Abstract— This work investigated the suitability of biodiesel

(predominantly Methyl Linolenate, Methyl Palmitate, Methyl

Oleate and Methyl Stearate) as an absorbent for the recovery

of VOCs from waste gas process streams through absorption.

The objective was to predict the vapour liquid equilibria

(VLE) data, in the form of infinite dilution activity

coefficients for five VOC families, in fatty acid methyl ester

solvents. The Original Universal Functional Group Activity

Coefficient (UNIFAC) model (Fredenslund et al., 1975),

Modified UNIFAC (Larsen et al., 1981) and Modified

UNIFAC (Bastos et al., 1988) was used to predict the infinite

dilution activity coefficients. The solubility of alkanes,

amines, alkenes, organic acids and alcohols showed a decrease

in activity coefficients with an increase in molecular weight.

Shorter chained esters with a lower carbon count had higher

activity coefficients when compared to the longer chained

esters with a higher carbon count. The solubility of VOCs in

biodiesel decreases with increase in ester hydrocarbon

unsaturation.

Keywords— Activity coefficients, biodiesel, phase equilibrium,

Universal Functional Activity Coefficient.

I. INTRODUCTION

The legislation on environmental conservation in South

Africa, as outlined in the National Environmental

Management: Air Quality Act 39 of 2004, has forced all

industries to closely monitor any effluents emitted to the

environment. This work focuses on the abatement of volatile

organic compounds through physical absorption using

polymeric solvents. The selection of the absorbent is governed

by the thermodynamic interactions as measured by the infinite

dilution activity coefficients among other factors. For

preliminary feasibility studies of a physical absorption

process, thermodynamic models are used to predict the

S.Ramdharee is with the Department of Chemical Engineering, Faculty of

Engineering and the Built Environment, University of Johannesburg, Auckland Park, Johannesburg 2028 (e-mail: sashayr007@gmail.com;

sramdharee@csir.co.za)

M.Belaid is with the Department of Chemical Engineering, Faculty of Engineering and the Built Environment, University of Johannesburg,

Doornfontein, Johannesburg 2028;(e-mail: mbelaid@uj.ac.za )

required phase equilibria. These are preferred instead of

measurements which are expensive, laborious and time

consuming. Biodiesel is one of the solvents with favourable

thermodynamic interactions with volatile organic compounds.

A. Technology Selection

The technologies used for VOC recovery are mainly

separation processes such as physical and chemical

absorption. Absorption is a separation method which involves

the removal of a compound from a contaminated gas stream

by contacting it with a suitable absorption fluid. Absorption

can be physical depending on concentration gradients or

chemical where a chemical reaction is used to enhance the

absorption process. Physical absorption follows the Nerst

partition law (1).

Absorption is a physical process, and it follows the Nerst

partition law. KN, the partition coefficient depends on

temperature. Equation (1) is valid for low concentrations and

when the species x does not change its form in the two phases

[1].

)12,(2

1xNK

xx

constant (1)

B. Solvent Selection

Biodiesel is produced from vegetable oils by converting the

triglyceride oils to methyl (or ethyl) esters through a process

known as transesterification. The transesterification process

reacts alcohol with the oil to release three "ester chains" from

the glycerine backbone of each triglyceride. The

transesterification of vegetable oil was first reported by

Duffy and Patrick, 1883 [2]. The selection of a suitable

scrubbing solvent for a specific waste gas stream composition

is influenced by a high absorption capacity for the separating

component, a high selectivity with reference to other gases,

low toxicity and low volatility.

J Hu, Z Du, Z Tang and E Min, 2004 [3] investigated the

suitability of biodiesel as a solvent and reported that small

quantities of non-monoalkyl esters affect solvent power. The

length of the carbon chain of the fatty acid group of biodiesel

Volatile Organic Compounds- Biodiesel

Thermodynamic Interactions Using Group

Contribution Methods.

