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Modeling study on CO 2 and H 2 S simulta

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Journal of Industrial and Engineering Chemistry 34 (2016) 344–355
Contents lists available at ScienceDirect
Journal of Industrial and Engineering Chemistry
journal homepage: www.elsevier.com/locate/jiec
Modeling study on CO2 and H2S simultaneous removal using
MDEA solution
Tohid Nejad Ghaffar Borhani a, Morteza Afkhamipour b, Abbas Azarpour c, Vahid Akbari d,
Seyed Hossein Emadi e, Zainuddin A. Manan f,*
a
Centre for Process Systems Engineering, Department of Chemical Engineering, Imperial College London, London SW72AZ, UK
National Iranian Gas Company (NIGC), South Pars Gas Complex (SPGC), Asaluyeh, Iran
Chemical Engineering Department, Universiti Teknologi Petronas, Bandar Seri Iskandar, 31750 Tronoh, Perak, Malaysia
d
Department of Process Engineering, Razi Petrochemical Company, Bandar-e Emam Khomeyni, Iran
e
Chemical Process Engineer, Engineering Department for Environmental and Chemical Engineering University of Calabria, Rende (C.S.), Italy
f
Process Systems Engineering Center (PROSPECT), Faculty of Chemical and Energy Engineering, Universiti Teknologi Malaysia, 81310 Johor Bahru, Johor,
Malaysia
b
c
A R T I C L E I N F O
Article history:
Received 28 September 2015
Received in revised form 27 November 2015
Accepted 3 December 2015
Available online 14 December 2015
Keywords:
Methyldiethanolamine
Mathematical model
CO2 and H2S absorption
Rate-based
Packed column
Sensitivity analysis
A B S T R A C T
This study presents a rate-based model of an absorber packed column for simultaneous absorptions of
acid gases into methyldiethanolamine (MDEA) aqueous solution. The model is in good agreement with
experimental data. The parametric study showed that the concentration of acid gases in the sweet gas
stream increases by decrease in the specific surface area of packing. The peak of selectivity factor
decreases with the increase in the mole ratio of CO2/H2S in the gas feed along the packed column. The
sensitivity analysis reveals that selecting the accurate correlations of the gas-side mass transfer
coefficient and specific surface area is vital.
ß 2015 The Korean Society of Industrial and Engineering Chemistry. Published by Elsevier B.V. All rights
reserved.
Introduction
Due to operability, economic, and environmental factors, the
impurities such as CO2, H2S, and other acid gases must be removed
from gas streams. These impurities are typically present in oil and
gas industry pipelines containing natural gas, refinery gases,
syngas, synthetic natural gas, and hydrogen manufacture [1,2]. The
acid gases concentration in different gas streams may vary, from
some parts per million (ppm) to 50% by volume. In order to prevent
the corrosion of pipelines and equipment, and also meet the
treated gas specifications, the capture and removal of acid gases to
a concentration of less than 1% for carbon dioxide and 4 ppm for
hydrogen sulphide is necessary [3]. Absorption with aqueous
solution of alkanolamines is the most common process for acid gas
removal. On the other hand, methyldiethanolamine (MDEA) has
been used as solvent in many plants due to its selectivity to
* Corresponding author. Tel.: +60 75535501/+60 7 5535609; fax: +60 7 5588166.
E-mail addresses: t.ngborhani@imperial.ac.uk (T.N.G. Borhani),
zain@cheme.utm.my (Z.A. Manan).
hydrogen sulfide absorption [1]. Selectivity of H2S over CO2 is the
direct result of the facts that (1) H2S and CO2 absorption rates are
controlled by resistances to mass transfer in the gas and liquid
phases, and (2) lower reaction rate of MDEA with CO2 as compared
to H2S, which leaves the absorption rate of CO2 almost completely
unenhanced by reaction [4]. Taking advantage of the slower
reaction rate of CO2 with MDEA, the absorption process can be
designed to achieve the complete removal of H2S, while only part
of the CO2 is absorbed into the MDEA solution [1]. There are a
number of studies on modeling of H2S selective absorption process
from gas streams utilizing the MDEA aqueous solutions [4–6].
Glasscock and Rochelle [7] proposed a general methodology for
CO2 and H2S absorption into the mixture of DEA and MDEA. They
compared the rigorous and approximate methods for the simulation. The simplified eddy diffusivity theory was used to simulate
the liquid-phase hydrodynamic characteristic in the rigorous
model. Pacheco and Rochelle [5] developed a framework to
perform the selective absorption of H2S using MDEA solution from
gas stream containing CO2. They used the Maxwell-Stefan and
enhancement factor theories in the model. Furthermore, the
performances of trayed and packed columns in the selective
http://dx.doi.org/10.1016/j.jiec.2015.12.003
1226-086X/ß 2015 The Korean Society of Industrial and Engineering Chemistry. Published by Elsevier B.V. All rights reserved.
