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Chemical Engineering Study Project 4

Abstract: The separation of CO2 from the flue gas of a 600 MWe Coal fired power station

was investigated with the aim of achieving 90% recovery of CO2 and a permeate purity of

90% CO2. The separation was to be performed using a dual stage membrane process. A range

of variables were investigated including membrane area, membrane configurations, sweep

flowrates and pressure ratios. The dual stage process was able to achieve up to 89.57%

recovery and 85.87% purity at a substantial energy cost. The dual stage process was deemed

to be able to achieve the targets but not within acceptable limits.

Paul Connaghan s0820010

Submission December 2011

University of Edinburgh, School of Engineering (and Electronics)

Chemical Engineering

Study Project 4 (U04634)

Membrane Separations for CO2 Capture: Dual

Stage Process simulations

Paul Connaghan

S0820010

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Table of Contents

1 Introduction ........................................................................................................................ 3

2 Literature Review ............................................................................................................... 4

2.1 Current Technologies .................................................................................................. 4

2.2 Theory of membrane separation units ......................................................................... 6

2.2.1 Membrane types ................................................................................................... 7

2.2.2 Models used ......................................................................................................... 8

2.2.3 Membrane parameters ........................................................................................ 11

2.3 Conclusion ................................................................................................................. 13

3 Modelling Process ............................................................................................................ 14

3.1 Aims .......................................................................................................................... 14

3.2 Simulator Modelling Strategy ................................................................................... 14

3.2.1 Manipulated Variables ....................................................................................... 14

3.2.2 Monitored Variables .......................................................................................... 16

3.2.3 Key Performance Parameters ............................................................................. 17

3.2.4 Simulator Interface............................................................................................. 18

3.3 Results ....................................................................................................................... 19

3.4 Critical Review .......................................................................................................... 27

3.5 Conclusion ................................................................................................................. 32

4 Appendices ....................................................................................................................... 33

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1 Introduction

A substantial amount of CO2 is produced through anthropogenic activities; In particular the

amount produced through power generation. Power generation is estimated to account for up

to 80% of worldwide greenhouse gas production[1]. Furthermore up to 25% of the energy

supply and 40% of the emissions produced are generated by coal fired power stations and the

rest largely through gas and oil [2]. With power demands increasing, especially within

developing countries which have a plentiful supply of coal: the emissions from coal fired

energy are set to increase by around 350% from 2000 to 2050 [3]. This represents an increase

from 40% to 55% of total global power emissions [4].

The effects of CO2 on the mechanisms of global warming has not been understood fully as of

yet but many climate models have shown that the continued increasing trends of CO2

atmospheric concentration will have a dramatic effect on the earth’s climate by 2100[5].

More and more governments and industries are looking for ways to reduce and limit their

CO2 emissions due to increasing numbers of directives and protocols. As a result of these

issues there is mounting pressure to find a way to sequester CO2 at an affordable rate. This

report looks into sequestration of coal fired emissions and how to achieve a satisfactory

degree of separation through membrane technologies.

There are a number of options available for capturing the CO2 produced by coal fired power

plants. The three main options as outlined by DOE [6] and the IEA [7] are:

1- Post-combustion – CO2 capture from the flue gas produced

2- Pre-combustion – CO2 capture from gasified coal synthesis gas

3- Oxy-combustion – Fuel is burnt with almost pure oxygen to produce a high purity

CO2 effluent

Both pre-combustion and oxy-combustion can capture 90% of CO2 produced with a high

purity [8] but are unable to sequester the CO2 produced by a direct fired coal power plant

without further modifications [9]: pre-combustion requires gasified coal syngas to be

prepared; oxy-combustion requires special equipment for N2 separation[10]; both require a

turbine system for combustion. The vast majority of coal fired power plants are directly fired

air combustion coal burning and this type will be continued to be constructed for the

foreseeable future. With this in mind researching possible sequestration techniques for these

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standard air fired combustion systems is an important area if we are to try to reduce our CO2

emissions.

A number of techniques are available for post combustion CO2 sequestration which must

deal with two main considerations:

1- Large flowrates of flue gas [4, 11]

2- The low partial pressures of CO2 in the flue gas

The main sequestration method that is promising is the use of amine absorption. This is a

proven technology which has been used for many years for industrial applications; however,

when used for power plant sequestrations it will be costly and energy intensive. Use of this

technology could result in a rise in cost of energy anywhere between 50-90% which is

undesirable[4].

Membranes are a developing area with respect to CO2 separations. They are a promising

candidate for this process due to a number of advantages: the ability to deal with large flows;

lack of moving parts means lower maintenance costs; a very small footprint. There is much

doubt as to whether membranes can be used to achieve the separation realistically. Although

they have many advantages, the use of a single membrane unit is insufficient for achieving

the necessary separation and we must look to dual stage processes for the feasibility of

achieving DOE targets [12]. There are a number of key factors that can affect a dual stage

process and all of these must be investigated if the process is to be competitive.

2 Literature Review

2.1 Current Technologies

There is a lot of effort being put into developing gas separation techniques as these are used

in so many different industries and processes. Furthermore to this, a lot of effort is being put

towards developing techniques for the separation of CO2 due to increasing pressure on

industries and the apparent criticality of the CO2 emissions.

As mentioned before the increasing pressure on reducing CO2 emissions to the atmosphere

has bolstered the research performed in the area of CO2 separation. The three main options

for reducing CO2 emissions as produced through power generation are as follows[8]:

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- Reduction of energy intensity

- Reduction of carbon intensity

- Enhancing CO2 sequestration

As power generation from fossil fuels is a mature technology there is little in the way of

substantial improvements that can be made in the efficiency of existing power stations and

therefore we must look to points two and three for improvements[8]. Reduction in carbon

intensity is not feasible for fossil fuel schemes; however, improvements could be made

through partial or complete use of renewable sources such as biofuels or wind energy. Again

this has little potential when looking into existing power stations as it would require costly

modifications to existing plants[9]. In order to have a sizeable impact on current CO2

emissions, sequestration needs to be investigated.

There are a number of technologies currently being researched for post combustion CO2

sequestration. The most mature is chemical absorption and the most extensively studied

within chemical absorption is monoethanolamine (MEA) absorption[8], which has been used

for many years in industries for a range of separations including CO2 recovery and natural

gas sweetening [9]. Amine absorption has been a prime candidate for CO2 sequestration for

some time. Some of the advantages associated are that it is a well developed technology

which is highly selective and can produce high purity CO2. However, it carries numerous

disadvantages such as large energy penalties, large plant footprint, degradation of material

and equipment and a low CO2 loading capacity [8]. The energy penalty and running costs

incurred through amine absorption is severe and questions the overall feasibility of the

process.

Membranes themselves are a somewhat mature area of technology with 20 years of

commercial experience and 50 years of development [13]. Loeb and Sourirajan first created

high flux anisotropic membranes with large surface area capabilities in 1960 which attracted

considerable interest due to applications to reverse osmosis[13]. Permea adapted the Loeb

Sourirajan membrane to produce the world’s first commercially available membrane, Prism,

in 1980. This was successfully applied to H2 recovery processes and showed the potential of

membranes for performing low cost separations. There has been substantial research into

membranes over the past 10-15 years as the market share has grown rapidly to an estimated

£2-3 billion per year[14]. The majority of the research has been focused on advancing the

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permeability and selectivity of membranes; two key properties for any separation.