Sashay Ramdharee, Edison Muzenda and Mohamed Belaid

has an effect on the solvent power of biodiesel, and the longer

the carbon chain, the weaker the solvent power. The

unsaturated fatty acid esters have a higher solvent dissolving

power than the saturated fatty esters, but the number of double

bonds in the unsaturated fatty acid esters has little effect on the

solvent power. Lastly the alcohol type also influences the

solvent power of biodiesel. The longer carbon chain of the

alcohol makes the dissolving power of biodiesel smaller.

Biodiesel is environmentally friendly, has a low volatility and

is also a renewable resource with low viscosity and good

solubility properties [4]. The largest fraction of biodiesel

consists of C16-C18 methyl esters which are readily

biodegradable. It can be produced at competitive prices [5].

C. Model Selection

Infinite dilution activity coefficients play an important role in

the analysis and design of separation processes such as

extractive and azeotropic distillation and liquid-liquid

extraction. At infinite dilution the single solute molecule is

completely surrounded by the solvent. Hence, infinite dilution

activity coefficients, (γ∞) are useful as they give a measure of

the greatest degree of non-ideality of a mixture [6].

The most successful methods currently used for the

calculation of activity coefficients are the group contribution

methods, in which the liquid phase is considered to be a

mixture of structural groups. The most well-known and

accurate of the group contribution methods proposed is the

Universal Functional Activity Coefficient (UNIFAC) [7].

Fredenslund, Jones and Prausnitz developed the UNIFAC

model in 1975 [8]. The UNIFAC method is a semi-empirical

system for non-electrolyte activity coefficients estimation in

non-ideal mixtures. It utilizes functional groups present in the

molecules that make up the liquid mixture to compute activity

coefficients. By utilising interactions for each of the

functional groups present in the molecules, as well as some

binary interaction coefficients, the activity coefficients can be

computed [9]. In the Original UNIFAC model (Fredenslund);

the activity coefficient is expressed as the sum of the

combinatorial and residual parts respectively [10].

r

i

c

ii lnlnln (2)

In equation (2), γcom

and γres

represent the combinatorial

(accounting for size and shape) and the residual (accounting

for energetic interactions) parts respectively. Many

modifications have been proposed to the both the residual and

combinatorial terms in order to improve the performance of

the UNIFAC model in the prediction of VLE, γ∞ and excess

enthalpies.

II. GROUP CONTRIBUTION METHODS

The group contribution method uses the principle that the

some simple aspects of structures of chemical components are

always the same in many different molecules. For example,

all organic components are built from carbon, hydrogen,

oxygen, nitrogen and halogens etc. This coupled with a

single, double or triple bonds means that there are only ten

atom types and three bond types with which we can use to

build thousands of molecules. The next more complex

building blocks of the components are the functional groups

which are themselves built of a few atoms and bonds.

Group contribution methods are used to predict the properties

of pure components and mixtures by using group properties.

This reduces the amount of data required radically. Therefore,

instead of requiring the properties of millions of components,

only the data for a few groups are required.

The group contribution concept has been used to estimate

various chemical properties of pure compounds such as

densities, heat capacities and critical constants [11]. Since the

early applications of group contribution methods, they have

been developed and applied to calculate activity coefficients

of the components in a liquid mixture. When considering

mixtures of molecules in terms of the fundamental groupings

of atoms, the following aspects should be accounted for: the

organization of the molecules in the solution and in the

standard state, the restrictions imposed on these interactions

by the organization of the groups into molecules and the

interaction of various groups which can occur in the solution

and in the standard state.

The advantage of group contribution methods is that it allows

for systematic interpolation and extrapolation of VLE data for

many chemical mixtures. It also offers an appropriate way of

predicting properties of mixtures for which experimental data

is limited. When considering such mixtures it is not necessary

to measure the intermolecular interactions as they can be

calculated from known group interaction parameters [12].

However, these are found from experimental data not

necessarily with the same molecules as those in the

investigated mixture, but containing the same functional

groups.

