modelling selective h2s absorption and desorption

Chemical Engineering and Processing 43 (2004) 701–715

Modelling selective H2S absorption and desorptionin an aqueous MDEA-solution using a rate-based

non-equilibrium approach

Markus Bolhàr-Nordenkampfa,∗, Anton Friedla,1, Ulrich Kossb,∗, Thomas Torkb,2

a Institute of Chemical Engineering, Vienna University of Technology, Getreidemarkt 9/166, A-1060 Vienna, Austriab Lurgi Oel Gas Chemie, Lurgiallee 5, D-60295 Frankfurt am Main, Germany

Received 27 December 2002; received in revised form 12 February 2003; accepted 12 February 2003

Abstract

A rate-based algorithm was used to yield a predictive tool for MDEA gas scrubbing processes. The model adopts the two-film theory,assuming that thermodynamic equilibrium exists only at the gas–liquid interphase, but not in the boundary layers, where temperature andconcentration gradients are present. Correspondingly chemical equilibrium among the reacting species in the liquid phase is assumed for thebulk phase, but not for the liquid boundary layer. Mass transfer is modelled using calculated mass transfer coefficients in combination with anenhancement model to account for the chemical reactions. Correlations for geometric data, like hold-up and interfacial area, and for reactionrates are provided to give reliable results. The latter correlations are also used to describe the desorption process, which is calculated with anequilibrium approach, considering the kinetics of CO2 desorption. The so obtained tool is tested against measurements done recently by LurgiGmbH at a commercially operated selective MDEA plant in Germany. A closed absorption and desorption loop was build up using AspenRATEFRACTM, capable of modelling the whole process with all necessary equipment.© 2003 Elsevier B.V. All rights reserved.

Keywords:Non-equilibrium stage model; Mass-transfer; Alkanolamines; Carbon dioxide; Hydrogen sulphide; Absorption of acid gases

1. Introduction

Removal of acid gas components from gas streamscontaining CO2 and H2S by aqueous alkanolamines hasbecome a well-established process. With the increase inenvironmental awareness, the exploitation of poorer qualityoil and natural gases, precise modelling of the gas ab-sorption process has become important for industrial plantdesign.

For example, H2S removal from natural gas must be max-imised to meet with pipeline specifications while CO2 ab-

∗ Corresponding authors. Tel.:+43-1-58801-15933;fax: +43-1-58801-15999 (M.B.-N.); tel.:+49-69-5808-3740;fax: +49-69-5808-2645 (U.K.).

E-mail addresses:[email protected](M. Bolhar-Nordenkampf), [email protected] (A. Friedl),ulrich [email protected] (U. Koss), [email protected] (T. Tork).

1 Tel.: +43-1-58801-15920; fax:+43-1-58801-15999.2 Tel.: +49-69-5808-2825; fax:+49-69-5808-2645.

sorption is often best kept minimal. Or maximum CO2 re-moval for use in enhanced oil recovery is desired. To meetwith the pollution standards, tail gas specifications are con-stantly undergoing restrictions requiring stringent scrubbingprocesses.

As it is shown inFig. 1 a typical industrial plant con-sists of an absorption and a desorption column, a solutioninterchanger for heat recovery, a solution cooler, a solu-tion pump, and a reboiler as well as a reflux-system forthe desorber. The absorber operates from ambient pressureup to 70 bar and from 25 to 70◦C. The energy consum-ing desorption of the acid gases is carried out at around130◦C and at pressures from ambient up to 3 bar. Desorp-tion pressure must not necessarily be lower than the absorp-tion ones (e.g. tail gas treatment), this depends further on therequirements of the connected Claus-Plant. MDEA-plantscan process up to 400 000 Nm3/h feed gas in one singletrain.

For accurate plant design it is of great importance to beable to predict the mass transfer behaviour in the absorption

0255-2701/$ – see front matter © 2003 Elsevier B.V. All rights reserved.doi:10.1016/S0255-2701(03)00011-4

702 M. Bolhar-Nordenkampf et al. / Chemical Engineering and Processing 43 (2004) 701–715

Fig. 1. Simplified flow sheet of a MDEA-acid gas removal plant.

and desorption column. Desorption can be calculated usingan equilibrium approach, but it has to be taken into accountthat the CO2 desorption is kinetically driven. An equilibriumapproach for the absorption is not suitable, if predictive capa-bilities of the model are necessary, as it is the case for selec-tive H2S and/or CO2 removal in alkanolamine-systems. Thiscan only be achieved using a rate-based non-equilibriummodel as it is done in this work. It is based on the massand heat transfer between the liquid and the vapour phaseoccurring on a height-increment of the structured and ran-dom packing, respectively. Mass and energy balances areconnected by rate-equations across the interface using thetwo-film theory to calculate the transfer rates. Thermody-namic equilibrium is assumed at the gas–liquid interface.In the liquid bulk phase additional chemical equilibrium isassumed.

The objective of this work is to adapt a rate-based algo-rithm implemented in Aspen (RATEFRACTM) to yield a pre-dictive tool for MDEA gas scrubbing processes. Therefore,the mass transfer coefficient of the liquid phase is calculatedadjusting a formulation from Brunazzi[1] to experimentalresults, while for the gas phase the Onda[2] formulation isused, which is already integrated in RATEFRACTM. A newenhancement model is developed to account for the chemicalreactions in the liquid phase. New correlations for geomet-ric data, like hold-up and interfacial area, and for reactionrates are provided to give reliable results. The latter correla-tions are also used to describe the desorption process, whichis calculated with an equilibrium approach, considering thekinetics of CO2 desorption.

The so obtained system is tested against measurementsdone recently by Lurgi3 at a commercially operated selectiveMDEA plant in Germany. A closed absorption and desorp-tion loop was build up, capable of modelling the whole pro-cess with all necessary equipments. The developed model isused for designing a large natural gas purification and con-ditioning project built by Lurgi.