Advancement on this front has been limited with the exception of some membranes which are

in early stages [15], and will most likely not be ready for commercialisation for some time.

Some success has come from development of hybrid membranes which can combine optimal

features from two or more membranes with impressive properties. It has been suggested that

for significant improvement a deeper understanding of the transport on a molecular level

should be sought after[16], which suggests that our current understanding and models of the

transport within membranes is insufficient.

As mentioned before, membranes are already in widespread use in industry; one of the

greatest benefits from membranes is the process intensification scale that can be achieved due

to their small footprint and efficiency. The use of membranes in water desalination can yield

a process 10 times more energetically efficient than thermal options [16] and Baker [17]

states that 5000-10000 N2 separation units are in operation worldwide and account for 1/3 of

N2 production.

The application of membranes in the sequestration of CO2 is a relatively undeveloped area

compared to industrial applications. Much research has been done to try and ascertain the

feasibility and optimum processes for it but little has been done in the way of larger scale

investigations. A pilot plant was constructed in 2008 in Arizona, Cholla, to test a membrane

separation process on the flue gas stream of a 995MW power plant [18]. The project is

looking to investigate a 6 month operational period with emphasis on the cost efficient

fabrication of a membrane skid and assessing the performance of the membrane. A map of

cost reductions for feasibility will also be generated. The initial results are promising with

respect to contaminants such as SOx within the process but the overall results are limited as of

yet. Another pilot plant has been constructed and reported on in Australia but there is limited

data as to the success of it [19]: CHEMECA [20] stated that it was producing purities in the

range of 20-50% but with no specifications on the recovery achieved, it can be assumed that

the process is achieving 90% recovery.

2.2 Theory of membrane separation units

Membranes have been used for many years to perform separations on a variety of fluids

[21].As discussed in section 2.1 some processes are well defined and have been optimised

over many years and some are emerging technologies which require much research. There is

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a substantial amount of theory surrounding membrane separation which must be understood

if any process is to be correctly modelled.

2.2.1 Membrane types

The basis for all membrane separations is that there are two process streams divided by a

permeable wall, or membrane. The structure of the membrane can vary greatly depending on

what material it is constructed from but the membrane types largely fall into two categories:

porous and dense.

Porous membranes are those which have many pores permeating through the membrane,

these are analogous to a conventional sieve or filter; it is by these pores that the membrane is

able to separate different gases. Figure 1a shows a porous membrane; the separation takes

place chiefly by physical size separation where smaller molecules will be able to pass through

the pores and larger ones will be unable to fit through, the driving force is primarily the

pressure gradient and molecular motion of the gaseous species. Due to the pore sizes used (20

- 1000+ Å [13]) these membranes are used for separation of large molecules such as colloidal

mixtures or bio molecules such as proteins[22].

Figure 1 [13] - (a) porous membrane (b) dense membrane

Dense or polymeric membranes consist of a dense polymeric material which separates

gaseous molecules by allowing certain species to preferentially adsorb and diffuse through

the membrane; this can be seen in figure 1b. The separation will therefore not only work on

the basis of size but will favour different molecules; this is advantageous when separating

molecules of similar size such as in flue gases. The driving force for dense separations relies

on the chemical potential gradient of the species in question. Dense membranes will be

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focussed on in this paper as these are the most promising membranes for a commercially

viable gas separation process[21].

2.2.2 Models used

There have been a number of models used to describe the diffusion of species through

membranes. The modelling process carried out in this simulator must be understood if an

investigation is to be successfully carried out. The relationships used to model the process are

laid out in this section.

The models used to describe porous membrane transport are problematic; as of yet no unified

theory has been accepted for widespread use[13]. This is largely due to the heterogeneous

nature of porous membranes, as seen in figure 1a. Another difficulty is the lack of a

satisfactory set of parameters that can be used to correctly characterise porous membranes.

As discussed in 2.2.1 porous membranes are unable to separate gaseous mixtures due to the

limiting size of the pores and as such will not be discussed any further.

The model used to describe transport through polymeric membranes is known as the solution-

diffusion model. This has been developed through a series of improvements over a period of

20 years from 1960-1980 [13]. The transport of gaseous species through a polymeric film can

be seen to happen in 3 main steps:

1- The molecule is absorbed into the membrane feed surface and dissolved into the

polymer

2- The molecule diffuses through the polymeric membrane

3- The molecule is desorbed from the permeate side of the membrane

The absorption and desorption of the molecule is relatively simple to model and can be

represented by the conditions (Temperature, Pressure and Concentration) of the membrane

feed and a characteristic known as the sorption coefficient. This will be covered in more

detail later.

The diffusion of a gaseous molecule through a polymeric membrane entails the molecule

moving through the empty spaces created by the thermal movement of polymer chains,

known as the free volume [13]. The relations used to describe the diffusion through a

membrane start with the proposition that the driving force for the gaseous species is

dependent on the chemical potential. The use of chemical potential effectively links the

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temperature, pressure, concentration and electrical potential together as can be seen in

equation 2 and 3.

By using the observation that the movement of a species from a high to low concentration is

governed by Ficks law we obtain equation 1[13] to describe species flux across the system:

(1)

Where Ji is the flux of component i, Li is the coefficient of proportionality and µi is the

chemical potential of component i in the membrane, R is the molar gas constant, T the

temperature and ni the number of moles of component i.

It can be seen that an expression describing the component concentration gradient within the

membrane is required to model the flux of species i. This is acquired using the chemical

potential of the species throughout the membrane. The chemical potential of the species is

equated at the membrane feed interface: the feed gas phase is taken as a compressible fluid;

the membrane phase as an incompressible medium. The chemical potential of each phase can

be seen in equations 2 and 3 [13]:

– Incompressible medium - (2)

– Compressible fluid - (3)

Here, γi represents the activity coefficient of component, vi the molar volume and p the

pressure. A superscript o indicates a reference value and a subscripted o indicates the feed

interface with subscripted m indicating the membrane phase. Equations 2 and 3 can be

rearranged to provide an expression for the concentration of the species in the membrane as

shown in equation 4 which is simplified due to the exponential term being very close to one:

(4)

By calculating the concentration of component i from equation 4 and combining the terms for

the feed-membrane and membrane-permeate interfaces and then combining this with

equation 1 we can arrive at equation 6 which fully describes the flux across the membrane. A

sorption coefficient has been defined as in equation 5:

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(5)

(6)

Here, ρm denotes the molar density of component i and Di the diffusion coefficient. l is the

thickness of the membrane. The subscripted l indicates the permeate side of the membrane. In

equation 6, KiGDi are combined to give the permeability coefficient of the gaseous species.

Similarly, an expression can be derived describing the permeate-membrane interface. In

order to model the flux across the membrane system a mass balance is used; a mass balance

is constructed over both interfaces of the membrane. The mass balance for the feed side can

be seen in equation 7, the mass balance for the permeate side has a positive flux as

components are flowing into it. The system is treated as a 1D plug flow scenario; other

assumptions taken are that the system is isothermal, isobaric, the gases behave ideally and

that there is constant permeability.