T.N.G. Borhani et al. / Journal of Industrial and Engineering Chemistry 34 (2016) 344–355
Nomenclature
aw
ap
Ac
B
CMDEA
I
CCO
2
CP,i
CP,G
CP,L
DL,i
DG,i
DCO2 ;L
DMDEA,L
dp
ECO2
E1
hg
Ha
HCO2
H H2 S
DhH2 O
DH H 2 S
DHCO2
kG,i
kL,i
KG,i
K2t
kli
L
Ni
Pi
Pi
TG
TL
UG
UL
n
xi
yi
Z
specific wetted area for mass transfer (m2/m3)
specific surface area of packing (m2/m3)
cross-sectional area of the column (m2)
concentration of MDEA in the bulk liquid (kmol/
m3)
concentration of CO2 at the gas-liquid interface
(kmol/m3)
molar heat capacity of component i in the liquid
phase (kJ/kmol K)
molar heat capacity of the gas (kJ/kmol K)
molar heat capacity of the liquid (kJ/kmol K)
diffusivity of component i in liquid (m2/s)
diffusivity of component i in gas (m2/s)
diffusivity of CO2in liquid (m2/s)
diffusivity of MDEA in liquid phase (m2/s)
nominal packing size (m)
CO2 enhancement factor
enhancement factor for instantaneous reaction
heat transfer coefficient in gas (kJ/K m2 s)
Hatta number
Henry’s law constant of CO2 in MDEA solution
(kPa m3/kmol)
Henry’s law constant of H2S in MDEA solution
(kPa m3/kmol)
heat of condensation of H2O (kJ/kmol H2O)
heat of absorption of H2S (kJ/kmol H2S)
heat of absorption of CO2 (kJ/kmol CO2)
gas-side mass transfer coefficient of component i
(kmol/m2 s kPa)
liquid-side mass transfer coefficient of component i
(kmol/m2 s kPa)
overall mass transfer coefficient of component i in
the gas phase (kmol/m2 s kPa)
second-order reaction rate constant (m3/kmol s)
liquid-side mass transfer coefficient (without
chemical reaction) of component i (m/s)
molar liquid flow (kmol/s)
molar flux of component i (kmol/m2 s)
partial pressure of component i in the bulk gas
phase (kPa)
partial pressure of component i in gas phase in
equilibrium with the liquid phase (kPa)
gas-phase temperature (K)
liquid-phase temperature (K)
gas superficial velocity (m/s)
liquid superficial velocity (m/s)
molar gas flow (kmol/s)
liquid-phase mole fraction of component i (kmol/
kmol)
gas phase mole fraction of component i (kmol/
kmol)
height of packing (m)
Greek letters
mG
gas viscosity (Pa s)
mL
liquid viscosity (Pa s)
rL
liquid density (kg/m3)
rG
sc
sL
345
gas density (kg/m3)
surface tension of packing (N/m)
surface tension of liquid (N/m)
Acronyms
diethanolamine
DEA
methyldiethanolamine
MDEA
Intalox Metal Tower Packing
IMTP
absorption of H2S were compared. Bolhàr-Nordenkampf et al. [4]
adapted the rate-based algorithm presented in Aspen Plus for gas
absorption and desorption using MDEA solution. The liquid phase
mass transfer coefficients, which were developed by Brunazzi,
were fitted to the experimental data. In addition, they developed a
new enhancement factor in this study and validated their model
against the experimental data obtained from the literature. Mandal
and Bandyopadhyay [3] performed theoretical and experimental
studies on the simultaneous absorption of CO2 and H2S into a
solution containing both MDEA and DEA. They used a wetted wall
column to investigate the effect of contact time and the
concentration of amines on the selectivity and absorption rate.
The Higbie’s penetration theory was utilized to model the diffusion
of acid gases in the mixture of amines. They found a good
agreement between the model results and the experimental data
of the absorption rate in the solution containing water, MDEA, and
DEA. Falahat et al. [6] used Aspen Plus and a rate-based approach
[4] to model and simulate the CO2 absorption using MDEA aqueous
solution. They compared results obtained from Aspen Plus and the
rate-based approach, and validated the model against pilot plant
data obtained from the literature. Moioli et al. [8] used Eddy
diffusivity theory instead of film theory in Aspen Plus using an
external subroutine to simulate the CO2 and H2S absorption from
gas streams. The authors employed different correlations to
calculate the density and viscosity of the amine solution. In
addition, they have also modified the parameters for VLE
calculations and validated the simulation using data from the
literature.
There are several commercial and academic software tools as
well as mathematical models developed to predict the behavior of
the acid gas capturing process from various gas streams. However,
the software tools are typically expensive to obtain, and the
mathematical models are mostly customized, and therefore
limited in terms of applicability as well capability. In these
studies, two different modeling approaches have been reported:
the equilibrium-stage models and the non-equilibrium stage
models (rate-based models).
The conventional equilibrium stage model assumes that the
vapor and liquid phases leaving each stage are in thermodynamic
equilibrium [9]. However, the equilibrium can be considered only
at the vapor and liquid interfaces. On the other hand, distillation
and absorption are, by nature, non-equilibrium processes
[10]. Therefore, the efficiencies such as the Murphree and pointby-point efficiencies (for tray columns) and the height equivalent
of a theoretical plate (HETP) (for packed columns) have been used
to represent the departure of the equilibrium (ideal) from the real
condition. The accuracy of the equilibrium model depends on the
proper guess of these efficiencies. However, accurate prediction of
the appropriate HETP is difficult [11]. On the other hand, the ratebased model takes into account of the mass and heat fluxes across
gas–liquid interface, and entirely avoids the approximations of
efficiency and HETP [12,13]. Therefore, the rate-based models are
found to be more superior to the traditional equilibrium-based
models. In rate-based model, it is assumed that the mechanical,
346
T.N.G. Borhani et al. / Journal of Industrial and Engineering Chemistry 34 (2016) 344–355
chemical, and thermodynamic equilibriums exist only at the fluid
interface [9]. In the approach presented in this paper, in addition to
the equations related to equilibrium modeling, the mass and heat
transfer rate equations are considered.
Pandya [14] proposed a general rate-based approach to model
the gas absorption using chemical solvents. Differential mass and
enthalpy balances, explicit expression for enhancement factor, and
assumptions such as ideal gas solution for gas phase and ideal
solution for liquid phase were included in this approach. The model
was applied for CO2 absorption in a packed column using MEA
aqueous solution, although the results were not validated against
the experimental data. Numerous mathematical models have been
developed with different assumptions based on Pandya’s approach
for the simulation of CO2 absorption process using amine solutions
[15–17].
In this study, the rate-based model is constructed based on
Pandya’s procedure for the simultaneous reactive absorption of
H2S and CO2 into an aqueous solution of MDEA in packed
column. Molar balance equations of the gas and liquid flow rates
were considered as a function of mass transfer flux of H2S, CO2,
and H2O, and the energy balance for liquid phase was considered
as a function of heat of absorption for H2S and CO2. The model
was validated by comparing the simulation results with
experimental data reported in the literature. In addition, a
sensitivity analysis of the simulation results was made to
investigate the effect of two different mass transfer correlations
on the hydraulic parameters and thermodynamic properties. It
should be noted that in the previous studies, the Pandya’s
procedure was not used to develop a model for simultaneous
absorption of H2S and CO2 in packed column employing the real
industrial data, and we did not find sensitivity analysis in the
literature on the same system.