A. Original UNIFAC model (Fredenslund et al.,

1975)

In this model, the infinite dilution activity coefficient is

expressed as the sum of the combinatorial and residual

contributions:

r

i

c

ii lnlnln (3)

In equation (3), c

iln is the combinatorial part accounting for

differences in the size and shape of the molecules and r

iln is

the residual that accounts mainly for the effects arising from

energetic interactions between groups present in solution.

For the combinatorial part:

i

i

i

i

i

i

i

i

ic

i qz

xx

1ln

21lnln (4)

In equation (4), i , i is the molar weighted segment and area

fractional components for the ith

molecule in the total system, z

being the coordination number respectively. ri and qi are

calculated from the group surface area and volume

contributions as in (6) and (7) respectively

j

jj

iii

rx

rx (5)

k

k

i

ki Rvr (6)

k

k

i

ki Qvq (7)

j

jj

iii

qx

qx (8)

The residual part is calculated as in (9)

)ln(lnln i

kk

k

i

k

r

i v (9)

m

n

nmn

mkm

m

mkmkk Q

ln1ln (10)

In (10), k is the activity of an isolated group in a solution

consisting only of molecules of type i. The calculation of the

residual activity coefficient ensures that the condition for the

limiting case of a single molecule in a pure component

solution is obeyed by ensuring that the activity is equal to 1.

m is the summation of the area fraction of group m, over all

the different groups and is somewhat similar in form, but not

the same as i . mn is the group interaction parameter and

is a measure of the interaction energy between groups. Xn is

the group mole fraction.

In (11), m is the group parameter

n

nn

mm

mxQ

xQ (11)

(12), mx is the group mole fraction.

nj

j

i

n

j

j

i

m

mxv

xv

x

,

(12)

mn, the group interaction parameter is calculated using (13)

T

amnmn exp (13)

In (13), mna represents the net energy of interaction between

groups’ m and n and has the units of SI Kelvin [13].

B. Modified UNIFAC (Larsen et al., 1981)

Larsen presented a modified version of the UNIFAC (Lyngby

modified UNIFAC) in which the Staverman-Guggeheim

combinatorial part was changed to a Flory-Huggings

combinatorial part with a modified volume fraction. He also

introduced temperature dependant group interaction

parameters. This model allows for the simultaneous

presentation of VLE and excess enthalpies. It is also capable

of presenting liquid-liquid equilibria using the modified

UNIFAC-VLE parameters with the same quality as the

original UNIFAC with LLE based parameters of Magnusses,

1982 [14]. The combinatorial term and the group interaction

parameters of the residual part were modified according to

(14) and (15):

i

i

i

icomb

i xx

1lnln (14)

In (14), i the segment fraction of component (i) calculated

from (15).

jj

iii

rx

rx 32

(15)

The interaction parameter mn in the residual part is

calculated from (16).

T

TTT

TTcTTba mnmnmn

mn

)ln()(exp

00

0

(16)

In (16), 0T is taken as a reference temperature equal to

298.15K (25oC)

C. Modified UNIFAC (Bastos et al., 1988)

The Modified UNIFAC (Bastos et al., 1988) only modifies the

combinatorial part of the Original UNIFAC of Fredenslund et

al, 1975 [15]

i

i

i

i

i

i

i

i

ic

i qz

xx

1ln

21lnln (17)

In (17), i is calculated from (18):

j

jj

iii

rx

rx

32

(18)

III. METHODOLOGY

A Microsoft excel spread sheet was developed for the

computation of the required phase equilibrium. Tables

including Component Identification, Original UNIFAC Group

Interaction Parameters (GIP), Modified UNIFAC Group

Interaction Parameters (GIP), Van der Waals parameters, and

‘Rk’ and ‘Qk’ parameter tables, were generated as part of the

computation procedure.