(7)

In equation 7, the permeability coefficient and the thickness are combined in order to give the

overall permeance of the membrane with respect to species i, π; the permeance is analogous

to the permeability of a membrane. Furthermore, to allow consideration of other components

the permeance of component i is taken as the key permeance and a dimensionless ratio

known as the selectivity is defined, α. This relates the permeance of each component relative

to component i. A more thorough explanation of the modelling of membrane processes can

be seen in [23].

The simulator uses the backwards finite difference method to solve the mass balance over the

interval. This method uses two calculated points and a solution interval to solve to varying

levels of accuracy. By calculating F at each point and taking the difference between these

points the method can approximate the gradient of the function (in this case dF/dA). This is

solved iteratively until the values are in close agreement. One step of the method can be seen

in equation (8):

(8)

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Where h is the step size and relates to the interval between j and j-1. The smaller the step size

the greater the accuracy that is achieved.

2.2.3 Membrane parameters

It is obvious the flux of any species will depend heavily on many factors. Significant research

has been done into the effect these parameters have on membrane separations. This section

looks at reported trends and the reasons for any relationships present.

Membrane - Arguably the most important feature of any membrane process is what

membrane and therefore what selectivity and permeance is being used. If a process is to meet

the targets set by the DOE then the optimal values for permeability and selectivity will need

to be chosen. It has been shown that an increase in permeance will give an increase in

recovery [4, 12]. This can be explained through equation 7 which shows the permeance being

directly linked to the flux and therefore the recovery of CO2. Merkel also shows that an

increase in permeance of 400% will lead to a lower capture cost by approximately 50% [4]. It

can be seen that increasing the permeance will slightly lower the purity of the captured CO2

but to an almost negligible degree; conversely by altering the selectivity we can change the

purity but with negligible effect on the recovery [12]. As discussed in 2.1 these values are set

by the membrane used and are therefore relatively rigid with respect to membrane processes.

Membrane Area - The area of the membrane used has been mainly used as a benchmark for

the success of a process. This largely holds true for processes as the capital cost of

membranes is prohibitive; the polaris membrane can cost upwards of $50/m2 [4], this can be

very expensive when membrane areas reach into millions of m2. A well reported trend is that

with an increase in area the recovery of the process will increase and the purity of the

permeate will decrease [4, 12].

Membrane Configuration - One parameter with countless different options is the

configuration of the membrane units along with the use of either compression or vacuum to

drive the flow. Zhaos paper looks into the use of different configurations of compressors and

vacuums used to achieve 70% recovery [24]. The variation of configuration leads to large

differences between the energy and the area required for the (Area varying from 19m2 to

404m2, energy use varying from 113kWh/te to 312kWh/te): the key result being that there is

a trade off between area and energy use. Using a vacuum pump is attractive as although

vacuums are usually more energy intensive to produce the equipment will have to deal with a

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lower flowrate as it is being place on the permeate stream which should lead to lower energy

consumption, however [14] shows that with vacuum suction a larger area will be required

leading to another trade off between favourable values.

A key area with less research done is the actual configurations and how they can be varied

with respect to recycle streams and what effect this has on the efficiency of separation [25].

This is to be looked into in depth in this report and the results analysed.[12] shows that with a

single membrane we cannot expect to achieve both high recovery and high permeate purity

within an acceptable cost. This well researched finding has meant that more and more

research is being done into dual and triple stage separations. With this a much higher

separation can be achieved but with the key result of more energy being used as compressors

and vacuums are needed for each stage.

Sweep Configuration - The use of a sweep stream and the recycling of streams has had some

investigation but the effect of differing compositions of sweep stream on the separation has

not been fully researched yet. The typical sweep stream used is a set amount of the retentate

stream. The flowrate of the sweep stream can also have an effect on the separation as this will

directly affect the PPDF of the species and therefore warrants investigation.

Temperature - The temperature and pressure of operation are also extremely important

parameters as they can have significant effects on the results of the separation. The

temperature can be seen to have a direct affect on the flux achieved through equation 7; this

is closely linked to the idea of thermal motion and the fact that a higher temperature will lead

to larger molecular motions. The actual operating temperature is fairly limited by the

membrane being used; most membranes are not able to withstand elevated temperatures and

could experience adverse performance if used out with close to ambient temperatures. Due to

this, there has been very little work done on the effect of temperature on the separation

achieved and it is unlikely that there is much to be done in this area. The development of

new, more robust, membranes able to withstand higher temperatures whilst still possessing

desirable permeance and selectivity would warrant further investigation into this area;

inorganic membranes have been tested at temperatures as high as 600°C while polymeric

membranes area usually limited to around 200°C [13, 16].

Pressure - The pressure operated at is a major factor for separations as this not only has a

direct effect on the separation achieved but heavily influences the power consumed. Much

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work has been done into operation at different pressure ratios[4, 12]. The pressure ratio can

be seen to limit the concentration enrichment attainable through equations 9 and 10[4]. These

show that the concentration enrichment cannot exceed the pressure ratio between the feed and

permeate. Merkel has shown that with an increase in pressure ratio the energy required to

achieve 90% recovery increases but the area also decreases [4]; the optimum ratios were

identified at values between 5 – 10.

(9)

(10)

2.3 Conclusion

As shown in this section, there has been a lot of work done in the area of CO2 sequestration

with many different technologies being investigated. This creates a very competitive

environment for achieving satisfactory separations. The options of pre and oxy combustion

are becoming more attractive with respect to building a new power plant but the end of pipe

techniques for post combustion should not be overlooked.

The theory behind membrane transport has been heavily researched over 50 years and can

describe membrane processes well but little knowledge is possessed of detailed molecular

movements during separations. With the introduction of supercomputers this is being

developed and may yet yield results which are able to be applied to new membranes.

Membranes have been developed commercially over the past 30 years for separations of

many kinds with some becoming industry preferred choices. The separation of CO2, however,

is relatively undeveloped and although much work has been done in the area, still requires

progress if it is to compete with the alternatives.

The successful trial of pilot plants will demonstrate the actual effectiveness of membranes for

separation of flue gases and will be key to determining whether further research could yield

results. From the work done so far on membrane separations of CO2 from flue gases it seems

unlikely that the targets required by the DOE will be able to be met by membranes within the

near future; a significant breakthrough is required if membranes are to become competitive

with other technologies.

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3 Modelling Process

3.1 Aims

The aim of this process was to model dual stage membrane separation simulations using the

Unisim design R400 package. The separation was to be performed on the flue gas stream of a

600 MWe plant as specified by the DOE report [11]. The feasibility of achieving 90%

recovery and 90% permeate purity of CO2 using two membrane units was investigated. The

parameters investigated ranged from membrane configuration to pressure ratio and can be

seen summarised in section 3.2.3. A number of key aspects of the process are to be monitored

including CO2 recovery, permeate purity and energy use.