3 Lurgi Oel Gas Chemie GmbH, Frankfurt, Germany.

2. Model theory

2.1. Mass and energy balance

The absorption can be treated as a kinetically determinedmass transfer process in which the degree of separation isdetermined by the mass and energy transfer rates betweenthe phases being contacted on each tray or within sections ofa packed column. This approach allows dealing with ‘real’trays and ‘real’ packing right from the outset and it results ina physically more realistic model based on the fundamentalchemistry and physics of the process.

Calculations are made of actual tray-by-tray or section-by-section transfer rates, being determined by mass and heattransfer coefficients with concentration and temperature dif-ferences as driving forces.

The rate approach has been described in detail for non-reactive separation processes by Krishnamurthy and Tay-lor [3], Cornelissen[4], and Weiland[5]. The presence ofchemical reactions, due to calculation of the reaction rates,increases the complexity of the mathematical system, con-cerning vapour–liquid equilibrium as well as mass transferprocess calculations. Detailed treatment of these two aspectscan be found at Chakravarty and Weiland[6], and at Sadarand Weiland[7].

A schematic diagram of a non-equilibrium stage is shownin Fig. 2, packed and trayed towers consist of a number ofsuch stages. Vapour and liquid streams from adjacent stagesare brought into contact on the stage and are allowed toexchange mass and energy across their common interface,represented in the diagram by the vertical wavy line. Theflux over the interphase is calculated using the two film the-ory, assuming that the mass transfer resistance is located inthe boundary layer on the gas side and on the liquid side,respectively. The stage is assumed to be at mechanical equi-librium and steady state operation. The transferring gasesreact with the amine in the liquid phase, yielding reactionproducts and liberating heat.

The overall mass and energy transfer rates through theinterfacial area on stagek of the column are given by the

M. Bolhar-Nordenkampf et al. / Chemical Engineering and Processing 43 (2004) 701–715 703

Fig. 2. Non-equilibrium stage.

following equations[3]:

Ni,k = yi,k+1Vk+1 − yi,kVk = aint,kNVi,k

= aint,k

n−1∑j=1j �=i

kVij ,k(yVj,k − yIj,k)

︸︷︷︸Diffusion

+ yVi,kNVt,k︸︷︷︸

Convection

(1)

= aint,kNLi,k = aint,k

n−1∑j=1j �=i

kLij ,k(xIj,k−xLj,k)+xLi,kNLt,k

,

with i = 1, 2, . . . , n− 1; k = 1, 2, . . . , m

Ek =Hk+1Vk+1 −HkVk

= aint,k

n∑i=1

NVi,kHVi,k︸︷︷︸

Convection

+ hVk (TVk − T Ik )︸︷︷︸

Conduction

(2)

= aint,k

(n∑i=1

NLi,kHLi,k + hLk (T

Ik − TLk )

),

with k = 1, 2, . . . , m

Henry’s law is used to calculate the mole fractionsxi,kandyi,k at the vapour–liquid interface:

Hi,k = yIi,k

xIi,k(3)

The correlations for the Henry coefficients used in this workare given inTable 1.

In contrast to the rate-based absorption model, the desorp-tion process is calculated using an equilibrium model (As-pen Plus, RADFRACTM). The equilibrium model is chosenfor this process due to the reason that the desorption processis, because of the higher temperatures present and, there-fore, faster reaction rates, more ‘equilibrium like’. Furtheron, for industrial plant design it is necessary to incorporatethe leading effects to get a reliable model capable to predictthe acid gas loadings of the lean solvent. Therefore, in thiswork the same reaction system in the liquid phase as for theabsorption process is considered (seeSection 2.3).

2.2. Mass transfer coefficient for the gas andfor the liquid phase

The mass transfer is calculated using the above describedtwo film theory [3] in combination with the generalisedMaxwell–Stefan approach to multicomponent mass transfer.In comparison to Fick’s Law the fluxJi is not linear depen-dent with respect to the molecular average mixture veloc-ity and its composition gradient∇xi. The Maxwell–Stefanapproach takes into account the chemical potential as the

Table 1Henry parameters

Componenti Source

CO2 [17,36]H2S [17,36,2]N2 [37]


main driving force, therefore, this approach is also able todescribe highly non-ideal systems[8,9]. Assuming that thedriving force is completely determined by the gradient ofthe chemical potential and by neglection of the Soret effectthe following simplified equation can be obtained:

(∇µi)p,TRT

=j=n∑j=1j �=i

xiNj − xjNi

cTKij(4)

Eq. (4) gives the relation between the thermodynamicproperties of the system and the flux over the gas–liquid in-terphase. It is used to obtain the diffusion coefficients nec-essary for the following mass transfer coefficients: vapourmass transfer coefficients are calculated using the Ondamodel [2]. Although primary developed for random pack-ings, the model for the vapour side yields good results withstructured packings too[2].

kVij = 5.23 ·(

GV

arp · ηV)0.7

· ScV1/3

ij · (arp · drp)−2

× (arp · KVij ) · 1

R · T (5)

whereG is the gas superficial mass velocity (gas densitytimes gas velocity),arp the specific surface area of the pack-ing,η the dynamic viscosity,Scthe Schmidt number,drp thenominal diameter of the packing,Kij the Maxwell–Stefandiffusion coefficient,R the gas constant, andT the temper-ature.

For calculation of the liquid mass transfer coefficients forstructured packings some relations can be found in the lit-erature[10–12], with the deficit of neglecting the depen-dence on the gas velocity and the packing height. Nawrockiand Chuang[13] showed in their work, that the flow dis-tance on an inclined plate is considerably important in themass-transfer process. Brunazzi[1] developed a Sherwoodcorrelation for the mass transfer on an inclined plate, Ponterand Yeung[14] introduced a mixing factor to account for themixing in the junctions between the planes of the packing,resulting in the following equation:

Sh= A · GzB

KaC(6)

Sh, GzandKa are the dimensionless Sherwood, Grätz, andKapitsa number (seeAppendix A), while A, B, andC areadjustable parameters. UsingEq. (6) the mass transfer co-efficient in the liquid phase can be expressed as

kL0

ij =KLij

d· A

×

[(umax · d · ρL

ηL

)·(

ηL

ρL · KLij

)· δ

H

]B(σ3 · ρLηL

4 · g

)C (7)

whered is a characteristic length of a thin liquid film, ob-viously related toδ, the thickness of the liquid film on theinclined plate of the structured packing. Ford the character-istic length of four timesδ is used[1], a typical flow lengthafter which the influence of local perturbations is thought tobe faded.H is a characteristic dimension of the column pack-ing. For the structured packingH is chosen as the distancefrom one junction point to the next junction point of themetal structure and, therefore, it can be easily obtained.umaxis the maximum velocity of the liquid film (seeSection 2.5).