IV. RESULTS & DISCUSSION

This section discusses the thermodynamic interactions of 25

volatile organic compounds in four methyl esters namely

methyl linolenate, methyl oleate, methyl stearate and methyl

palmitate. The objective was achieved using the Original

UNIFAC of Fredenslund et al, 1975; Modified UNIFAC of

Bastos et al, 1988 and the Modified UNIFAC of Larsen et al.,

1981.

A. Alkanes

Figure 4-1: Variation of activity coefficients with mole fraction for the Alkane family in Methyl Palmitate for a) Original

UNIFAC; b) Modified UNIFAC Bastos; c) Modified UNIFAC Larsen; Methyl Linolenate for d) Original UNIFAC; e) Modified

UNIFAC Bastos; f) Modified UNIFAC Larsen

a) d)

b) e)

e) f)

Figure 4-1: The mole fraction variation of the Alkane family in Methyl Palmitate for a) Original

UNIFAC; b) Modified UNIFAC Bastos; c) Modified UNIFAC Larsen; Methyl Linolenate for d) Original

UNIFAC; e) Modified UNIFAC Bastos; f) Modified UNIFAC Larsen

0

0.2

0.4

0.6

0.8

1

1.2

0

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0.9 1

Act

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eff

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Mol fraction

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Mol fraction

0

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0

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0

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0

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1

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0.9 1

Act

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eff

icie

nt

Mol fraction

Figure 4-2: Variation of activity coefficients with mole fraction for the Alkane family in Methyl Stearate for a) Original

UNIFAC; b) Modified UNIFAC Bastos; c) Modified UNIFAC Larsen; Methyl Oleate for d) Original UNIFAC; e) Modified

UNIFAC Bastos; f) Modified UNIFAC Larsen

a) d)

b) e)

e) f)

Figure 4-2: The mole fraction variation of the Alkane family in Methyl Stearate for a) Original

UNIFAC; b) Modified UNIFAC Bastos; c) Modified UNIFAC Larsen; Methyl Oleate for d) Original

UNIFAC; e) Modified UNIFAC Bastos; f) Modified UNIFAC Larsen

0

0.2

0.4

0.6

0.8

1

1.2

0.1

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0.5

0.6

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0.9 1

Act

ivit

y co

eff

icie

nt

Mol fraction

0

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0.8

1

1.2

0

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Act

ivit

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eff

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nt

Mol fraction

0

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1

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Act

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Mol fraction

0

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1

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Mol fraction

0

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1

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Mol fraction

0

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1

0

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Act

ivit

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eff

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nt

Mol fraction

-Interactions of alkanes in saturated/unsaturated esters

Methyl oleate/alkane interactions yield lower activity

coefficients compared to methyl linolenate/alkane interactions

which are also higher than those of methyl stearate. Thus

solubility of the VOCs decreased with an increase in the ester

hydrocarbon chain unsaturation.

The (C-C) bond has a dissociation energy of 347kJ/mol and

the (C=C) bond has dissociation energy of 839kJ/mol.

Therefore, more energy is required to break the solute-solute

bonds in unsaturated esters to allow for solute-solvent bonds

to form, thereby accounting for the higher activity

coefficients. Also, the higher activity coefficients are due to

the cis-formation of the unsaturated double bonds. This

results in a reduced solvent surface area for solute/solvent

interactions to occur, thus resulting in higher activity

coefficients for unsaturated esters.

B. Amines

The solubility of amines decreases with increase in VOC

molecular weight, Figs. 4-3 and 4-4. This can be attributed to

an increase in the Van der Waals forces between solute-solute

interactions as VOC molecular weight is increased. Thus,

increased energy is required to break the solute-solute bonds

to allow for solute-solvent interactions. The greatest solubility

was observed with tertiary amines due to hydrogen bonding.