3.2 Simulator Modelling Strategy

As shown in section 2.2.3 there are a number of key variables to be investigated in order to

find the optimum configuration of a dual stage membrane process. The method of

investigation of these variables is set out in this section.

As many papers have investigated obtaining high recovery (70/90%) and economic energy

use with little focus on the permeate purity this report will chiefly aim to achieve the DOE

targets of 90% recovery and 90% permeate purity and then look into the power consumed.

When using dual stage membrane processes it is important to note that one membrane will

typically be deemed the high recovery membrane and one the high purity membrane. The

high recovery membrane will be the membrane which has the retentate exiting the process;

this membrane requires high recovery because as much CO2 needs to be removed as possible

before discharging the retentate to the atmosphere. The high purity membrane is the

membrane which has the permeate stream going to sequestration: high purity is required here

if the DOE targets are to be met [11]. Examples of high purity and high recovery membranes

can be seen in figure 2c; the membrane with streams 1 and 2 entering it is the high recovery

membrane and the membrane with stream 5 entering is the high purity membrane.

3.2.1 Manipulated Variables

There are a number of variables that should be manipulated in order to ascertain their effect

on the success of the separation process and find the optimal setup for a dual stage process.

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Membrane Configurations - The first area to be investigated was the use of different

configurations for the membrane unit. As each unit has four streams associated with it this

gives rise to a large number of possible configurations that could be used. Not all of these

configurations will give useful or indeed meaningful benefits to the separation. A total of 5

configurations have been chosen for investigation as these have been specified as promising

arrangements in Agrawals paper [25]. These can be seen in figure 2:

Figure 2 [25]- Membrane configurations

Investigating these configurations will allow the optimal arrangement to be determined with

respect to the key performance parameters. Each configuration will have the sweep fraction,

flowrate, membrane parameters and pressure ratio held constant and the areas varied until

90% recovery has been achieved. This should allow an effective comparison of the ability of

each configuration to achieve the separation. For the first membrane unit in figure 2c stream

1 is the feed, stream 2 the sweep, stream 3 the retentate and stream 4 the permeate.

Membrane Area – As discussed in section 2.2.3 the area of the membrane used in the

separation has a direct effect on the separation achieved. Membranes can generally achieve a

high recovery through utilising a large area which is able to recover most of the CO2 passing

over the membrane; a consequence of equation 7. The area of each membrane in the

configuration will be altered from the lowest possible (some membrane areas are unstable

and cannot be solved with this simulator, this is discussed further in section 3.4) to a

sufficiently high value. The effect this has on both the recovery and permeate purity will be

determined for both high purity and high recovery membranes.

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Sweep Flowrate Fraction – The sweep flowrate fraction is an important variable. The

fraction is as defined in equation (11) and directly affects the process. The sweep flowrate

fraction is the molar flowrate percentage based on the feed.

(11)

Where n dot represents the molar flowrate of the stream. The effect on the process is derived

from the PPDF governing the transport. By either changing the flowrate of the sweep gas or

its composition we can directly affect the overall PPDF and therefore the flux through the

membrane. By using a high sweep flowrate fraction (typically 10-20%) the recovery of a

membrane can be increased. A lower sweep fraction is utilised in high purity membranes:

typically 0-100 mol/s or less than 1% is used. These will be varied from 0-2% for the high

purity membrane and 0-20% for the high recovery membrane.

Pressure ratios – The use of pressure ratios is an important aspect of membrane separations

as this can greatly affect the requirements of the process. A larger pressure ratio will mean

that a lower area is required for the same recovery. This is a direct result of the pressure ratio

issue discussed in 2.2.3, equation 10. Using a larger pressure ratio will lead to increased

running costs as the energy consumed by the compressors accounts for the majority of the

overall energy use. The pressure ratio will be varied from 5 to 10 (corresponding to a change

in inlet pressure from 110 kPa to 220 kPa where the outlet is kept constant at 22 kPa), this has

been deemed as the suitable limit for pressure ratios with respect to power consumption[4].

Membrane Selectivity and Permeance – The selectivity and Permeance of membranes are

determined by which membrane is being used and as such the actual values feasible in reality

are limited. The values used for the majority of the report are those of the Polaris Membrane

which has a CO2/N2 selectivity of 50 and a CO2 permeance of 1000 GPU [4]. A theoretical

membrane is also investigated which has a selectivity of 100 and a permeance of 12000 GPU,

this has been named PIM + + and utilises the permeance of a membrane known as PIM [15]

and the selectivity which has been deemed the optimal limit attainable.

3.2.2 Monitored Variables

In order to successfully analyse this simulation a number of variables need to be monitored

and analysed to provide key performance parameters as discussed in section 3.2.

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The first and foremost variable to be monitored is the flowrates into and out of the

membranes. The molar flowrate of each component should be recorded for the feed stream,

sweep stream, permeate stream and retentate stream. By monitoring all of these flowrates we

can determine the necessary key performance indicators.

The simulator used had a built in spreadsheet function that allowed all molar flowrates to be

measured and dynamically displayed. This ensured all variables could be recorded and key

performance indicators calculated efficiently and swiftly.

The power consumption of all units was monitored. All compressors were taken as a positive

power consumption owing to the energy required to raise the pressure of components. The

power consumption of turbo expanders was taken as negative owing to the energy released

when a gases pressure is reduced.

3.2.3 Key Performance Parameters

Certain key performance parameters were to be calculated in order to ascertain the success

and feasibility of the separation achieved. The key performance indicators for this process are

defined as the recovery, the permeate purity, the retentate purity and the overall energy use.

The recovery is defined how much of the CO2 entering the process is recovered in the

outgoing permeate stream (stream 7 in figure 2c). The recovery was calculated as in equation

(12):

(12)

The permeate and retentate purities were taken as the mole fractions of the corresponding

streams with respect to CO2 (streams 3 and 7 respectively in figure 2c). This could be easily

calculated using unisims spreadsheet function and equation (13):

(13)

The overall power consumption of the process was determined simply by measuring the

power consumption of individual compressors and expanders and combining them as laid out

in 3.2.2 and equation (14):

(14)

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Another useful indicator for comparison between processes is the energy required to capture

one mole of CO2, or the specific power consumption. This is easily worked out from the data

gathered and is defined as in equation 15:

(15)

Table 1 - Summary of Variables

Manipulated Variables Monitored Variables Key Performance indicators

Membrane area

Membrane Configurations

As seen in figure 2

Sweep Flowrate Fraction

Permeate and Feed side pressures

Membrane Selectivity and Permeance

Molar Flowrates

Feed Stream

Sweep Stream

Permeate Stream

Retentate Stream

Power Consumption

CO2 Recovery

Permeate purity (CO2 content)

Retentate purity (CO2 content)

Overall power consumption

Specific Power consumption

3.2.4 Simulator Interface

The simulator used was an addition to the design program, Unisim Design R400. It was

developed by the University of Edinburgh to model membrane separations with a focus on

CO2 from flue gas streams.