A, B andC are constants, which have to be determined bygeneral mass transfer experiments on structured packings.The original equation of Brunazzi[1] was adopted, usingthe following values for the constants:A: 3 andB: 0.8. ForC a value of 0.09 was chosen according to literature[15].

2.3. Chemical reactions

Reactions which take place in the liquid phase can be di-vided in principle into two groups. Reactions equilibriumcontrolled and reactions kinetically determined. The chemi-cal reactions determine the composition of the different ionspecies in the liquid phase and, therefore, the enhancementof the mass transfer.

Equilibrium reactions are fast enough to assume chem-ical equilibrium throughout the entire liquid phase. Thisassumption is fulfilled if reaction kinetics is significantlyfaster than mass transport in the phase. These reactionscan be modelled using equilibrium constants. A certainnumber of equilibrium reactions occur within the systemCO2–H2S–Alkanolamines[16]. An overview over these re-actions and correlations are given inTable 2(Reaction I–VI).

Kinetic reactions must be modelled differently. The as-sumption that reaction kinetics is much faster than masstransfer can not be applied, therefore, reaction kinetics hasto be included in the calculations.

The first reaction to be considered is the hydration of CO2:

CO2 +H2O → H+ + HCO−3 (VII )

This reaction is very slow[17] and may be neglected. Thesecond reaction is the bicarbonate formation:

CO2 + OH− → HCO−3 (VIII )

This reaction is fast and can enhance mass transfer evenwhen the concentration of the hydroxyl ions is low and may

Table 2Equilibrium reactions and parameters

Reaction Source

I H2S+ MDEA⇔MDEAH+ + HS− [34]II HCO3

− + OH⇔H2O+ CO2−3 [34]

III MDEA+ H2O⇔OH− + MDEAH+ [34]IV 2H2O⇔H3O+ + OH− [38]V MDEA+ + H2O⇔MDEA+ H3O+ [36]VI H2S+ H2O⇔HS− + H3O+ [38]


have significant contribution to the observed reaction rate.The reaction kinetics was measured by Pinsent[18]. Augsten[19] proved in his work the dominant role of this reaction ofCO2 with OH− at pH-values greater than 8. This conditionapplies for MDEA-solution. The correlations for reactionVIII which are used in this work can be found at Pinsent[18].

Tertiary amine acts as a base catalyst for the hydrolysisof CO2 to bicarbonate[20]:

CO2 +H2O+ MDEA → MDEAH+ + HCO−3 (IX )

This mechanism implies that tertiary alkanolamines, suchas MDEA, do not react directly with CO2. This thesis isproved by the work of Versteeg and van Swaaij[16]. It wouldnot be necessary to implement reaction IX into the Aspensystem were it not for the fact that for the implementation ofthe enhancement model an overall reaction is necessary (seeenhancement factor). Measurements on the kinetic of thisreaction have been made by various authors showing quite awide scattering[2,3,21–29]. In this model the measurementsdone by Rinker[25] are used to model the overall reactionrate of reaction IX.

In the desorber the same reactive system is assumed asfor the absorber.

2.4. Enhancement model

When a transferring component undergoes reaction afterdissolving physically into the liquid, mass transfer rates of-ten are increased dramatically. A several-thousand-fold im-provement is not uncommon. This is reflected in a muchhigher value of the liquid-side mass transfer coefficient, de-noted as above, for the chemically reactive case bykLij . Thephysical and reactive transfer coefficients are related througha so-called enhancement factorEi by the expression:

kLij = Ei · kL0

ij (8)

wherekL0

ij is the mass transfer coefficient for the same pro-cess taking place without present reaction. The enhancementfactor accounts quantitatively for the effect of reaction onmass transfer and it depends, among other things, on the ki-netic details of the particular reaction taking place. Amongall reactions occurring, the kinetically slowest one deter-mines the enhancement factor and liquid-phase chemical re-action does not influence gas-side mass transfer coefficients.To determineEi, it is necessary to consider only chemicalreactions taking place in the liquid phase.

Generally, the enhancement factor is a function of thetransport properties like diffusion coefficients and kineticparameters like the reaction rate and order of the reactants.Therefore, it varies quite widely from stage to stage. Thisis also the reason, why a single overall packing efficiencycannot equalise the inaccurate equilibrium-stage approach.Each gas-solvent pair must be treated individually. Conse-quently, the enhancement factor is unique to the system andthe operating conditions.

For H2S the resistance of the mass transfer is on thegaseous side, therefore, the enhancement factor of H2S isnot important for determining absorption rates. For CO2 theabsorption rate is dominated by the liquid side mass trans-fer, requiring proper CO2 enhancement factor calculations[15]. In this work the Aspen enhancement model for CO2is replaced by the enhancement factor model, due to sev-eral problematic assumptions the model makes. The Aspenmodel calculates the enhancement using an average diffusioncoefficient for all components and an average mass transfercoefficient. Due to this assumption every component has thesame concentration boundary layer. This is not a realisticapproach, because of the fact that the concentration profilebuilds up in order of the reaction rates.