Model development
Governing equations of packed column
A rigorous and detailed description of a model can be utilized as
a reference model for sensitivity studies whereby significant and
insignificant parameters are recognized. Considering a two-phase
stage operation like those in gas–liquid contactors, the balance
equations for the liquid and gas phases have to be taken into
account [18]. Therefore, the governing equations of a packed
column model are presented below:
Total material balance for the gas and liquid phases
The total mole balance for the gas phase is:
X
dG
¼ aw AC
Ni
dz
i ¼ H2 S; CO2 ; and H2 O
When acid gases are transferred through the phase boundary
and react to form a new compound, there is no net increase in the
total moles of the liquid phase. Therefore, the change in the total
liquid flow rate is only due to the evaporation of water, which is
described in the following equation:
dL
¼ aw AC N H2 O
dz
(2)
Component material balance for the gas and liquid phases
Variation of mole fraction of component i in the gas phase along
the height of the column is given by the following equation:
G
dyi
dG
¼ aw AC Ni
þ yi
dz
dz
i ¼ H2 S; CO2 ; H2 O
1. The system operates at steady-state condition.
2. The absorption column is under adiabatic mode of operation.
3. The specific wetted area is the same for both heat and mass
transfer.
4. The liquid-phase heat transfer resistance is small as compared to
that of the gas phase, and the interface temperature is thus the
same as the bulk temperature.
5. Flow is one-dimensional in the z-direction, and the variation of
concentration and temperature in the radial direction is
insignificant.
6. No chemical reactions take place in the gas phase.
7. H2S, CO2, and H2O are the only species transferred across the
interface.
(3)
The basic components, which are considered in the liquid
+
phase, are HCO
3 , CO2, H2O, H2S, HS , MDEA, and MDEAH , and the
main reactions occurring in the liquid phase are as follows:
KCO2
In order to model the simultaneous absorption of CO2 and
H2S from a gas stream utilizing a packed absorber column and
MDEA aqueous solution, the mathematical modeling approach
was used in this study. Material and energy balances were
written around a differential element of the column. The
two-film theory, which is the simplest theory of mass transfer
and leads to a set of steady state equations, was utilized in the
model. The liquid solvent and sour gas flow counter-currently.
In this case, the packing material, which determines the specific
absorption area, is packed from Z = 0 to L. Envelope III is a
volume element in the differential packed height (Dz) of the
absorber, which is divided into gas- and liquid-phase elements
denoted by envelopes I and II, respectively. CO2 and H2S diffuse
from the gas phase to the liquid phase and react with amine to
produce nonvolatile products. The main assumptions for the
model development are summarized below:
(1)
MDEAHþ þ HCO
3 , MDEA þ CO2 ðaq:Þ þ H2 O
KH2 S
MDEAHþ þ HS , MDEA þ H2 Sðaq:Þ
(R1)
(R2)
By considering the stoichiometric relations (reactions (R1) and
(R2)), component i variation in the liquid phase along the column
can be considered by the following equation:
L
dxi
dL
¼ aw AC N i
þ xi
dz
dz
(4)
In Eqs. (1)–(4), Ni is the molar flux of component i across the
gas–liquid interface, aw is the surface area of wetted packing per
unit volume, G is the total gas flow, L is the total liquid flow, AC is
the cross-sectional area of the column, yi is the gas mole fraction of
component i, and xi is the liquid mole fraction of component i.
Energy balance for the gas and liquid phases
The absorption of acid gases (H2S and CO2) in the chemical
solvent results in the release of heat. Following absorption,
exothermic chemical reactions take place between MDEA and
acid gases (H2S and CO2) [19]. Heat of solution as well as the
chemical reactions enhance the temperature of liquid stream and,
accordingly, increase the temperature of gas stream because the
gas stream is in direct contact with the liquid stream along the
column. The differential energy balances for the gas and liquid
phases around the differential height of the column are as follows:
dT G
hG aw AC
ðT G T L Þ
¼
dz
VCpG
(5)
T.N.G. Borhani et al. / Journal of Industrial and Engineering Chemistry 34 (2016) 344–355
ia A
dT L hX
w C
¼
Ni C pi hG ðT G T L Þ
dz
lC pL
X
a A
w C
þ
N i DH i þ N H 2 O DH H 2 O
;
LC pL
347
Using the two-film model, the overall mass transfer coefficients
for H2S and CO2 are expressed as follows [22]:
H H2 S
1
1
¼
þ
K H2 S;v kH2 S;v kH2 S;L
i
¼ CO2 ; H2 S
(6)
where TG and TL are temperature of the gas and the liquid phases,
respectively. DHi is the heat of absorption of component i, DHH2 O is
the heat of condensation of water, Cpi is the molar heat capacity of
component i in the liquid phase, CpG is the molar heat capacity of
the gas phase, CpL is the molar heat capacity of the liquid phase, and
hG is the heat transfer coefficient of the gas phase. The Chilton–
Colburn analogy was utilized to calculate the heat transfer
coefficient of the gas phase [20]. The heat of absorption of CO2
and H2S into the MDEA aqueous solution was extracted from Posey
and Rochelle [19]. The Gibbs–Helmholtz equation and Antoine
equation were applied to estimate the heat of condensation of
water [21].
HCO2
1
1
¼
þ
K CO2 ;v kCO2 ;v kCO2 ;L ECO2
(9)
(10)
The thermodynamic and transport properties incorporated in
the model along with the relevant literature sources are given in
Table 1.
Enhancement factor and reaction kinetics
The mass transfer flux between the gas phase and the liquid
phase is given by the following equation [22]:
In a reactive absorption process, it is necessary to address the
effects of chemical reactions on the rate of mass transfer. In
general, three methods are considered to take into account the
chemical reactions in the modeling and simulation endeavor.