Bond disassociation energies are responsible for the variation

in activity coeffients shown in Figs. 4-3 and 4-4. The bond

disassociation energies for (N-H), (C=O), (C-H) are

392kJ/mol, 802kJ/mol and 414 kJ/mol respectively. . Due to

the low electronegativity of the nitrogen atom, the hydrogen

molecule is available for bonding with the solvent. Therefore,

less energy is required to break the solute-solute bonds,

allowing for solute-solvent bonds to form, hence the increased

solubility, .

The VOCs solubility increases with the increase in the esters

molecular weight. As the solvent increases in size the surface

area also increases affecting the intensity of the London

dispersion forces of the solvent molecule, thus enhancing

solute solubility.

-Interactions of amines in saturated/unsaturated esters

Amines were most soluble in methyl stearate. Solubility of

amine VOCs decreased with an increase in unsaturation in the

ester hydrocarbon chain, Figs. 4-3 and 4-4. More energy is

required to break the solute – solute bonds in unsaturated

esters allowing for solute – solvent bond formation accounting

for low solubility. The low solubility is due to cis-formation of

the unsaturated bonds resulting in reduced solubility in

unsaturated esters.

Figure 4-3: Variation of activity coefficients with mole fraction for the Amine family in Methyl Palmitate for a) Original

UNIFAC; b) Modified UNIFAC Bastos; c) Modified UNIFAC Larsen; Methyl Linolenate for d) Original UNIFAC; e) Modified

UNIFAC Bastos; f) Modified UNIFAC Larsen

a) d)

b) e)

a) f)

Figure 4-3: The mole fraction variation of the Amine family in Methyl Palmitate for a) Original

UNIFAC; b) Modified UNIFAC Bastos; c) Modified UNIFAC Larsen; Methyl Linolenate for d) Original

UNIFAC; e) Modified UNIFAC Bastos; f) Modified UNIFAC Larsen

0

0.2

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1

1.2

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0.4

0.5

0.6

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1

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Mol fraction

Fig. 4-4 : Variation of activity coefficients with mole fraction for the Amine family in Methyl Stearate for a) Original UNIFAC;

b) Modified UNIFAC Bastos; c) Modified UNIFAC Larsen; Methyl Oleate for d) Original UNIFAC; e) Modified UNIFAC

Bastos; f) Modified UNIFAC Larsen

a) d)

b) e)

c) f)

Figure 4-4: The mole fraction variation of the Amine family in Methyl Stearate for a) Original

UNIFAC; b) Modified UNIFAC Bastos; c) Modified UNIFAC Larsen; Methyl Oleate for d) Original

UNIFAC; e) Modified UNIFAC Bastos; f) Modified UNIFAC Larsen

0

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Mol fraction

C. Alkenes

The low activity coefficients of alkene VOCs in Figs 4-5 and

4-6 are due to the polarizing effect caused by the delocalised

electron cloud around the benzene molecule. Spectroscopic

evidence shows that all bond lengths are equal and

intermediate between single and double bond lengths and that

the benzene molecule is flat [16]. The solubility of alkenes

decrease with increase in VOC molecular weight due to the

increase in Van der Waals forces between solute – solute

interactions, Figs 4-5 and 4-6.

-Interactions of alkenes in saturated/unsaturated esters

Solubility decreases with increase in unsaturation in the ester

hydrocarbon chain, Figs 4-5 and 4-6. A lot of energy is

required for solute – solvent bond formation. The low

solubility can also be attributed to cis-formation of the

unsaturated double bonds.

D. Organic acids

For organic acids, solubility decreases with increase in VOC

molecular weight, Figs 4-7 and 4-8. This could be due to the

increase in Van der Waals forces bewteen solute – solute

molecules. Hence more energy is required to overcome the

the attractive forces to allow for solute – solvent interactions.

Solubility also decreases with an increase in unsaturation of

the solvent.

E. Alcohols

An increase in Van der Waals forces of attraction with

increased alcohol chain length accounts for the decrease in

solubility with increase in solute molecular weight, Figs 4-9

and 4-10.