The enhancement factor model in this work does not useaveraged values of the diffusion coefficient and the masstransfer coefficient. Thus a unique enhancement factor iscalculated for each component and then multiplied with thecorresponding mass transfer coefficient, as shown inEq. (9).This equation was developed by Danckwerts[30] and takesa residual concentration in the bulk phase into account:

E′CO2

=Ha ·

√E∞−E′

CO2E∞−1

tanh

[Ha ·

√E∞−E′

CO2E∞−1

]

·

1 −

cBCO2− cBCO2 equilib

cICO2· cosh

Ha ·

√E∞ − E′

CO2

E∞ − 1

(9)

with

Ha =√kMDEA · DLCO2

· cBMDEA

kL0

CO2

(10)

E∞ = 1 + DLMDEA

DLCO2

· cBMDEA

cICO2

(11)

wherekMDEA is the reaction rate corresponding to Rinker[25] and kL

0

CO2is the mass transfer coefficient for physical

absorption of CO2 in MDEA solution.Eq. (9) can be simplified for large values ofE∞ or for

Hatta numbers lower than 2:

E′CO2

= Ha

tanh(Ha)(12)

Last [15] developed in his work a simplified approxima-tion to Eq. (9) for calculating the enhancement factor forHatta numbers large than 2 andE∞ values lower than 100:

E′CO2

= 1(1 − 1

E∞Ha3/2

+ 1

E3/2∞

)2/3(13)


Table 3Parameters for packing

Liquid load w (m3/m2 h) Packing � � �

<40 Mellapak X (60◦) 0.0169 0.37 0.25Mellapak Y (45◦) 0.02 0.37 0.25Rhombopak 9M 0.021 0.37 0.42

>40 Mellapak X (60◦) 0.0075 0.59 0.25Mellapak Y (45◦) 0.0089 0.59 0.25Rhombopak 9M – – –

In this work Eqs. (12) and (13), respectively, are used forcalculation of the enhancement factor for CO2.

2.5. Geometric data input: hold-up, interfacial area andliquid film thickness

2.5.1. Hold-up in the absorber (structured packing)Last [15] showed that the influence of segment wise

calculation becomes most important at high pressures,where among other effects the enhanced exothermic CO2-absorption has a great influence on the viscosity of theliquid, which again has a retroaction on the hold-up.

Sulzer Chemtech Ltd. provides a correlation for theirpacking which is based on empirical data.

hL = α · a0.83geo · wβ ·

(ηL

η+H2O

)χ(14)

The parameters�, �, � of the different packings are givenin Table 3.

2.5.2. Hold-up desorber (random packing)Equilibrium calculations normally do not require a

hold-up calculation, because of the assumed Vapour–Liquid-equilibrium between the two phases. Due to the fact thatkinetic reactions requiring the hold-up to calculate the reac-tion rate, will be used in the desorber too, a hold-up modelhad to be implemented into the system.

Billet and Schultes[31] studied in 1999 a large number ofrandom packing and retained the following correlation forcalculating the hold-up:

hL =(

12 · ηL

g · ρL · w · a2rp

)1/3

·(dh

arp

)2/3

(15)

with

ReL = w · ρLarp · ηL < 5 :

dh

arp

= Ch ·(w · ρLarp · ηL

)0.15

·(w2 · arp

g

)0.1

(16)

ReL = w · ρLarp · ηL ≥ 5 :

dh

arp

= 0.85 · Ch ·(w · ρLarp · ηL

)0.25

·(w2 · arp

g

)0.1

(17)

wherew is the liquid load,arp the specific surface area ofthe random packing,dh the hydraulic diameter andCh is thehydraulic constant for the packing.

2.5.3. The liquid film thickness (absorber)The liquid film thickness (absorber) on the inclined plate

of the structured packing can be obtained by setting thepotential and dissipation energy equal[32]:

δ = 3

√3 · w · ηL

aint · ρL · g · sin2ψ(18)

with

w = δ · aint · u · sinψ (19)

whereaint is the interfacial area,u the average liquid filmvelocity andψ the angel of the inclined plane in referenceto the horizontal plane.

2.5.4. Interfacial area (absorber)The correct calculation of the interfacial area is a difficult

aspect itself. Last[15] compared in his work interfacial cal-culation routines form various authors, finding a large scat-tering in the obtained values for the same packing (Mellapak500 Y) from 36.4 to 255 m2/m3.

The interfacial model used in this work is based on a corre-lation developed by Brunazzi[1]. Her approach is modifiedin this work by introducing a weight factorϕ, accountingfor non-perfectness, i.e. that not all of the hold-up takes partin the film flow, e.g. through channelling or accumulationof liquid on the edges of the structure. In this approach onlyϕ · hL of the hold-up takes part in mass transfer. The inter-facial area can now be calculated with the adapted Brunazziequation:

ϕ · hL = δ · aint (20)

wherehL is the liquid hold,aint the interfacial area andδthe liquid film thickness. If assumed that the weight fac-tor ϕ is a function of the liquid load,ϕ can be correlatedto the ratio of the actual liquid loading to the liquid load-ing at the loading point:ϕ=(w/w0)ξ. It shall be pointedout that at the loading pointϕ should equal unity, therebyassuming that the total hold-up is flowing as liquid filmdown the packing. By solving the set ofEqs. (18) and(20) the following correlation for the interfacial area can beretrieved:

aint =[( ww0

)ξhL

]3/2√ρLg sin2ψ

3wηL(21)

wherew0 is the manufacture defined liquid load at the load-ing point, andξ a adjustable parameter. It could be shownin experiments with KOH-solution that the interfacial areaaint is proportional to the liquid loading:aint ∝ w0.2. Us-ing this correlation andEq. (21) one can determineξ by


exponent comparison. It followsξ= 0.09667 according to[15].

2.6. Thermodynamic models

Non-idealities of the gas phase are calculated using theSRK model. For the liquid phase the Electrolyte-NRTL-modelis used to calculate the chemical potential and the activitycoefficients, respectively. The Electrolyte-NRTL model wasoriginally proposed by Chen et al.[33], for aqueous elec-trolyte systems. It was later extended to mixed solvent elec-trolyte systems[34]. For modelling the MDEA–H2S–CO2system the non-randomness NRTL parameters measured byAustgen[19] are used.

The correlations and parameters used in Aspen were com-pared with measured correlations[15]. Besides surface ten-sion and viscosity only slight discrepancy between themwere found. Therefore, and to lower complexity of the sim-ulation system, surface tension and viscosity only, were in-cluded in user subroutines. An overview is given inTable 4.

