCO2 and kgCO2 /(m3 h), respectively. mass transfer coefficient H2 O on zeolite 13X 6 × 10−4 s−1 10−3 s−1 7 × 10−3 s−1 (emin th ,Pr) (eth ,Prmax )

5.2

(5.05,23.50) (5.65,39.99)

(4.86,23.55) (5.23,40.89)

(4.52,25.89) (5.16,48.95)

Role of water content in the feed

Finally, we investigate the performance of the cycle when feed conditions vary. Two additional concentrations of water vapor in the feed are considered, i.e. yH2 O = 1.5 % and yH2 O = 4.5 % on a volume basis. The molar flow rate of CO2 was held constant for the three concentrations by adjusting the feed velocity.

25



7

AA(14cm)/13X

5

3


9

7

AA(14cm)/13X

5

3

20 40 60 Productivity, Pr [kgCO2/(m3h)]

kH2O = 10-3 s-1



9 Energy consumption, etot [MJ/kgCO2]

kH2O = 6 × 10-4 s-1


9 Energy consumption, etot [MJ/kgCO2]

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 26 of 39

kH2O = 7 × 10-3s-1

7

5 AA(6cm)/13X

3



Figure 10: Specific energy consumption vs. productivity for different values of the mass transfer coefficient of water vapor on zeolite 13X, kH2 O , i.e. 6 × 10−4 s−1 , 1 × 10−3 s−1 and 7 × 10−3 s−1 .

The resulting pareto frontier for varying feed concentrations are shown in Figure 11 for two values of kH2 O , 10−3 s−1 and 7 × 10−3 s−1 . For each feed concentration, the activated alumina/zeolite 13X configuration pareto leading to the best performance is shown. The results demonstrate the robustness of the investigated cycle, as operating points fulfilling the constraints are found for the entire range of feed conditions considered. The results show also that the process performance is penalized with increasing moisture content in the feed, as expected. As indicated in the figure, the length of the activated alumina section leading to the best performance increases with the concentration of water vapor in the feed because a greater fraction of activated alumina in the bed is required to prevent the water front from penetrating the zeolite fraction too far. Moreover, the increase in energy penalty due to a higher moisture content in the feed is more pronounced when the mass transfer resistance is higher.

26


Page 27 of 39

9

9

kH2O = 10-3 s-1

7 yH2O: 4.5% AA(20cm)/13X

5

yH2O: 3.3% yH2O: 1.5%

AA(14cm)/13X AA(6cm)/13X

purity ≥ 0.95 recovery ≥ 0.90

3 0



1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


kH2O = 7 × 10-3 s-1

7

yH2O: 4.5% 5

AA(10cm)/13X AA(6cm)/13X

purity ≥ 0.95 recovery ≥ 0.90

3


60

0

yH2O: 3.3% yH2O: 1.5%

AA(6cm)/13X


60

Figure 11: Specific energy consumption vs. productivity for different values of the mass transfer coefficient of water vapor on zeolite 13X, kH2 O , i.e. 1 × 10−3 s−1 and 7 × 10−3 s−1 , at three feed concentrations of water vapor, i.e. yH2 O = 1.5 %, 3.3 % and 4.5 %. For each value of kH2 O , pareto frontiers are shown for the layered-bed configurations that lead to the best process performance.

6 6.1

Discussion Discussion of the TSA-process

The traditional strategy of coping with water vapor in the feed in the context of CO2 -capture processes by adsorption is to employ an upstream drying process followed by a second process step in which the CO2 -separation occurs. Here, we present a process that can cope with wet flue gas and achieve strict specifications on the CO2 product in a single process step. These two concepts are shown conceptually in Figure 12. The innovative aspect of the process considered here is the combination of a layered-bed configuration and the use of condensers in the recycle streams that originate from a column at high temperature. This allows to remove moisture from the process continuously, and ultimately allows to treat a moist feed stream within a single unit operation, while reaching satisfactory performance. Indeed, when using the same black box model for the drying unit with an energy penalty of removing moisture from the feed of 8 MJ/kgH2 O removed as in Hefti et al. 8 preceding the 6-step TSA cycle in Figure 8, a minimal energy consumption of 4.15 MJ/kgCO2 is obtained to which the contribution of the drying step is 30 %. Hence, it is slightly lower than obtained with layered beds. Note, however, that the energy penalty of removing the moisture is