These methods include the chemical equilibrium constants,
reaction rate expressions, and enhancement factors (E). In this
study, the effect of chemical reactions is expressed in term of the
enhancement factor, which is the ratio of the mass transfer
enhanced by a reaction over the mass transfer without the reaction
[31]:
Ni ¼ K i;G ðPi Pi Þ
ECO2 ¼
Mass transfer
(7)
Pi
where Pi is partial pressure of component i in the gas bulk,
is
partial pressure of component i in equilibrium with the liquid
phase, Ki,G is the overall mass transfer coefficient for component i
(CO2 and H2S), and the term ðP i Pi Þ represents the driving force for
mass transfer. The thermodynamic model presented by Posey and
Rochelle [19] was utilized for calculation of the equilibrium partial
pressures of H2S and CO2 over the aqueous MDEA solution. The
equilibrium partial pressure of H2O ðPH
Þ over the MDEA solution
2O
was estimated using the Antoine equation [21]. It was assumed
that the liquid-side resistance against mass transfer of water vapor
of the solvent is negligible. Consequently, the overall mass transfer
coefficient for the water vapor is equal to the mass transfer
coefficient in the gas phase, which is signified by the following
relation:
1
1
¼
K H2 O;G kH2 O;G
(8)
kCO2 ;L
kCO2 ;L
(11)
The enhancement factors can be calculated using two
different methods: by fitting experimental results and by
theoretical derivation using some simplified assumptions for
the model [32]. Commonly, the enhancement factors depend on
the reaction type (reversible or irreversible), the chemical
kinetics, liquid composition, physical and transport properties
of the components in the liquid, the reaction order and
stoichiometry, and the model considered for the mass transfer
[33]. Therefore, enhancement factors are affected by such
parameters as temperature, solvent concentrations, acid gas
loadings, kinetic constants, and so on. Enhancement factors are
only calculated for the liquid phase, where chemical reactions
occur. In CO2 absorption process, the liquid phase mass transfer
resistance is important, and, therefore, enhancement factor
should be used. Various types of enhancement factors are
demonstrated in the literature [33].
Table 1
Thermodynamic and transport properties used in the absorber model.
Property
Source
Comment
Gas density
Density of MDEA solution
Specific heat of liquid solution
Specific heat of gas components
Thermal conductivity of the gas
Diffusivity of CO2, H2S and water in the gas phase
Diffusivity CO2 in MDEA solution
Diffusivity of H2S in MDEA solution
Diffusivity of MDEA in liquid phase
[23]
[24]
[25]
[26]
[26,27]
[27]
[24]
[28]
[29]
Gas viscosity
viscosity of the MDEA solution
The second-order reaction rate constant
for the reaction between CO2 and MDEA
Selectivity factor (S)
Henry’s law constant of H2S in MDEA solution
[27]
[24]
[5]
Soave–Redlich–Kwong equation
It is an exponential function of liquid phase temperature and MDEA mass fraction
Linear mixing
DIPPR
DIPPR for pure compounds, Mason and Saxena method for mixture
Chapman–Enskog–Wilke–Lee and Fuller methods
It is a polynomial function of liquid phase temperature and MDEA mass fraction
DH2 S;MDEA ¼ 2:24109 T l m0:725
l
DMDEA;L m0:6
¼ DMDEA;H
m0:6
L
H2 O
2O
DMDEA;H2 O ¼ exp 13:088ð2360:7=T L Þ24:727105 C am
Chapman–Enskog for pure compounds and mixing rule for mixture
It is a function of liquid phase temperature and MDEA mass fraction
k2t ¼ 2:576109 expð6024=T Þ
Henry’s law constant of H2S in the pure water
Henry’s law constant of CO2 in MDEA solution
[19]
[24]
[11]
[30]
S ¼ xH2 S =xCO2 = yH2 S =yCO2
HH2 S ¼ ð1bðxMDEA ÞÞðHH2 S;H2 O ÞÞ
b = 0.033 MWMDEA 0.917
HH2 S;H2 O ¼ expð18:1937ð2808:5=T L Þ þ 2:5629Ln T L 0:01868Þ
It is a function of liquid phase temperature and MDEA mass fraction
T.N.G. Borhani et al. / Journal of Industrial and Engineering Chemistry 34 (2016) 344–355
348
The general determination of enhancement factor requires the
solution of a set of partial differential equations governing the
simultaneous diffusion mass transfer and chemical reactions in the
liquid film [34]. The system of equations can be solved numerically,
but in the case of an absorption column the calculations is
complicated, and, therefore, often the analytical expressions for
enhancement factors are applied. The analytical expression for
enhancement factor depends on the mass transfer theory applied
as well as the rate of absorption. The expressions, which are
available for the enhancement factors for the mass transfer
described by the film theory, penetration, and surface renewal
theories, are functions of a Hatta number [11]. Hatta number is a
dimensionless number. The term in numerator illustrates the
contribution of the reaction, and the denominator implies the
physical mass transfer in the liquid film. Three various regimes of
reaction rates can be considered based on the amount of Hatta
number confirming the necessity of the film discretization for
liquid phase [35,36].
For H2S, the resistance to mass transfer lies in the gas phase, and
no enhancement factor is required for the absorption rate
calculations [4]. In contrast, for CO2 the liquid-phase mass transfer
resistance is important, and an enhancement factor is needed for
the absorption rate calculations. In this study, to calculate the CO2
enhancement factor, two cases were considered as follows:
For large values of enhancement factor for fast reaction and
Hatta numbers lower than 2, the enhancement factor is given by
[37]:
ECO2 ¼
Ha
tanhðHaÞ
(12)
The enhancement factor for infinite fast reaction (E1) values
lower than 100 and Hatta numbers larger than 2 was calculated by
[4]:
ECO2 ¼
E1 1=E1
1
þ 3=2
Ha3=2
E1
for the unknown variables. The equations of the model were solved
using finite difference method employing the initial values in the
range between bottom and top of the column in order to find the
amount of each variable at the end of packed column. The obtained
values were compared with the real data of the column. If there
was much difference between the real data and the calculated
values, the initial guesses were corrected. A simplified flow chart of
the calculation steps used in the present model is shown in
Fig. 1. According to the flowchart, the algorithm contains the
following steps:
1. Selection of a value for differential height along the packed
column (Dz).
2. Introduction of the variables like temperature, mole fraction,
liquid flowrate, and inlet gas to the absorber column.
3. Some amounts assumed for temperature, mole fraction and
liquid flow rate at the outlet of the column.
4. If the counter i is less or equal to the imax, then the algorithm
will go to the next step of the calculation otherwise the
algorithm will be terminated.
5. If i imax, the calculation of all the physical and chemical
properties of the liquid and gas phases is carried out.
6. Calculation of overall mass transfer coefficient for gas phase.
7. Calculation of the mass transfer flux using Eq. (7).
8. Calculation of the partial derivatives for mole fractions,
flowrate, and temperature in liquid and gas phases.
9. Definition of the next differential height.
10. Calculation of the outlet variables in the next Dz from bottom
to the top of the column. If we consider all the variables in the
column by P, the amount of variables in the next Dz can be
calculated by Pnext = P + Dz (dP/dz).