2.7. Modelling approach

2.7.1. AbsorberThe absorber as aforementioned is modelled with the

RATEFRACTM model. This model is linked to the AspenPlus simulation engine, which provides the user interface,the models to calculate the different apparatus in the flow di-agrams and the physicochemical parameters. The user sub-routines for calculation of viscosity, surface tension and thekinetic routines are, therefore, linked directly to Aspen Plus,whereas the mass transfer routine and the routine for calcu-lation of the interfacial area are linked to RATEFRACTM.Fig. 3shows the linkage and transfer variables of the differ-ent user routines, adopted from Pacheco[35].

Fig. 3. Simulation system absorber.

Table 4Overview of used correlations

Parameter Phase Correlation applied

Density Liquid ClarkVapour Soave-Redlich-Kwong

Viscosity Liquid Last[15]Vapour Chapman-Enskog-Brokaw

Diffusion-coefficients Liquid Wilke-Chang, Nerst-HartleyVapour Chapman-Enskog, Wilke-Lee

Fugacitiy Liquid Electrolyte-NRTLVapour Soave-Redlich-Kwong

Surface tension Liquid Last[15]

Aspen Plus allows the usage of user routines for nearlyall physiochemical properties, RATEFRACTM providesdata interfaces to link user routines for binary mass transfercoefficients, heat transfer coefficients, for interfacial areaand pressure drop. For the linkage of the hold-up modeland the enhancement factor model no data interfaces areprovided by the RATEFRACTM model so they had to becreated.

2.7.2. DesorberAs the desorber is based on the RADFRACTM module in-

cluded in Aspen Plus, where all routines are linked too. Theviscosity and surface tension subroutines provide, as in theabsorber simulation, the necessary physiochemical proper-ties. Additionally a subroutine for calculating the reactionrates for the kinetically controlled CO2 reaction is linked tothe RADFRACTM module. The hold-up, necessary for thekinetic reaction, is obtained by a subroutine, which resolvesthe necessary packing parameters out of the packing datasubroutine.

Fig. 4 shows the linkage and transfer variables of thedifferent user routines.


Fig. 4. Simulation system desorber.

3. Results and discussion

The developed model was tested on experimental data ofan industrial plant in Germany built by Lurgi. Representa-tive input conditions for the acid gas absorber in a plant inGermany are summarised inTables 5 and 6. These condi-tions were used for the simulation. A summary of the resultsis given inTable 7.

In Figs. 5 and 6a comparison between the measuredand calculated values for the H2S and CO2 concentrationin the clean gas over the different measurements (D-1–D-6)

Table 5Characteristics of absorber and desorber

Characteristics Refinery Germany

Absorber Desorber

Column diameter (m) 0.9 1.7Packing height (m) 3.789/5.486 12Backwash trays (stages) – 1–3Packing Mellapak 250 X Pall metal 35 mm,

Stage: 4–19Number of segments/stages 20 20

Table 6Typical operating data of amine-acid gas absorber/desorber refinery Ger-many

Parameter Refinery Germany

Absorber Desorber

Inlet gas flow rate (kmol/h) 110–140 –Inlet liquid flow rate (kmol/h) – 1718–2170Inlet L/G ratio (−) 3.52 –Inlet gas temperature (◦C) 40.6–41.3 –Inlet liquid temperature (◦C) 25 112.9–115.1Inlet gas loading H2S (vol ppm) 8000–10 000 –Inlet gas loading CO2 (vol.%) 2.8–3.8 –MDEA concentration (wt.%) ∼50 ∼50Inlet liquid H2S loading

(mol/mol amine)0.0054 0.0895–0.179

Inlet liquid CO2 loading(mol/mol amine)

0.00016 0.0006–0.01522

Pressure (bar) 1.1 2.24–2.26

Table 7Design results refinery Germany

Parameter Refinery Germany

Absorber Desorber

Outlet gas flow rate (kmol/h) 108–142 13.75–29.82Outlet liquid flow rate (kmol/h) 351–528 1763–2208Outlet gas temperature (◦C) 25.1 40.0Outlet liquid temperature (◦C) 23.4–24.5 126.9–128.3Outlet gas loading H2S

(mol ppm/mol%))46–165 95–96

Outlet gas loading CO2 (mol%) 2.7–3.5 0.31–1.05Outlet liquid H2S loading

(mol/mol amine)0.0231–0.0475 0.0056–0.010

Outlet liquid CO2 loading(mol/mol amine)

0.0064–0.0045 2.9 E-5–0.00014

is given. The two different packing heights in the measure-ments result from two different inlet nozzles chosen for thelean amine. Calculated values were obtained using the de-veloped rate based model and TSWEET4.

TSWEET is a commercial equilibrium approach basedsimulation tool, developed especially for gas sweetening pur-poses. The usage of this program requires the estimation ofresidence times on assumed trays in the absorber for the in-ternal kinetic reaction model calculations. The disadvantageof TSWEET is that the estimated residence time correspondsonly for very few operating conditions to a real residencetime calculated using real geometric parameters. In mostcases a ‘virtual’ residence time has to be chosen, requiring abroad experience of the user on the absorption behaviour ofthe system at the specific operating conditions in advance.

It can be seen, that the non-equilibrium model, althoughdeveloped and tested on a laboratory column, gives excellentresults on the industrial absorber. It predicts the measuredH2S values far better (21 ppm average deviation) than theTSWEET (88 ppm average deviation) simulation and givescomparable results for the CO2 values (Non-equilibrium:0.22 vol.%; TSWEET: 0.28 vol.% average deviation). How-ever, the most important aspect is, that the scaling up of thenon-equilibrium model was done without fitting any param-eter, of the measured values, whereas for the TSWEET cal-culations, as aforementioned the residence time profiles andefficiencies were selected with respect to optimised simula-tion results.

In Fig. 7 the calculated vapour mole fractions concentra-tion profiles of CO2 and H2S over the packing height for 3.9and 5.62 m are given for two representative measurements,respectively. The difference between the absorption of H2Sand CO2 can be seen clearly. CO2 which has to dissolve firstbefore reacting with MDEA, has a nearly constant absorp-tion gradient over the whole packing, whereas H2S showsthe typically bend chemical reactive absorption profile. Itcan be generally stated that all simulation programs predicta better cleaned gas in case of H2S for all measurements.