27



subject to the specific process adopted. Thus, the layered bed process considered here comes at the expense of a higher energy consumption, but it ”saves” an entire (drying) process. Which of the two scenarios is the preferred option depends on numerous factors, for example the availability of equipment and the requirements of the products. Note that activated alumina is an exemplary desiccant and other layer materials are possible, e.g. silicas. A desiccant with a different isotherm shape would result in different profiles (Figure 9) and thus could lead to different performance. A major reason for choosing activated alumina was the availability of a multi-component isotherm model 29 , notably considering the co-adsorption of CO2 and water vapor. From the results presented here, it is rather clear, however, that no matter which desiccant is used, the best process performance is obtained when the water front advances as little as possible into the adsorption bed and a larger portion of the bed is available for the CO2 -N2 separation. Using scenario (b), a dry CO2 product can be obtained. While this is in principle also possible for (a), within the TSA process developed in this work, the CO2 product contains water vapor as well. If this can be tolerated or not is determined by the specifications imposed on the CO2 product. In the context of CCS, the situation where the CO2 product contains water vapor resembles the product streams obtained in amine-scrubbing processes. If the CO2 is to be transported to a storage site, the water vapor will be condensed in the compression train before injection into a pipeline or transportation by ship. Even if the product stream had to be treated in a downstream drying unit, this situation could still prove advantageous: The required size of such a drying unit would be smaller than in the case where the entire feed is treated upstream of the TSA process. There have been many studies investigating TSA cycles in the context of CCS (see e.g. Ntiamoah et al. 43 for an overview). Most of these studies quantified CO2 purity and recovery, while process performances, i.e. energy penalty and productivity, are less frequently reported. Studies that do report performance are summarized in Table 5. The process performance obtained in this work compares well with existing literature. Thermal energy consumption ranges from 3.4 MJ/kgCO2 43 to 7.9 MJ/kgCO2 44 . There are a few noteworthy observations. First, note that in numerous works a dry feed stream is considered. Adding a pre-drying step to a typical feed stream at temperature of 303 K and water vapor content of 3.3 % would increase the energy penalty by approximately 1-1.3 MJ/kgCO2 . Flue gas from a coal-fired power plant typically contains water

28


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vapor and we therefore believe that a wet feed stream should be considered when designing the capture process, particularly in adsorption. The second observation is that specifications typical for CCS (e.g. CO2 purity ≥ 0.95 and recovery ≥ 0.9) are not always fulfilled and more stringent specifications on the separation increases the energy requirement. Typical energy consumptions of amine-scrubbing are also summarized in Table 5. These processes still outperform adsorption-based capture processes, however, they typically already include at least some heat integration, e.g. when recycling lean solvent from the stripper to the absorber. Basic heat integration for a (comparable) TSA process 45 has been shown to reduce the energy penalty by 10-20 % – in this case, the energy consumption is within the range reported for amine-scrubbing processes 46 . Adsorption processes are not as mature as amine-based processes, nonetheless, advanced materials 47 with high CO2 /N2 and CO2 /H2 O selectivity in combination with process design 8 could improve process performance in the future. Table 5: Literature summary of some post-combustion TSA and amine processes. Ref. TSA processes M´ erel et al. 44 Clausse et al. 48 Ntiamoah et al. 43 Hefti et al. 8 Joss et al. 45 this work Amine processes Abu-Zahra et al. 49 IEAGHG 50 Singh et al. 46 Singh and St´ ephenne 51 a b c

CO2 fraction feed

wet feed

CO2 purity

CO2 recovery

Energy consumption ( MJ/kgCO2 )

0.1 0.1 0.15 0.12 0.12 0.12

no no no yesa yesa yes

– 95 0.91 0.96 0.96 0.95

– 81 0.55-0.84 0.9 0.9 0.9

7.9 3.23 3.37-4.5 5.1 5.1b 4.86

0.13

yes yes yes yes

c c c 0.998

≥ 0.9 0.875 0.9 0.9

3.0-3.9 3.2 2.26-4.8 2.33

0.05-0.1 0.09

pre-drying according to Figure 12 (b) was considered value w/o considering heat integration While CO2 purity is not always reported for amine-scrubbing processes, typically it is beyond 0.99 50 .