The interface consisted of 4 panels. The first panel allowed the user to connect feed,

permeate, retentate and sweep streams to the unit operation. The second panel allowed the

user to enter the parameters of the membrane: area, key permeance, selectivity of each

component. The third panel allowed the user to set the number of grid points used int he

solving mechanism. The fourth panel was the standard Unisim worksheet panel and allowed

the user to monitor all streams entering and leaving the membrane. The interface of the

membrane unit was well integrated into the Unisim environment and was able to be

understood quickly with a basic knowledge of Unisim. The interface panels can be seen in

appendix IIIa.

As mentioned in 3.2.2 the spreadsheet function was used to aid data gathering. The

spreadsheet layout can be seen in appendix IIIb. All relevant details are easily observed and

key performance parameters are calculated automatically.

Page | 19

3.3 Results

Initially all 5 configurations were investigated to try and ascertain which was the most

efficient at achieving 90% recovery of CO2. The permeate purity was to be investigated

afterwards. The results of attaining 90% recovery can be seen summarised in table 2:

Table 2 - Configuration Investigation

Configuration Area 1 Area 2 Total

Area

Recovery Permeate

purity

Retentate

Purity

Power

consumption

Specific Power

consumption

x105m

2 x10

5m

2 x10

5m

2 % % % x100MW kJ/mol CO2

1 50 6.1 56.1 83.53 51.95 .5/8.39 .9714 39.62

2 22 4.2 26.2 90.76 33.57/9.236 1.75 0.62 20.41

3 43 2.75 45.75 90.12 63.76 1.128 1.335 50.45

4 5.5 42 47.5 90.17 63.28 1.142 1.264 47.76

5 2.7 43 45.7 90.09 63.69 1.221 1.295 48.9

It should be noted that the pressure ratio for each configuration was kept at 5 (inlet pressure

of 110 kPa; outlet pressure of 22 kPa) unless stated otherwise.

It can be seen from table 2 that configurations 3,4 and 5 are all promising configurations as

they are able to achieve 90% recovery with a substantial permeate purity. Configuration 1 is

by far the weakest. This required the largest area of all configurations, was unable to achieve

90% recovery (partially due to simulator stability issues discussed later) and gave a retentate

stream with too high a CO2 content. Configuration 2 was promising with respect to achieving

90% recovery at a low energy cost and membrane area but was unable to produce a

satisfactory permeate purity. Configurations 1 and 2 are unable to achieve satisfactory

retentate or permeate streams due to the well known issue mentioned in Zhao [12] stating that

1 membrane unit is unable to provide both recovery and purity, showing that both a high

recovery and high purity membrane area required. Configuration 1 can achieve a low

retentate purity at first but is unable to recover much in the second membrane if purity is also

desired here. Configuration 2 can recover a large amount in both but again but will not be

able to provide high purity at the same time.

Configurations 3, 4 and 5 are all comparable as the areas are similar and specific power

consumption is also similar. Configuration 4 would seem to be the most attractive at this

Page | 20

point due to the lower specific power consumption (~4% lower than 3 and 5) which would

most likely be the deciding factor due to the overall similarity in membrane areas. All

retentate purities are acceptable as they are below 2%. The permeate purities here appeared to

reach a practical limit approaching 65% and surpassing this value seemed problematic.

It should be noted that the pressure ratio issue discussed in equation 10 does not limit this

process. Although the input concentration of CO2 is 14.1% which would suggest a limit of

70.5% at a pressure ratio of 5, the use of two membrane units and a recycle loop changes this

as the feed to the high purity membrane will be significantly higher, around 40% in most

cases, which theoretically allows the process to surpass 90% purity.

From the results for achieving 90% recovery of CO2 with each configuration it can be seen

that configurations 1 and 2 are not able to fulfil the DOE goals adequately due to the

insufficient retentate or permeate purity issues as discussed above. From these results 3,4 and

5 are the most promising and these will be taken forward for further investigation. The next

stage was to investigate the effect of changing the area of the membrane. Initially the area

was varied and all relevant key performance indicators calculated. The results of varying the

area can be seen in figures 3 a,b and c; it should be noted that the numbers next to each point

correspond to the area of the membrane measured in 105m. All parameters were kept at the

values in table 2 unless being altered.

It should be noted that not all values recorded are included in this section and certain values

have been omitted for the sake of clarity. All recorded values can be seen in appendix IV

which is on a data CD. For more detailed information on the position of compressors and

expanders appendix IIIc should be examined, this is also on the data CD.

Page | 21

Figure 3 - (a)(b)(c) effect of changing membrane areas

The variables changed in figure 3 a,b and c were:

The area of the purity membrane

The area of the recovery membrane

52

57

62

67

72

82 84 86 88 90 92 94

Pe

rme

ate

pu

rity

(%

CO

2)

Recovery (%)

Figure 3 a - Configuration 3 area change

purity membrane area

recovery membrane area

56

58

60

62

64

66

68

82 84 86 88 90 92 94

Pe

rme

ate

Pu

rity

(%

CO

2)

Recovery (%)

Figure 3 b - Configuration 4 area change

purity membrane area

recovery membrane area

56

57

58

59

60

61

62

63

64

65

66

82 84 86 88 90 92 94

Pe

rme

ate

Pu

rity

(%

CO

2)

Recovery (%)

Figure 3 c - Configuration 5 area change

purity membrane area

recovery membrane area

Page | 22

All 3 configurations can be seen to obey similar relationships; with an increase in the purity

membrane area the recovery will increase but the permeate purity will decrease. This has

been widely reported as a standard trend and can be linked to equation 7 [4, 12]. By

increasing the area of the membrane, the flux of CO2 is increased leading to a higher

recovery. However, by increasing the membrane area, the flux of other molecules (in this

case H2O, N2 and O2) also increases, leading to a decrease in permeate purity as the CO2

concentration is diluted. The specific power consumption falls with an increase in the purity

membrane area, this is due to the increased flux across the membrane. This will not only lead

to more power recovered from the expander operating on the permeate stream but the larger

amount of gases removed from the process will mean that less compressing power is required

in other streams such as the recycle.

The configurations can also be seen to increase in recovery and permeate purity if the area of

the recovery membrane is increased. This is due to the fact that a larger area will allow a

larger CO2 flux as shown above, again leading to an increase in recovery. This sends more

CO2 to the high purity membrane and as the purity membrane area is constant causes the

recycle stream and therefore the feed stream to be richer in CO2. The increased CO2 content

passing over the high purity membrane causes an increase in CO2 purity in the permeate

stream. This trend would most likely have been different if configurations 1 and 2 had been

investigated. The lack of recycle would have caused the permeate purity to decrease slightly

as the feed would not have been as rich in CO2. The expected result here would have been for

the recovery to increase and the purity to decrease as has been shown in literature [4], this

highlights the importance of the recycle stream. An increase in the size of the recovery

membrane causes an increase in specific power consumption as the larger membrane flux

creates a much larger recycle stream which needs to be recompressed before entering another

membrane.