4 Brian Research Inc.


Fig. 5. Comparison of calculated and measured H2S concentrations in the clean gas.

For CO2 this general trend can not be seen, but the relativedeviation of the calculated values is much lower. InFig. 8the liquid and vapour temperature profile of the absorberare given. The difference in the temperature profile of thevapour and the liquid phase is obvious. In equilibrium cal-culations, this difference is neglected and calculations arecarried out with an average stage temperature.

The desorber model was tested against 13 measurementson different days on an industrial desorber in Germany withthe parameters given inTable 6. These H2S and CO2 load-ings are compared with equilibrium calculations performedwith Aspen and TSWEET, which can be found inFigs. 9and 10. Thereby Aspen-kinetic represents calculations donewith the developed regeneration model including the kinetic

Fig. 6. Comparison of calculated and measured CO2 concentrations in the clean gas.

reaction of CO2, whereas Aspen-equilibrium represents sim-ulations done with equilibrium based reactions only.

By looking atFig. 10 the unsuitability of modelling theCO2 remaining loading with TSWEET or Aspen totallybased on vapour–liquid equilibrium calculations is seen.TSWEET obtains a regenerated amine solution, with onlyinfinite remaining CO2 loadings. The same applies to theAspen-equilibrium approach. Because much of the reboilerduty is needed to strip CO2 to such low values, less duty isleft to strip H2S of. Therefore, the H2S remaining loadingscalculated by TSWEET and Aspen-equilibrium are muchtoo high. TSWEET: predicts values which are more thantwice as high as the measured once, Aspen-equilibrium ap-proach predicts the values four times higher.


Fig. 7. Comparison H2S and CO2 concentration profile.

By variation of equilibrium constant of the CO2 reactionin the Aspen-equilibrium model an interaction between des-orption of CO2 and H2S was found: the lower the CO2 leanamine loading, the higher the H2S loading gets. This is dueto the fact that the reboiler duty is primarily used for strip-ping of CO2, therefore, less duty is left for the stripping ofH2S. The reason for this behaviour is that the equilibrium

Fig. 8. Comparison vapour and liquid temperature profile.

reaction for CO2 at stripping temperature is very fast, nearlyinfinite.

In the kinetic approach of CO2 desorption the equilibriumreaction of CO2 is replaced with a kinetic reaction. Thismodel gives very good results for CO2 (average deviation:0.04 mmol/molAmin) and H2S loadings (average deviation:2 mmol/molAmin) in comparison to the other two simulation


Fig. 9. H2S loading of regenerated MDEA.

Fig. 10. CO2 loading of regenerated MDEA.

tools. Due to the interaction between the stripping of H2Sand CO2 the higher remaining load for CO2 results in a lowerremaining load for H2S. Thus the reboiler duty which is notused for stripping of CO2 can now enhance H2S desorption.

Fig. 11shows the effect on the loading profile for H2S andCO2 over the packing height for different reboiler duties. Thedesorption profile of CO2 shows a much stronger influenceon a variation of the reboiler duty as the H2S profile.

3.1. Application of both models on a currently runningproject

Finally the rate based absorber and equilibrium based des-orber model were used in a currently running project de-signing a gas sweetening plant. A raw gas stream (methane,ethane and trace components) of 8300 kmol/h with 3 mol%H2S and 4 mol% CO2 should be cleaned. The challengemodelling this system was due to the high pressure of 56bar and stringent clean gas conditions of 3 ppm for H2S and0.7–1.5 for CO2.

Closed loop calculations were performed. As input datafor the absorber the design specifications for the plant weretaken, whereas for the desorber the composition for the

rich amine stream calculated with the absorption model wastaken. The calculated stream value for the regenerated aminesolution was then used again as lean amine input stream tothe absorber.

Conditions for the acid gas absorber and desorber aresummarised inTable 8. In Fig. 12the vapour mole fractionprofile of H2S and CO2 in the absorber obtained from thecalculation is given over the packing height: the H2S con-centration of the clean gas is achieved after 4 m of pack-ing, whereas for achieving the desired CO2 specification thecomplete packing height is needed. It can be clearly seen

Table 8Characteristics of absorber and desorber (current project)

Characteristics Current Project

Absorber Desorber

Column diameter (m) 2.6 4.2Packing height (m) 11 12Backwash trays (stages) – 1–3Packing Mellapak 250 Y Pall metal 35 mm,

Stages: 4–19Number of segments/stages 30 19


Fig. 11. CO2 and H2S loading profile at different reboiler duties.

Fig. 12. Vapour mole fraction profile absorber currently running project.

that the CO2 concentration in the clean gas can be greatlyinfluenced by the packing height, whereas for the H2S con-centration in the clean gas the packing height plays a minorrole. Low H2S concentrations are achieved only by low re-maining loading of the regenerated amine solution. LowerH2S concentration in the clean gas can be obtained onlyby adjusting the reboiler duty, in order to obtain lower H2Sloadings in the regenerated MDEA solution, whereas theCO2 concentration in the clean gas stays nearly unaffected.

4. Conclusion

In this work a rate-based algorithm implemented in As-pen (RATEFRACTM) was used to yield a predictive tool forMDEA acid gases scrubbing processes. Mass transfer coef-ficients of the liquid phase are calculated adjusting a formu-lation from Brunazzi[1] to experimental results, while forthe gas phase the Onda[2] formulation is used. A new en-hancement model is developed to account for the chemical


reactions in the liquid phase. New correlations for geomet-ric data, like hold-up and interfacial area, and for reactionrates are provided to give reliable results. The tool whichwas developed on laboratory measurements was applied onan industrial scale absorber with excellent results. It allowspredicting acid gas concentrations in the clean gas of theabsorber, with only the input of geometrical data needed.No estimations of parameters having an empirical charac-ter rather than a physical background like the ‘virtual resi-dence time’ in TSWEET, have to be made which makes thisnon-equilibrium model a powerful and straightforward tool.