!2=3
(13)
where Hatta number and enhancement factor for infinitely fast
reaction were expressed as [37]:
qffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi
B
K 2t DCO2 ;L CMDEA
(14)
Ha ¼
kCO2 ;L
E1 ¼ 1 þ
B
DMDEA;L CMDEA
I
DCO2 ;L
CCO
(15)
2
B
where DCO2 ;L is the diffusivity of CO2 in MDEA solution, CMDEA
is the
concentration of MDEA in the bulk liquid, DMDEA,L is the diffusivity
I
of the MDEA in liquid phase, and CCO
is the concentration of CO2 at
2
the gas–liquid interface.
Numerical solution
The system of differential Eqs. (1)–(6) described in the previous
section was solved simultaneously to find the composition of CO2
and H2S and temperature profiles along the column. For an
absorption column that operates in countercurrent flow, only the
inlet gas and inlet liquid flow conditions are known. The outlet gas
and outlet liquid flow conditions are not completely clear at the
end of the column, and, consequently, the problem is a two-point
boundary value problem. The shooting method is recommended
for such problems [11,14,15]. The total height of the column was
divided into 40 differential elements of height (DZ) for structured
packing (Mellapak 250) and 50 for random packing (Intalox
Metal Tower Packing (IMTP)). The bottom of the column was set as
the starting point, and the values were assumed as initial condition
Fig. 1. Simplified flow chart for the numerical solution.
T.N.G. Borhani et al. / Journal of Industrial and Engineering Chemistry 34 (2016) 344–355
Table 2
Operating conditions and gas stream composition for Case I [4].
D1
Parameter
Gas flow rate (kmol/h)
Inlet L/G ratio ()
Gas temperature (8C)
Liquid temperature (8C)
MDEA concentration (wt.%)
Pressure (bar)
Liquid H2S loading (mol/mol amine)
Liquid CO2 loading (mol/mol amine)
Composition in gas stream
CO2 (vol.%)
H2S (vol. ppm)
D6
110
3.52
40.6
25
50
1.1
0.0054
0.00016
140
3.52
41.3
25
50
1.1
0.0054
0.00016
3.6
8000
3.6
8000
11. Repetition of steps 3 to 10 in order to achieve the proper values
in the output of the packed column.
12. Print of the mole fraction, flowrate, and temperature in gas and
liquid phases along the packed column.
13. Termination of the algorithm.
349
the height of the column were not available for the close
validation of CO2–H2S–MDEA system. According to Fig. 2(a) and
(b), it can be figured out that the H2S decreases exponentially and
in the middle of the column it reaches very low amounts of ppm
but decrease of the CO2 along the column has linear form which
reaches a minimum at the outlet of the packed column. As it is
obvious from Fig. 2(c), the liquid temperature decreases
dramatically, and gas temperature increases slightly until the
middle of the column which two profiles reaches each other and
show the flat behavior till the end of column. Fig. 2(d) illustrates
the profile of the gas and liquid flowrate along the column. It
should be noted that the liquid and gas flowrate profiles must be
analyzed vice versa. CO2 and H2S are absorbed by MDEA aqueous
solution as the gas goes to the top of the column encountering the
flow rate reduction. The gas flowrate profile declines from the
bottom to the top of the column smoothly. In contrast, the liquid
flowrate profile considerably rises from the top to the bottom of
the column. Two profiles cross each other at the middle of the
column. It is interesting to note that the predicted concentration
and temperature profiles shown in these figures are very similar to
those obtained using absorption model linked to the Aspen Plus
simulator by Bolhàr-Nordenkampf et al. [4].
Results and discussion
Case II
The proposed model was applied for two practical cases. The
first case was extracted from the work of Bolhàr-Nordenkampf
et al. [4], and the second case was related to an industrial real unit,
which is described by details in the following sections:
Case I
For the first case study, the experimental work of BolhàrNordenkampf et al. [4] is used, who reported six measurements
(D1–D6) of H2S and CO2 absorption into an aqueous MDEA solution
in an absorber column. The experiments were implemented in a
0.9 m diameter column filled with Mellapak 250, with a total
packing height of 5.486 m and pressure of 1.1 bar. Out of the
6 experimental measurements performed by Bolhàr-Nordenkampf
et al. [4], two measurements (D1 and D6) were selected to validate
the model for low (D1) and high (D6) gas flow rates. The operating
conditions and the composition of the gas stream of two
measurements are given in Table 2.
In Table 3, a comparison between the experimental data and the
calculated values for CO2 and H2S concentration in the sweet gas
for low (D1) and high (D6) gas flow rates is given. According to
Table 3, it can be seen that there is a good agreement between the
experimental and modeled values of both CO2 and H2S in case D1
but there is some deviation in the case of H2S in D6 which may be
due to the high gas flowrate in case D6. However, the unit of the
H2S amount is based on ppm, and model prediction is acceptable in
industrial point of view.
Three types of profiles are illustrated in Fig. 2, which are
concentration profiles of CO2 and H2S in the gas phase and flowrate
profiles of temperature, gas and liquid through the packing height.
It should be noted that concentration and temperature data along
Table 3
Comparison of simulation results for the absorber packed column with
experimental data.