The trends do not behave ideally as a straight line would be expected. This can largely be

attributed to the simulation solver, equation 8 in particular, and is discussed further in 3.4

The next step was to investigate the effect that changing the flowrate of the sweep stream had

on the separation process. The investigation into the sweep stream can be seen summarised in

figure 4 a,b,c where the numbers on the graph correspond to the sweep flowrate fraction:

Page | 23

Figure 4 - (a)(b)(c) Effect of changing the sweep fraction

The variables changed in figure 4 a,b and c were:

The sweep flowrate fraction of the purity membrane

The sweep flowrate fraction of the recovery membrane

56

57

58

59

60

61

62

63

64

65

66

67

76 78 80 82 84 86 88 90 92

Pe

rme

ate

pu

rity

(%

CO

2)

Recovery (%)

Figure 4 a - Configuration 3 Sweep change

recovery membrane sweep fraction

purity membrane sweep fraction

56

58

60

62

64

66

68

75 77 79 81 83 85 87 89 91 93

Pe

rme

ate

pu

rity

(%

CO

2)

Recovery (%)

Figure 4 b - Configuration 4 Sweep change

recovery membrane sweep fraction

purity membrane sweep fraction

54

56

58

60

62

64

66

68

76 78 80 82 84 86 88 90 92

Pe

rme

ate

pu

rity

(%

CO

2)

Recovery (%)

Figure 4 c - Configuration 5 Sweep change

recovery membrane sweep fraction

purity membrane sweep fraction

Page | 24

Again all three configurations can be seen to obey similar relationships. When the sweep

flowrate fraction of the recovery membrane is increased, the recovery and permeate purity

can be seen to increase. This is due to the CO2 concentration being decreased in the permeate

side due to the increased air flowrate; this causes a larger PPDF and increases the CO2 flux

across the membrane leading to a higher recovery. The increased CO2 feed to the permeate

membrane causes a higher CO2 flux relative to other components leading to a higher

permeate purity. The increased CO2 content also passes on to the recycle leading to a higher

feed content of CO2, these two effects act together to increase both the recovery and purity.

The specific energy consumption of process rises with an increase in recovery membrane

flowrate as this allows more gas into the system to be recompressed for the second membrane

and also leads to a larger recycle stream.

An increase in the sweep flowrate fraction of the purity membrane can be seen to cause a

slight increase in recovery and a decrease in purity. The dilution of the CO2 concentration due

to the increased air flowrate leads to a lower permeate purity and this causes a larger PPDF

which allows a larger CO2 flux which causes the increase in recovery. This is compounded by

the lower CO2 content in the recycle further leading to a decrease in permeate purity. The

specific power consumption for an increase in purity membrane sweep flowrate fraction

decreases as the larger flow exiting in the permeate stream allows more energy to be

recovered from the turbo expander downstream.

An interesting result in changing the recovery sweep fraction is that the recovery can be seen

to decrease after a certain value (may not be completely clear here due to accuracy issues).

This is most likely due to the fact that increasing the sweep flowrate will eventually lead to

the PPDF being decreased due to the CO2 content in the air sweep stream. The trends

observed here are largely the same when repeated at a pressure ratio of 10, however the point

at which a configuration reaches a maximum with respect to recovery can be seen to change

significantly (at a pressure ratio of 10 the maximum was 6.7% as compared to a maximum at

13% for a pressure ratio of 5).

Configuration 4 would appear to be different in that the recovery does not tail off as it does

with configurations 3 and 5. Configurations 3 and 5 can be seen to reach a limit of recovery

at different sweep flowrate fractions (13% for configuration 3 and 17.7% for configuration 5)

and therefore it can be assumed that the range of investigation was not large enough to allow

the maximum to be reached for configuration 4.

Page | 25

The key result from these investigations is the knock-on effect of the recycle and the fact that

this can change reported trends.

The next step was to investigate the effect that changing the pressure ratio had on the

processes, this can be seen summarised in table 3:

Table 3 - Pressure ratio investigation

Config. area 1

area

2

Total

Area

Recover

y

Permeate

mol frac

Retentate

mol frac.

energy

use

pressure

in

pressure

out

press

ure

ratio

x105m2 x105m

2 x105m

2 % %CO2 %CO2 x100MW kPa kPA

3 43 2.75 45.75 90.02 63.76 1.128 1.335 110 22 5

3 13.5 1 14.5 90.22 76.6 1.198 1.995 220 22 10

4 5.5 42 47.5 90.7 63.39 1.147 1.268 110 22 5

4 1.25 16.5 17.75 89.99 78.15 1.146 2.595 220 22 10

5 2.7 43 45.7 90.09 63.69 1.221 1.295 110 22 5

5 1 15 16 90.82 75.55 0.8409 2 220 22 10

The area required for each configuration to achieve 90% can be seen to drop drastically; by

around 65% for each configuration, this represents substantial capital cost savings in a

membrane process. This is due to equation 7 and the PPDF increasing meaning that a smaller

area is required to provide the same CO2 flux relating to 90% recovery. The downside to

increasing the pressure ratio is the substantial increase in energy use due to the additional

compression; an increase of 49%, 104% and 54% for configurations 3, 4 and 5 respectively.

The permeate purity is increased which is most likely a result of the pressure ratio discussed

in equation 10. By doubling the pressure ratio the concentration enrichment possible is

effectively doubled as well which leads to a higher permeate purity. The retentate can be seen

to remain relatively constant. A decrease in retentate purity is seen in configuration 5 and can

be explained due to the increased recovery leaving a lower CO2 flow in the retentate.

The effect of changing the sweep stream from an air stream to the recycled retentate stream

was then investigated. This is effectively splitting stream 6 in figure 2c and recycling this to

streams 2 and 8 to be used as the sweep. The results can be seen summarised in table 4:

Page | 26

Table 4 - Sweep composition investigation

Setup area 1 area 2 Total Area Recovery

Permeate

mol frac

Retentate

mol frac.

energy

use

pressure

ratio

x105m

2 x10

5m

2 x10

5m

2 % %CO2 %CO2 x100MW

C3 – air sweep 43 2.75 45.75 90.02 63.76 1.128 1.335 5

C3 – double ret.

sweep 40 3 43 90.16 62.41 1.419 1.263 5

C3 – double ret.

sweep 13 1.05 14.05 90.17 75.75 1.349 1.939 10

C4 – air sweep 5.5 42 47.5 90.7 63.39 1.147 1.268 5

C4 – double ret.

sweep 6 38 44 90.38 59.5 1.281 1.285 5

C4 – double ret.

sweep 1.15 18 19.15 90.7 79.35 1.162 2.967 10

C5 – air sweep 2.7 43 45.7 90.09 63.69 1.221 1.295 5

C5 – double ret.

sweep 2.85 41 43.85 90.02 62.48 1.447 1.247 5

The recycling of the retentate actually leads to an increase in the CO2 content of the sweep;

this seems counterintuitive as by changing the sweep to the retentate the PPDF is decreased

as the retentate has a higher CO2 content than the air being used. By recycling the otherwise

discarded retentate stream it allows the process to capture some more CO2 from the stream

and therefore increase the recovery (or allow a smaller area to provide the same recovery).

The decrease in purity is a result of the lower PPDF allowing less CO2 to permeate. A small

decrease in power is seen when the sweep stream is recycled, this can be attributed to the use

of an already pressurised retentate stream being put through an expander to recover some

energy. The air stream previously used was being expanded from 101.3 kPa to 22 kPa and the

retentate stream is being expanded from 110 kPa to 22 kPa therefore allowing more energy to

be recovered than before.