For the desorber an equilibrium based model (RAD-FRACTM) with an implementation of the kinetic CO2 re-action was used. This tool was applied on industrial scaleas well, yielding excellent results, though not completelyrate-based. Together with the absorber model closed loopcalculations can be performed.

In the near future further measurements are planned atindustrial selective MDEA plants, which would enable totest the developed models further and fine tune them.

Acknowledgements

We have to thank Matthias Linicus and Gerhard Schnei-der, Lurgi Oel Gas Chemie/Frankfurt as well as to FredGobin, Aspen Technology Inc. for their support and assis-tance on computational matters.

Appendix A. Nomenclature

aint interfacial area (m2/m3)ageo specific surface area of structured

packing (m2/m3)ah hydraulic diameter (m2/m3)arp specific surface area of random

packing (m2/m3)ci concentration of componenti in the

solution (mol/kgsolution)ct total concentration per volume

(kmol/m3)Ch hydraulic constant for dumped

packing (−)d characteristic dimension (m)dh hydraulic diameter (m)drp nominal diameter of packing or

packing size (m)Di Fick diffusion coefficient (m2/s)e point energy flux (J/(m2 s))ECO2 enhancement factor of CO2 (−)E∞ enhancement factor for infinite fast

reaction (−)fi component feed rate (kmol/s)g gravitational constant (m/s2)

G gas superficial mass velocity (kg/(m2 s))hL liquid holdup (m3/m3)H specific enthalpy (J/kmol)H flow distance (m)Hi Henry-coefficient of componenti (Pa)Ha Hatta number (−)kij binary mass transfer coefficient for

the binary pairi and j (kmol/(Pa m2 s))

kOH− reaction rate—forward reaction VIII(m3/(kmol s))

k−1OH− reaction rate—backward reaction

VIII (1/s)kMDEA reaction rate—IX (m3/(kmol s))Kij Maxwell–Stefan binary diffusion

coefficient of componenti insystemi and j (m2/s)

Ki equilibrium constant of specificcomponenti (unit depends onspecific reaction)

L total liquid flow (kmol/s)n moles (−)Ni molar flux of componenti

(kmol/(m2 s))pi partial pressure of componenti (Pa)R gas constant (J/(mol K))Re Reynolds number (−)S side stream flow (kmol/s)Sc Schmidt number (−)T temperature (K)u(y) velocity of liquid dependent on

coordinatey (m/s)vi component vapour flow (kmol/s)V total vapour flow (kmol/s)w liquid load (m3/(m2 s))xi liquid phase molar fraction of

componenti (−)yi vapour phase molar fraction of

componenti (−)zi absolute value of ionic charge

Greek lettersα constant for SulzerEq. (4)(−)β constant for SulzerEq. (4)(−)χ constant for SulzerEq. (4)(−)δ liquid film thickness (m)η dynamic viscosity (Pa s)ϕ part of holdup flowing as film (−)µi chemical potential of componenti

(J/mol)ν kinematic viscosity (m2/s)ρ density (kg/m3)σL liquid surface tension (Nm)ψ angel of inclined plane in reference

to the horizontal plane (◦)


Subscriptsi, j component numberk stage numberm molecular speciesp variable at operating pressures solventt estimated ‘true’ valuew water

Superscripts′ modification of specific variable+ standard conditions (105 Pa; 293.15 K)I interfaceB bulk phaseL liquid bulkLF liquid feedV vapour bulkVF vapour feed0 refers to variable without reaction

Dimensionless numbers

Galilei number Ga = g · d3h

v2

Grätz number Gz= Re · Sc · δ

H

Hatta number Ha =√kMDEA · DCO2 · cBMDEA

k0CO2

Kapitsanumber

Ka = σ3 · ρη4 · g

Reynoldsnumber

Re= umax · d · ρη

Schmidtnumber

Scij = η

ρ · Kij

Sherwoodnumber

Sh=k0

ij · dKij

References

[1] E. Brunazzi, A. Paglianti, Liquid-film mass-transfer coefficients ina column equipped with structured packings, Ind. Eng. Chem. Res.36 (1997) 3792–3799.

[2] K. Onda, H. Takeuchi, Y. Okumoto, Mass transfer coefficients be-tween gas and liquid phases in packed columns, J. Chem. Eng. Jpn.12 (1967) 56–70.

[3] R. Krishnamurthy, R. Taylor, A non-equilibrium stage model ofmulticomponent separation processes-part I: model description andmethod of solution, AIChE J. 3 (1985) 449–456.

[4] A.E. Cornelissen, Simulation of absorption of H2S and CO2 intoaqueous alkanolamines in tray and packed columns, Trans. Inst.Chem. Eng. 58 (1980) 242–250.

[5] R.H. Weiland, M. Rawal, R.G. Rice, Stripping of carbon dioxidefrom monoethanolamine solutions in a packed column, AIChE J. 28(1982) 963–973.

[6] R.H. Weiland, T. Chakravarty, A.E. Mather, Solubility of carbondioxide and hydrogen sulfide in aqueous alkanolamines, Ind. Eng.Chem. Res. 32 (1993) 1419–1430.

[7] H. Sardar, M.S. Sivasubramanian, R.H. Weiland, Simulation of com-mercial amine treating units, Proceedings of the Gas ConditioningConference 35th, 1985.

[8] M.J. Frank, J.A. Kuipers, G.F. Versteeg, Modelling of simultaneousmass and heat transfer with chemical reaction using the Maxwell–Stefan-Theory-I. Model development and isothermal study, Chem.Eng. Sci. 10 (1995) 1645–1659.

[9] M.J. Frank, J.A. Kuipers, G.F. Versteeg, Modelling of simulta-neous mass and heat transfer with chemical reaction using theMaxwell–Stefan-Theory-II. Non isothermal study, Chem. Eng. Sci.10 (1995) 1661–1671.

[10] R. Billet, M. Schultes, Predicting mass transfer in packed columns,Chem. Eng. Technol. 16 (1993) 1–9.

[11] J.L. Bravo, J.A. Rocha, J.R. Fair, Comprehensive model for theperformance of columns containing structured packings, Inst. Chem.Eng. Symp. Ser. 1 (1992) A489–A507.