Parameter
CO2 outlet concentration
(mole fraction)
H2S outlet concentration
(mol ppm)
Experimental data
Simulation result (This
Work)
D1
D1
0.03
120.0
D6
0.035
28.0
0.0297
116.0
D6
0.0341
19.0
For the second case study, the operating data gathered from
South Pars Gas Complex (SPGC), which is located in Assaluyeh,
south of Iran, was employed. Before giving a description of the Case
II, the gas sweetening process unit of SPGC was described. The
scheme of the gas sweetening process unit is shown in Fig. 3. The
sour gas enters the unit through a separator, and is filtered to
remove any free liquid or entrainment solids (101-D-101 and 101F-101). The filtered gas containing acid gases (un-treated gas) is
channeled to the bottom of the absorber column. In the tray
column, the un-treated gas stream has a countercurrent contact
with the aqueous lean solution of MDEA. Acid gases mean CO2, and
H2S separate from un-treated gas stream, transfer to the lean
solution, and consequently make rich solution. The treated gas
leaves the tray absorber column at the top, and is sent to the
dehydration unit. In order to recover the hydrocarbons from the
rich solution, this solution is removed from the bottom of the
absorber to perform the flash process in a rich amine flash drum
(101-D-103). Therefore, hydrocarbons co-absorbed in the rich
amine solution absorb in the flashed gas phase. The flashed gas
phase from 101-D-103 also contains CO2 and H2S, and, thus, an
extra sweetening step with a split-stream of lean MDEA is
implemented to meet the required H2S specification (4 ppm H2S)
(101-C-103). The fuel gas absorber (101-C-103) is a random
packing column which is packed with Intalox Metal Tower Packing
of 15 mm (IMTP 15), and is mounted on the top of the rich amine
flash drum (101-D-103). The sweet flash gas is then routed to the
fuel-gas network. It mainly contains light hydrocarbons and some
CO2. In desorber column (101-C-102), the rich amine solution is
regenerated by means of stripping steam supplied by reboiler of
the column. In order to improve the purification of the MDEA
solution, the desorber is equipped by a reflux system. The
performance of the desorber column is better at high temperatures
and low pressures. The gas, which mostly consists of acid gases and
water vapor, exits the top of the desorber, and is processed for
sulfur recovery unit (SRU). The heat of lean MDEA solution, which
leaves the reboiler of the desorber column, is transferred to the rich
MDEA solution using a heat exchanger (101-E-101). Prior to
recycling the lean amine back to the absorber amine tank (101-T101) and high pressure amine pump (101-P-101), the amine is
cooled to a temperature that is 15 8C higher than the sour gas using
a heat exchanger (101-E-103).
T.N.G. Borhani et al. / Journal of Industrial and Engineering Chemistry 34 (2016) 344–355
350
9000
(a)
H 2 S mole ppm in gas phase
8000
7000
6000
5000
4000
3000
2000
1000
0
0
1
2
3
4
5
6
CO2 mole fraction in gas phase
Height of the column (m)
0.038
0.037
0.036
0.035
0.034
0.033
0.032
0.031
0.03
0.029
0.028
(b)
0
1
2
3
4
5
6
Height of the column (m)
315
Temperature (K)
313
311
Gas Temperature Profile
309
Liquid Temperature Profile
(c)
307
305
303
301
299
297
295
0
1
2
3
4
5
6
Height of the column (m)
Gas molar flowrate (Kmol/h)
(d)
114
362
113
Gas flow rate profile
361
112
Liquid flow rate profile
360
111
359
110
358
109
357
108
107
356
106
355
105
Liquid molar flowrate (Kmol/h)
363
115
354
0
1
2
3
4
Height from column bottom (m)
5
6
Fig. 2. Concentration and temperature profiles along the packed column for Case I (a): profile of H2S in gas phase (b): profile of CO2 in gas phase (c): gas and liquid temperature
profiles (d): gas and liquid molar flow rate profiles.
This study focuses on the modeling of a packed column. For this
reason, only the simulation of the fuel absorber column (101-C103) was considered. The absorber column is a random packed
column (IMTP-15) with a diameter of 0.49 m and a total packing
height of approximately 3.1 m. The flashed gas stream containing
1.8 vol.% CO2 and 13,000 vol. ppm H2S is cleaned by a 46 wt.%
MDEA solution at a pressure of 7.5 bar. The input conditions and
gas composition for the absorber column of the plant are
summarized in Table 4.
Table 5 indicates the absolute errors obtained from the
comparison between the simulation results and the available
data of the industrial absorber packed column. This table shows
T.N.G. Borhani et al. / Journal of Industrial and Engineering Chemistry 34 (2016) 344–355
351
Fig. 3. Layout of the gas-sweetening unit at SPGC.
that the proposed model has been able to predict the exit
concentration and temperature from the packed column very well.
According to Table 5, the absolute error for model prediction is only
0.5%, 0.48%, and 1.85% for the gas outlet mole flow rate, the
temperature and the CO2 outlet concentration, respectively. It
should be mentioned that the H2S amount in the outlet stream
reported in the experimental data is less than 4 ppm. The model
predicted the H2S amount 1.14 ppm that is less than 4 ppm
implying an acceptable result.
Similar to Case I, three different profiles over the packing height
are given in Fig. 4 for Case II. According to Fig. 4(a) and (b), the
predicted gas concentration profiles for H2S and CO2 along the
Table 4
Operating conditions and gas stream composition for Case II.
Parameter
Values
Gas flow rate (kmol/h)
Liquid flow rate (kmol/h)
Gas temperature (8C)
Liquid temperature (8C)
MDEA concentration (wt. %)
Pressure (bar)
Liquid H2S loading (mol/mol amine)
Liquid CO2 loading (mol/mol amine)
43
34.75
27
38.5
46
7.5
0.00011
0.00007
Mole fraction of components in the gas stream
CH4
C2H6
C3H8
H2O
N2
i-C4H10
n-C4H10
i-C5H12
n-C5H12
84.73
5.44
1.851
0.35
3.438
0.31
0.492
0.152
0.136
packed column obtained from the model. As the gas stream moves
up the column, H2S and CO2 are absorbed by the MDEA solution,
resulting in their concentrations to decrease along the bed height.
Based on Fig. 4(a) and (b), there is a clear difference between the
absorption of H2S and CO2. CO2 has an almost constant gradient
along the packing area, which indicates that the rate of mass
transfer of CO2 is higher than its rate of reaction with MDEA. It can
be concluded that the reaction between CO2 and MDEA is limited
and slow. This is completely the reverse for H2S. While the reaction
of H2S with MDEA is instantaneous, its mass transfer rate is slow.
Note that although H2S reacts chemically with MDEA immediately
even at the bottom of the column, the CO2 is initially dissolved
physically before undergoing a chemical reaction with MDEA.
Fig. 4(c) illustrates the typical temperature profiles of the gas and
liquid along the packed column. It should be taken account that a
temperature bulge occurs because when the liquid flows down the
packed column, it continuously absorbs the acid gases. Due to the
heat of reaction generated by the acid gases absorption there is a
continuous increase in the liquid temperature. The temperature
drop at the bottom of the column results from the cold gas entering
the bottom coming into contact with the hot liquid flowing
downwards. The cold gas absorbs heat from the hot liquid, causing
Table 5
Comparison of the simulation results of the absorber packed column with plant
data.