With the major parameters investigated it can be seen that achieving 90% recovery and 90%

permeate purity is unrealistic without consuming a significant amount of energy. As

mentioned above, a theoretical membrane known as PIM + + was tested. This membrane is a

hybrid between the PIM membrane[15] and a theoretical limit for membrane selectivity. PIM

+ + would have the selectivity of PIM and a selectivity of 100 which has been deemed as an

Page | 27

attainable limit for membranes. If this membrane can be produced commercially membrane

processes stand a much better chance at achieving DOE targets.

Table 5 - Testing of PIM + + membrane

Total Area Recovery

Permeate

mol frac

Retentate

mol frac.

energy

use

pressure

ratio

x105m2 % %CO2 %CO2 x100MW

config. 3 3.76 87.24 71.6 1.615 1.405 5

config 3. ret.

Recycle. PR 10 1.406 89.28 84.9 1.409 2.558 10

config. 4 3.7 83.9 72.67 2.12 1.358 5

config 4. ret.

Recycle. PR 10 1.56 83.89 79.24 2.77 4.146 10

config. 5 3.98 89.33 69.38 1.242 1.354 5

config 5. ret.

Recycle. PR 10 1.5525 89.87 85.87 1.14 2.739 10

From these results it can be seen that the increase in membrane parameters gives very

promising results. The configurations running at a pressure ratio of 5 give good results,

although still not achieving DOE targets. The configurations can come within 20% of the

targets at a power consumption of around 22% of the plants output. The increase in energy

consumption relative to the polaris membrane is due to the selectivity allowing less gas to

permeate and causing a larger recycle which has to be compressed. By running at a pressure

ratio of 10 the permeate purity can be increased significantly but at a great cost with respect

to energy consumption. Configuration 5 can almost achieve the DOE targets when used with

PIM + + and a pressure ratio of 10; at an energy use of 45.65% of the power plants output.

The area required decreases massively with PIM + + but will also be much more expensive

as this is not a physically constructed

3.4 Critical Review

This section looks into the simulation and assesses the viability of the modelling process and

how accurate the results may be.

Assumptions

There are a number of assumptions made in this modelling process which could have a

significant effect on the viability of the model produced. The membrane units are assumed to

be isobaric and isothermal. In reality there will be a slight pressure and temperature drop over

Page | 28

the membrane. The temperature drop is a largely safe assumption as with the proper design

any possible drop could be minimised and rendered negligible. The assumption that the

membrane is isobaric is justified as the membrane is a dense polymer and treating it as an

incompressible medium is valid; again, a slight drop may be witnessed in reality but would be

negligible with respect to effects on the process.

The assumption of constant permeability can have more of an effect on the viability of the

process compared to others. In reality the permeability of the membrane would change with

numerous factors: pressure, temperature, time, concentration. For the purposes of the

simulation this assumption is valid as including varying permeability would greatly

complicate the model. Much research has been done into the variance of permeability in areas

such as plasticisation or time dependence and if the simulation was to be carried out

experimentally this could be accounted for. The Cholla pilot plant has reported that the

membranes have been performing well with respect to contaminants which could degrade

performance over time, this would seem to reinforce this assumption.

The assumption of 1D plug flow allows the flux to be easily approximated. It is unlikely that

the flow would be close to 1D plug flow in reality as there would be flow in multiple

directions due to local pressure gradients that would most likely be present. The flux of the

multidirectional flows can be assumed to be at least an order of magnitude smaller than the

assumed flow direction. Also, as all CO2 is entering one plane and leaving the other parallel

plane the overall flow can easily be modelled as 1D plug flow with respect to overall flow

direction.

Lastly, the permeate side flow was assumed to have perfect mixing. This allows the permeate

side concentration to be approximated and easily calculated. In reality the concentration at the

permeate interface would be significantly higher which would act to decrease the PPDF and

lower the flux. Using a sweep flow will add to the mixing on the permeate side but a

concentration gradient would still be present. The extent that this assumption has on the

process cannot be properly determined and would warrant further investigation before

designing any potential membrane processes.

Modelling process

The modelling process aimed to be carried out in the most efficient way which would allow

all necessary variables to be calculated. By looking into the requirements of each

Page | 29

configuration initially, the optimum configurations were able to be ascertained and these

brought forward for further investigation, reducing the time required for simulations.

The parameters investigated in this report seem to be sufficient to give a good understanding

of the possibilities for a membrane separation process. Some additional areas of investigation

which would have been advantageous but were unable to be carried out due to time

constraints are:

- More than two pressure ratios could be investigated to determine any possible

trending effects

- More than two membranes could be investigated so that a deeper understanding of the

membrane parameters could be gained

- The investigations could be carried out with 80 grid points to provide greater accuracy

and more distinct trends

- Carrying out an investigation into power consumption without any sweep streams

may allow a better understanding of how parameters affect this

- An investigation into altering the sweep fraction with a recycled sweep stream could

yield interesting results but would be time consuming due to the use of two recycle

loops

- Investigation into the energy recoverable from heat sources such as compressed gases

could yield considerable savings

Carrying out these additional points would be very time consuming and as such only the main

areas have been investigated this paper.

As the energy consumption is such a key parameter in this process it would be advisable to

carry out further investigation into this to determine the actual accuracy of the values

observed. Unisim takes into account factors that would affect the power consumption of

compressors and vacuums such as adiabatic and isentropic efficiencies and idealities. The

power consumption in reality would likely be different to those calculated but cannot

accurately be judged whether they would be higher or lower.

The key performance indicators used are mostly adequate for analysis of the overall

performance and only one additional performance indicator would be included if the

simulation was repeated, the process selectivity. The process selectivity relates the permeate

CO2/N2 ratio to that of the feed side and is used as a variable in [12].

Page | 30

Notes on the simulator

The simulator was able to model the majority of the process with ease and performed well.

The biggest issue would be the fact that the simulator experienced some stability issues with

solving around certain values.

This was first noticed when loading a previous simulation; the simulator was unable to solve

if the area of each membrane was increased straight to the expected value initially. When

trying to solve, the simulator experienced negative flowrates in some streams and would

eventually reach an inconsistency which prevented it from being solved. Instead the area of

each membrane had to be gradually increased until the required value was reached; this added

some time to the simulations but was not overly time consuming. This was also experienced

with the sweep flowrates. A useful method was to take note of the last values run in the

simulation before the file was saved, if these were put into the simulation it would be able to

run at the required values straight away and would save time.

This stability issue was also observed when altering variables such as the flowrate and area. If

a large change was made to the variable (eg. sweep flowrate of 3000 mol/s to 100 mol/s) the

simulator would be unable to solve. Instead the values should be changed gradually (in steps

of 250-500 mol/s for example) and the simulator would be able to solve successfully.

The simulator solved to acceptable accuracy levels with respect to comparisons of runs and

observing trends; if the process was to be carried out in real life it is unlikely that any higher

accuracy would be desired or even needed. The accuracy is largely determined by the number

of grid points used which relate to equation 8. 50 grid points were used for the majority of

simulations as this gave an acceptable trade off between solving time and accuracy. For final

results of individual runs such as the comparison between all 5 configurations or the pressure

ratio investigation, 80 points were used in order to provide boosted accuracy allowing better

comparisons between results.