[12] M.H. Brito de, U. von Stockar, A.M. Bangerter, P. Bomio, Effectivemass-transfer area in a pilot plant column equipped with structuredpackings and with ceramic rings, Ind. Eng. Chem. Res. 33 (1994)647–656.

[13] P.A. Nawrocki, K.T. Chuang, Carbon dioxide absorption into a stableliquid rivulet, Can. J. Chem. Eng. 74 (1996) 247–255.

[14] A.B. Ponter, P.H. Au-Yeung, Estimation of liquid film mass transfercoefficients for columns randomly packed with partially wetted rings,Can. J. Chem. Eng. 60 (1980) 94–99.

[15] Last, Absorption mit überlagerter chemischer Reaktion in Pack-ungskolonnen bei Drücken bis 50 bar, Universität München,München, 1999.

[16] G.F. Versteeg, W.P.M. Van Swaaij, On the kinetics between CO2

and alkanolamines both in aqueous and non-aqueous solutions-II.Tertiary amines, Chem. Eng. Sci. 3 (1988) 587–591.

[17] D.M. Austgen, G.T. Rochelle, Model of vapour–liquid equilibria foraqueous acid gas–alkanolamine systems using the electrolyte-NRTLequation, Ind. Eng. Chem. Res. 28 (1989) 1060–1073.

[18] B.R. Pinsent, L. Pearson, F.J. Roughton, The kinetics of combinationof carbon dioxide with hydrogen ions, Trans. Faraday Soc. 13 (1956)1512.

[19] D.M. Austgen, A Model of Vapour–Liquid Equilibria for AcidGas–Alkanolamine–Water Systems, University of Texas, Austin,1989.

[20] J. Ko, M. Li, Kinetics of absorption of carbon dioxide into solutionsof N-methyldiethanolamine plus water, Chem. Eng. Sci. 19 (2000)4139–4147.

[21] G. Astarita, D.W. Savage, Gas absorption and desorption with re-versible instantaneous chemical reaction, Chem. Eng. Sci. 35 (1980)1755–1764.

[22] N. Haimour, A. Bidarian, O.C. Sandall, Kinetics of the reactionbetween carbon dioxide and methyldiethanolamine, Chem. Eng. Sci.6 (1987) 1393–1398.

[23] R.J. Littel, W.P. van Swaaij, G.F. Versteeg, Kinetics of carbon dioxidewith tertiary amines in aqueous solution, AIChE J. 11 (1990) 1633–1640.

[24] G. Xu, C. Zhang, S. Qin, Y. Wang, Kinetics study on absorptionof carbon dioxide into solutions of activated methyldiethanolamine,Ind. Eng. Chem. Res. 3 (1992) 921–927.

[25] E.B. Rinker, S.S. Ashour, C.S. Orville, Kinetics and modellingof carbon dioxide absorption into aqueous solutions of N-methyl-diethanolamine, Chem. Eng. Sci. 5 (1995) 755–768.

[26] W. Yu, G. Astarita, Kinetics of carbon dioxide absorption in solutionof methyldiethanolamine, Chem. Eng. Sci. 8 (1985) 1585–1590.

[27] D. Barth, C. Tondre, J. Delpuech, Kinetic and mechanism of thereactions of carbon dioxide with alkanolamines: a discussion con-cerning the case of MDEA and DEA, Chem. Eng. Sci. 12 (1984)1753–1757.


[28] Y. Wang, C. Zhang, S. Qin, Kinetic study of absorption of carbondioxide in aqueous MDEA, J. Chem. Ind. Eng. 4 (1991) 466–474.

[29] D. Richon, F. Pani, A. Gaunand, R. Cadours, C. Bouallou, Ki-netics of absorption of carbon dioxide in concentrated aqueousmethyldiethanolamine solutions in the range 296–343 K, J. Chem.Eng. Data 2 (1997) 353–359.

[30] P.V. Danckwerts, Absorption by simultaneous diffusion and chemicalreaction, Trans. Faraday Soc. 46 (1950) 300–304.

[31] R. Billet, M. Schultes, Prediction of mass transfer columns withdumped and arranged packings, Trans. Inst. Chem. Eng. 38 (1999)498.

[32] J.H. Spurk, Strömungslehre-Einführung in die Theorie derStroömung, second ed, Springer, Berlin, 1987.

[33] C.C. Chen, H.I. Brit, J.F. Boston, L.B. Evans, A local compositionmodel for the excess Gibbs energy of aqueous electrolyte systems:part I: single solvent, single completely dissociated electrolyte sys-tem, AIChE J. 4 (1982) 588–596.

[34] G. Vallée, P. Mougine, S. Julian, W. Fürst, Representation of CO2

and H2S absorption by aqueous solutions of diethanolamine usingan electrolyte equation of state, Ind. Eng. Chem. Res. 38 (1999)3473–3480.

[35] M.A. Pacheco, G.T. Rochelle, Rate-based modelling of reactive ab-sorption of CO2 and H2S into aqueous methyldiethanolamine, Ind.Eng. Chem. Res. (1998) 4107–4117.

[36] D.M. Austgen, G.T. Rochelle, Model of vapour–liquid equilibria foraqueous acid gas–alkanolamine systems, 2. Representation of H2Sand CO2 solubility in aqueous MDEA and CO2 solubility in aqueousmixtures of MDEA with MEA or DEA, Ind. Eng. Chem. Res. 30(1991) 543–555.

[37] G.T. Rochelle, M. Posey, Modelling CO2 and H2S solubility inMDEA and DEA: design implications, Proceedings of the 1996 75thAnnual Convention of the Gas Processors Association (1996) 80–91.

[38] T.J. Edwards, G. Maurer, J. Newman, J.M. Prausnitz, Vapour–liquidequilibria in multicomponent aqueous solutions of volatile weakelectrolytes, AIChE J. 24 (1978) 966–976.

modelling selective h2s absorption and desorption

Documents

chemical engineering

give reliable results

liquid lm thickness

mass transfer coefcient

carbon dioxide absorption

regenerated amine solution

chemical engineering

carbon dioxide