Parameter
Simulation
results
Plant
data
Absolute
error (%)
Gas outlet mole flow rate (kmol/h)
Gas outlet temperature (K)
CO2 outlet concentration (Mole fraction)
H2S outlet concentration (Mol ppm)
42.21
310.5
0.00795
1.14
42.0
312
0.0081
<4
0.5
0.48
1.85
–
T.N.G. Borhani et al. / Journal of Industrial and Engineering Chemistry 34 (2016) 344–355
352
H2S mole ppm in gas phase
14000
(a)
12000
10000
8000
6000
4000
2000
0
0
0.5
1
1.5
2
Height of the column (m)
2.5
3
CO2 mole fraction in gas phase
0.02
0.018
0.016
0.014
0.012
0.01
0.008
0.006
0.004
0.002
0
3.5
(b)
0
0.5
1
1.5
2
2.5
Height of the column (m)
3
3.5
314
(c)
312
Temperature (K)
310
308
306
Gas temperature profile
304
Liquid temperature profile
302
300
298
0
0.5
1
1.5
2
2.5
3
3.5
Height of the column (m)
44
Gas molar flow rate (kmol/h)
(d)
35.5
43.6
35.4
Gas flow rate profile
Liquid flow rate profile
43.4
43.2
35.3
35.2
43
35.1
42.8
35
42.6
42.4
34.9
42.2
34.8
Liquid molar flow rate (kmol/h)
35.6
43.8
34.7
42
0
0.5
1
1.5
2
2.5
3
3.5
Height of the column (m)
Fig. 4. Concentration and temperature profiles along the packed column for Case II (a): profile of H2S in gas phase (b): profile of CO2 in gas phase (c): gas and liquid
temperature profiles (d): gas and liquid molar flow rate profiles.
its temperature to decrease. This leads to a temperature bulge at
the bottom of the packed column. Fig. 4(d) shows the variation of
the molar flow rate of gas and liquid streams along the packed
column. As can be seen, the gas flow rate decreases from the
bottom (inlet) to the top of the column, and the liquid flow rate
increases from the top to the bottom of the column. Two profiles
cross each other at the top of the column.
Parametric study of the absorber column
The simulation study was carried out to analyze the effect of
important process parameters on the packed absorber column
(101-C-103) performance. In this study, the effect of mole ratio of
CO2/H2S in the gas feed on selectivity, the effect of liquid flow rate
on the overall mass transfer coefficient of H2S and CO2, and the
T.N.G. Borhani et al. / Journal of Industrial and Engineering Chemistry 34 (2016) 344–355
0.018
MR=1
10
MR=1.1
8
MR=1.3
IMTP 50
IMTP 60
MR=1.2
0.018
IMTP 15
0.014
IMTP 25
MR=1.4
IMTP 40
0.016
IMTP 50
4
2
0
0.02
IMTP 40
0.016
0
0.5
1
1.5
2
2.5
3
Height of the column (m)
IMTP 60
0.012
0.014
0.01
0.012
0.008
0.01
0.008
Fig. 5. Effect of mole ratio of CO2/H2S in gas feed on selectivity (S) profiles along the
packed column (The MR represents the mole ratio of CO2/H2S in gas feed).
CO 2 mole fraction
12
6
0.022
IMTP 15
IMTP 25
H2 S mole fraction
H2S Selectivity factor(s)
14
353
0.006
0.006
0.004
0.004
effect of packing specific area on the concentration of acid gases in
sweet gas stream were discussed. Simulation results on the effect
of mole ratio of CO2/H2S on the H2S selectivity along the packed
column is presented in Fig. 5. The figure shows that increasing the
ratio of gas feed along the packed column, decreases the peak of
selectivity. Increasing the mole ratio of CO2/H2S increases the
solubility of CO2 in the solutions. As a result, the CO2 concentration
in the liquid phase will increase. However, due to the unchanged
partial pressure of H2S in the gas phase, the H2S amount in the
liquid phase does not increase. This causes the H2S peak selectivity
to decrease. Therefore, the packing height above the peak
selectivity performs the removal of CO2 from the gas stream
without a significant removal of H2S. This may result in a stream
with high concentration of hydrogen sulfide for the production of
pure sulfur downstream of the gas-sweetening unit (sulfur
recovery unit (SRU)). The simulation result on the effect of liquid
flow rate on the overall mass transfer coefficients of H2S and CO2
along the packed column is presented in Fig. 6. The results show
that the overall mass transfer coefficients increase with increasing
liquid flow rate along the packed column. This is because the
increase in the liquid flow rate results in the spread of liquid on the
packing surface and an increase in the effective interfacial area
between liquid and gas in the packing. A significant decline in the
mass transfer coefficient of CO2 is observed as compared with the
0.002
0.002
0
0
0
1
2
Height of the column (m)
Fig. 7. Effect of packing type on H2S and CO2 concentration along the packed
column.
mass transfer coefficient of H2S. This seems to be a reasonable
result since, in the presence of H2S, the lower amine molecules are
available to react with CO2. A change in the specific area of packed
bed by testing different types of random packing has an effect on
the concentration of H2S and CO2 in the exit gas stream as shown in
Fig. 7. The absorber column of the plant packed with Intalox Metal
Tower Packing (IMTP) type has the nominal diameter of 15 mm
(IMTP 15) and surface area of 270 m2/m3. Other IMTP with
different specific area values were tested in the model to evaluate
the possibility to improve the results. Results demonstrate that
IMTP 15 having the largest specific area than others IMTP gave the
best result of exit concentration of H2S and CO2 in the gas stream,
whereas the IMTP 60 having a surface area of 85 m2/m3 gave the
highest exit concentration of H2S and CO2 in the sweet gas stream.
0.399
0.0386
L=30(kmol/hr)
0.397
0.396
L=36 (kmol/hr)
0.0382
L=40 (kmol/hr)
0.0378
L=40( kmol/hr)
0.0374
L=36 (kmol/hr)
0.395
L=30 (kmol/hr)
0.037
0.394
0.0366
0.393
0.0362
0.392
0.0358
0.0354
0.391
0.035
0.39
0.0346
0.389
0.0342
0.388
0.0338
0.387
0.0334
0
0.5
1
1.5
2
2.5
3
Height of the column (m)
Fig. 6. Effect of liquid flow rate on the overall mass transfer coefficient of H2S and CO2 along the packed column.