Even when 80 grid points were used some discrepancy was noticed when the same values

were simulated twice; the discrepancy was less than with 50 grid points (~0.2% as opposed to

~0.8%). The simulation also seemed relatively sensitive to starting values. When changing

variables the results would often be the same if the values were changed from 0 to the final

value in steps but would change if the values were changed from the final value to 0. This is

Page | 31

due to the fact that the simulator would have the flowrates and compositions from the last run

and would solve iteratively using these as a starting point, leading to small differences in final

values.

Process viability/Results

The main aim of this report was to determine the viability and effect of parameters on a dual

stage membrane separation process.

As discussed above, the results are relatively accurate and can be deemed accurate enough for

the purposes of comparing technologies and determining the viability of the process.

It can be seen from the results that a membrane process will be unable to attain a permeate

purity of 90% at a pressure ratio of 5 within acceptable conditions. Achieving 90% recovery

can be done relatively easy with a membrane area of around 4.5 million m2 and a power

consumption of around 20% of the plant output. With a pressure ratio of 5 the permeate

purity seems to reach a maximum at around 70% which is a high permeate purity but not high

enough to meet the DOE targets.

The investigations into the effect of the area and the sweep flowrate serve to highlight the

importance of the recycle stream. The recycle stream not only allows more CO2 to be

captured and therefore recovered but can have a knock-on effect which can further increase

the permeate purity, or, in some cases decrease the permeate purity.

Merkel states that to be competitive with current absorption the membrane process should use

less than 30% of the power plants output[4]. This shows that it is unlikely that a pressure ratio

of 5 will be able to be competitive with respects to overall purity at the same time as

achieving 90% recovery. Increasing the pressure ratio must be done with attention to the

power consumption as this increases the power consumption significantly.

The final investigations show that in order to approach the 90% recovery and 90% purity

mark we need increasingly difficult conditions such as high pressure ratios and experimental

membranes.

The results obtained seem to show that at the current level of technology it is possible, but not

feasible, to obtain 90% recovery and 90% permeate purity from a dual stage membrane

process.

Page | 32

3.5 Conclusion

The modelling process carried out here effectively shows the fact that there are a large

number of factors which have a significant effect on the success of a membrane separation

process.

This report successfully investigated some of these factors and much research has been done

on a multitude of other factors from different viewpoints. The sheer number of

configurations, variables and performance indicators that can be changed and measured is

prohibitively exhausting. This report has attempted to focus on the parameters largely

relevant to achieving the DOE targets.

The results obtained show that considerable levels of purity can be achieved at relatively low

costs but the reality of achieving DOE targets at the current level of technology and within an

acceptable cost are unlikely to be met. Achieving 90% recovery is relatively easy compared

to 90% purity and can be done within acceptable energy use but at a substantial membrane

area and therefore cost.

Overall, membranes are a promising CO2 separation technology which requires key

commercially available breakthroughs in order to compete with other developing

technologies. Membranes with selectivities in excess of 100 would be beneficial as it appears

that reaching 90% permeate purity is the limiting step for this process.

Page | 33

4 Appendices

I. References

1. IEA, Emissions from Fuel Combustion 1971-2004, 2006a, International Energy

Agency: Paris, France.

2. Quadrelli, R. and S. Peterson, The energy–climate challenge: Recent trends in CO2

emissions from fuel combustion. Energy Policy, 2007. 35(11): p. 5938-5952.

3. The Future of Coal – Options for a Carbon Constrained World. MIT Interdisci-

plinary Study, 2007.

4. Merkel, T.C., et al., Power plant post-combustion carbon dioxide capture: An

opportunity for membranes. Journal of Membrane Science, 2010. 359(1-2): p. 126-

139.

5. J.T. Houghton, Y.D., D.J. Griggs, M. Noguer, P.J. van der Linden, X. Dai, K. and

C.A.J. Maskell, Climate Change 2001: The Scientific Basis. Cambridge

University Press, 2001. New York.

6. J.D. Figueroa, T.F., S. Plasynski, H. McIlvried, R.D. Srivastava Advances in CO2

capture technology – the U.S. Department of Energy’s Carbon Sequestration

Program. International Journal of Greenhouse Gas Control 2008. 2: p. 9–20.

7. Adams, D., Davison, J., Capturing CO2, IEA Greenhouse Gas R&D Programme

Report. 2007.

8. Yang, H., et al., Progress in carbon dioxide separation and capture: A review.

Journal of Environmental Sciences, 2008. 20(1): p. 14-27.

9. Wang, M., et al., Post-combustion CO2 capture with chemical absorption: A state-of-

the-art review. Chemical Engineering Research and Design, 2011. 89(9): p. 1609-

1624.

10. Scheffknecht, G., et al., Oxy-fuel coal combustion—A review of the current state-of-

the-art. International Journal of Greenhouse Gas Control, 2011. 5: p. S16-S35.

11. Cost and Performance Baseline for Fossil Energy Plants. Volume 1: Bituminous

Coal and Natural Gas to Electricity, Aug 2007. DOE/NETL.

12. Zhao, L., et al., A parametric study of CO2/N2 gas separation membrane processes

for post-combustion capture. Journal of Membrane Science, 2008. 325(1): p. 284-294.

13. Baker, R.W., Membrane Technology And Applications. 2004, Wiley: Membrane

Technology and Research, Inc.

14. Haiqing Lin, T.M., Richard Baker, The Membrane Solution to Global Warming, in

Sixth Annual Conference on Carbon Capture & Sequestration2008, Membrane

Technology and Research, Inc: Pittsburgh, Pennsylvania.

15. Budd, P., et al., Gas permeation parameters and other physicochemical properties of

a polymer of intrinsic microporosity: Polybenzodioxane PIM-1. Journal of Membrane

Science, 2008. 325(2): p. 851-860.

Page | 34

16. P. Bernardo, E.D., G. Golemme, Membrane Gas Separation: A Review/State of the

Art. Industrial and Engineering Chemistry Reasearch, 2009. 48: p. 4638-4663.

17. Baker, R.W., Future Directions of Membrane Gas Separation Technology. Industrial

and Engineering Chemistry Reasearch, 2002. 41: p. 1393-1411.

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Page | 35

II. Nomenclature

Variable Value Units

Ji Molar flux mol/m2s

Li Coefficient of proportionality

µi Chemical potential J/mol

R Gas constant J/K mol

T Temperature K

ni number of moles mol

x distance m

γ activity coefficient mol-1

v molar volume m3/mol

P pressure Pa

Mi molar weight g/mol

ρ molar density m3/mol

Di Diffusion coefficient m2/s

π Key permeance GPU (10-6

cm3/cm

2s cmHg)

α Selectivity N/A

ṅ molar flowrate mol/s

Page | 36

III. Drawings

A – Simulator Data Entry Screens

B – Spreadsheet Data gathering function

C – Please see attached data CD

IV. Data

Please see attached CD