6.2

Discussion of the assumptions

As stated in the Modeling section the adsorption process depends heavily on the description of the adsorption equilibria of the components present in the feed. Due to the complexity of the interaction of water vapor and CO2 as well as the experimental difficulties encountered in measuring water vapor adsorption 52 some noteworthy uncertainties arise. Because of this, the uncertainty in the mass transfer coefficient of water vapor on zeolite 13X was investigated in detail. While it is beyond

29



the scope of this work to repeat a parametric analysis for all other uncertainties, there are at least three that deserve a brief discussion. The first is the uncertainty in pure component water vapor adsorption at low concentration (Henry’s region) that arises due to the limited resolution of our dew point sensor. As observed in Figure 5 and confirmed in other works 24,53 , the isotherm of water vapor is steep due to the high affinity towards zeolite 13X. To quantify the true Henry’s constant one would need to employ an experimental setup with a higher resolution. To appreciate the implications of such uncertainty for the process performance of the TSA-process, the effect of a Henry’s constant assumed higher than the estimated one can be investigated. As a representative case, the pareto points obtained with kH2 O =1 × 10−3 s−1 (Figure 10) were thus re-calculated assuming a threefold (arbitrary) Henry’s constant, i.e. by simulating the process with a higher Hw while all other conditions were kept the same. For points for which the specifications on the CO2 -product were still fulfilled, the energy consumption was 2 % higher and the productivity remained the same. While there is no way of guaranteeing that the Henry’s constant is not even higher, this suggests that the process performance is not sensitive to small uncertainties in the Henry’s constant of water vapor on zeolite 13X. The second uncertainty is about the assumption concerning the description of the temperature dependence of water vapor adsorption on zeolite 13X. Adsorption data at different temperatures collapse onto a single curve when shown against relative humidity, allowing to incorporate the temperature dependence through the vapor pressure. This approach has been recommended by Leppäjärvi et al. 25 and its main advantage is that a wide range of temperatures can be described, as required for the TSA process. Indeed, such behavior has been reported 25,26 to apply to various zeolites up to temperatures exceeding 100◦ C. Similar to the mass transfer coefficient of water vapor on zeolite 13X, literature values of the heat of adsorption for the same system vary, namely from 43 kJ/mol 25 to beyond 60 kJ/mol 17,36 . Krishnamurthy et al. 10 , who investigated a vacuum swing adsorption process for a similar feed stream as considered here used a value between 45 and 55 kJ/mol. Thus, describing the temperature dependence through the vapor pressure hence using as in this work, a heat of adsorption of 43.3 kJ/mol, leads to an ”optimistic“ value of the energy penalty. In the absence of additional data and due to the fact that our existing water adsorption

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data overlap at different temperatures we refrain from altering our assumption. Clearly, it would be desirable to have more experimental studies investigating the system considered here.

7

Conclusions

In this work, we present a novel TSA cycle with condensers that is capable of treating wet flue gas and of reaching 90 % CO2 -recovery and 95 %-purity with satisfactory process performance. The prerequisite for this analysis was a thorough characterization of the multicomponent adsorption equilibrium of CO2 and water on zeolite 13X and the utilization of a simple explicit isotherm model, as presented in the first part of this paper. Compared to single-sorbent beds used in dry feed streams, the key determinant of the process performance for the layered bed configuration is the penetration depth of the water front at cyclic steady state. In essence, there is no meaningful separation between CO2 and nitrogen up to the locus of the water front in the bed due to the strong adsorption of water vapor. The particular locus of the water front is determined by the combined effects of the guard-layer length, the relative retention of CO2 and water vapor and the mass transfer resistance. Due to its uncertainty, the mass transfer rate of water vapor on zeolite 13X has been considered as well. It is shown that by adjusting the guard-layer length comparable performance is reached for the entire range of reported mass transfer coefficients. The robustness of the process could further be underlined by achieving good process performance for a higher content of water vapor in the feed, i.e. up to 4.5 %.

Acknowledgement Support from the Swiss Commission for Technology and Innovation to the collaborative project with Casale SA is gratefully acknowledged.

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(a) Layered-bed N2

CO2, H2O

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(b) Single Sorbent with Pre-Drying

N2

CO2

13X

CO2, N2, CO2, N2,

H2O

H 2O

13X

Drying

CO2, N2

n Al2O3

H 2O

n H2O

Figure 12: Generic schemes for CO2 capture from wet flue gas, where n indicates the number of columns. (a) Dual sorbent case with condensers. (b) Upstream drying step with subsequent adsorption process.

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Post-Combustion CO2 Capture from wet Flue Gas by Temperature

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