Overall Mass Transfer Coefficient of CO2 (kmol/m2 h bar)
0.039
0.398
Overall Mass Transfer Coefficient of H2S (kmol/m2 h bar)
3
354
T.N.G. Borhani et al. / Journal of Industrial and Engineering Chemistry 34 (2016) 344–355
Sensitivity analysis of the absorber model
The parametric sensitivity analysis was conducted for the
absorption of CO2 and H2S into MDEA solution to examine the
effects of important parameters on the predicted H2S concentration in the sweet gas. The sensitivity analysis of the model in the
current study is based on the work of the Gabrielsen et al. [16]. The
studied parameters include hydraulic parameters and thermodynamic properties. The hydraulic parameters of the column consist
of specific wetted area and mass transfer coefficients for liquid and
gas sides. The thermodynamic properties include the Henry’s law
constant, the diffusivity of H2S in gas phase, the diffusivity of H2S in
MDEA solution, the gas viscosity, the liquid viscosity, liquid
density, and liquid surface tension. Errors of 50% to +50% were
introduced to the values of chosen parameters with two different
mass transfer correlations [38,39]. The corresponding errors of
change in the H2S concentration in the sweet gas were then
calculated. Since the varied properties are functions of variables
such as temperature and pressure, they cannot be considered as a
constant value in the column. Therefore, various methods were
presented to overcome the constraint mentioned. The main goal of
the sensitivity analysis is to study the change in properties within a
desirable range of temperatures and concentrations. In this study,
the measurement (D1) from Bolhàr-Nordenkampf et al. [4] was
chosen as a base case to perform the sensitivity analysis.
Sensitivity to thermodynamic properties
Fig. 8 shows the effect of errors in the thermodynamic
properties on the change in the H2S concentration in the sweet
gas for two different mass transfer correlations of structured
packing [38,39]. Errors of 50% to +50% were introduced to the
values of thermodynamic properties, and the corresponding errors
in the mole fraction of H2S in the sweet gas were determined. Fig. 8
indicates that the mass transfer correlation of Rocha et al. [39] is
less sensitive toward thermodynamic properties as compared with
the mass transfer correlation of De Brito et al. [38]. Under the
conditions encountered in this work, the model is more sensitive to
the diffusivity of H2S in the gas phase than to other properties. This
property is crucial when calculating the gas-side mass transfer
coefficient. For this reason, the Fuller and Chapman–Enskog–
Wilke–Lee equations [27] for diffusivity of H2S in gas phase were
tested to check the possibility of the results improvement. The
results signify that the Fuller equation has the biggest errors on the
change in the H2S concentration in the sweet gas. Therefore,
calculations were carried out with the Chapman–Enskog–Wilke–
Lee equation. The selection of proper correlations for the
calculations of the thermodynamic properties is very important
in obtaining reliable predictions of the hydraulic parameters. For
this reason, the sensitivity to hydraulic parameters is discussed in
the next section.
Sensitivity to hydraulic parameters
Fig. 9 illustrates the effect of errors in hydraulic parameters that
include the specific wetted area and the liquid and gas-side mass
transfer coefficients on the change in the mole fraction of H2S in the
sweet gas. Errors of 50% to +50% were introduced to the values of
the fluid dynamic parameters with two different mass transfer
correlations [38,39]. Fig. 9 demonstrates that the mass transfer
correlation of Rocha et al. [39] is less sensitive toward hydraulic
parameters as compared with the mass transfer correlations of De
Brito et al. [38]. The mole fraction of H2S in the sweet gas remains
unaffected by the errors in the liquid-side mass transfer coefficient.
Fig. 8. Effect of errors in the physical properties on H2S concentration in sweet gas using (a): mass transfer correlation of Rocha et al. [39] and (b): mass transfer correlation of
De Brito et al. [38].
T.N.G. Borhani et al. / Journal of Industrial and Engineering Chemistry 34 (2016) 344–355
355
%Deviation in the prediction of mole fraction H2S in
clean gas
8
Mass transfer coefficient,liquid side (De Brito et al., 1994)
Mass transfer coefficient,gas side (De Brito et al., 1994)
Specific wetted area (De Brito et al., 1994)
Mass transfer coefficient,liquid side (Rocha et al., 1996)
Mass transfer coefficient,gas side (Rocha et al., 1996)
Specific wetted area (Rocha et al., 1996)
7
6
5
4
3
2
1
0
-50
-40
-30
-20
-10
0
10
20
30
40
50
%Deviation for hydraulic parameters
Fig. 9. Effect of errors in fluid dynamic parameters on H2S concentration in sweet gas using two different mass transfer correlations [38,39].
When looking at the errors of hydraulic parameters using the two
different mass transfer correlations presented in Fig. 8, sensitivity
toward the gas-side mass transfer coefficient is obviously higher
than that of the liquid-side mass transfer coefficient. Choosing the
suitable correlations for the calculation of the gas-side mass
transfer coefficient and specific wetted area are very important in
attaining the accurate and reliable prediction for the gas H2S
concentration in the sweet gas.
Conclusion
In this study, a rate-based model for the simultaneous reactive
absorption of acid gases (H2S and CO2) into an aqueous solution of
MDEA in a packed column was proposed. A number of experiments
were performed in two different packed bed absorption columns
with random and structured packing to validate the presented
model. In different conditions, the sensitivity analysis of the model
was carried out. In sensitivity analysis, two different mass transfer
correlations were examined. The model was most sensitive toward
the gas-side mass transfer coefficient and specific wetted area for
the absorber containing Mellapak 250. Also, the effect of the
important process parameters on the absorber model was studied.
The results of parametric study of the absorber model revealed that
the concentration of acid gases in the sweet gas stream increases
with the decrease in the specific surface area of packing, and the
overall mass transfer coefficients increases with the increase in the
liquid flow rate along the packed column. The simulation results
for the effect of mole ratio of CO2/H2S on the H2S selectivity along
the packed column indicated that the selectivity peak decreased
with the increase in the ratio in gas feed along the packed column.
As the model is validated on the real industrial data, it can be
helpful in the industrial research, optimization, development,
scale-up and design of CO2 removal processes by MDEA solution.
Acknowledgment
The authors would like to thank the South Pars Gas Complex
(SPGC) for providing the data used in this research.
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