Figure 4-5: Variation of activity coefficients with mole fraction for the Alkene family in Methyl Palmitate for a) Original

UNIFAC; b) Modified UNIFAC Bastos; c) Modified UNIFAC Larsen; Methyl Linolenate for d) Original UNIFAC; e) Modified

UNIFAC Bastos; f) Modified UNIFAC Larsen

a) d)

b) e)

a) d)

Figure 4-5: The mole fraction variation of the Alkene family in Methyl Palmitate for a) Original

UNIFAC; b) Modified UNIFAC Bastos; c) Modified UNIFAC Larsen; Methyl Linolenate for d) Original

UNIFAC; e) Modified UNIFAC Bastos; f) Modified UNIFAC Larsen

0

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Mol fraction

0

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0.4

0.6

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1

1.2

0

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0.2

0.3

0.4

0.5

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0.8

0.9 1

Act

ivit

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nt

Mol fraction

0

0.2

0.4

0.6

0.8

1

1.2

1.4

0

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0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9 1

Act

ivit

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eff

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nt

Mol fraction

0

0.2

0.4

0.6

0.8

1

1.2

1.4

0

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0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9 1

Act

ivit

y co

eff

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nt

Mol fraction

0

0.2

0.4

0.6

0.8

1

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9 1

Act

ivit

y co

eff

icie

nt

Mol fraction

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9 1

Act

ivit

y co

eff

icie

nt

Mol fraction

Figure 4-6: Variation of activity coefficients with mole fraction for the Alkene family in Methyl Stearate for a) Original

UNIFAC; b) Modified UNIFAC Bastos; c) Modified UNIFAC Larsen; Methyl Oleate for d) Original UNIFAC; e) Modified

UNIFAC Bastos; f) Modified UNIFAC Larsen

a) d)

b) e)

c) f)

Figure 4-6: The mole fraction variation of the Alkene family in Methyl Stearate for a) Original

UNIFAC; b) Modified UNIFAC Bastos; c) Modified UNIFAC Larsen; Methyl Oleate for d) Original

UNIFAC; e) Modified UNIFAC Bastos; f) Modified UNIFAC Larsen

0

0.2

0.4

0.6

0.8

1

1.2

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9 1

Act

ivit

y c

oe

ffic

ien

t

Mol fraction

0

0.2

0.4

0.6

0.8

1

1.2

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9 1

Act

ivit

y c

oe

ffic

ien

t

Mol fraction

0

0.2

0.4

0.6

0.8

1

1.2

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9 1

Act

ivit

y c

oe

ffic

ien

t

Mol fraction

0

0.2

0.4

0.6

0.8

1

1.2

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9 1

Act

ivit

y c

oe

ffic

ien

t

Mol fraction

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9 1

Act

ivit

y c

oe

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ien

t

Mol fraction

0

0.1

0.2

0.3

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0.5

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0.9 1

Act

ivit

y c

oe

ffic

ien

t

Mol fraction

Figure 4-7: Variation of activity coefficients with mole fraction for the Organic acids family in Methyl Palmitate for a) Original

UNIFAC; b) Modified UNIFAC Bastos; c) Modified UNIFAC Larsen; Methyl Linolenate for d) Original UNIFAC; e) Modified

UNIFAC Bastos; f) Modified UNIFAC Larsen

a) d)

b) e)

c) f)

Figure 4-7: The mole fraction variation of the Carboxylic acid family in Methyl Palmitate for a)

Original UNIFAC; b) Modified UNIFAC Bastos; c) Modified UNIFAC Larsen; Methyl Linolenate for d)

Original UNIFAC; e) Modified UNIFAC Bastos; f) Modified UNIFAC Larsen

0

0.2

0.4

0.6

0.8

1

1.20

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9 1

Act

ivit

y co

eff

icie

nt

Mol fraction

0

0.2

0.4

0.6

0.8

1

1.2

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9 1

Act

ivit

y co

eff

icie

nt

Mol fraction

0

0.2

0.4

0.6

0.8

1

1.2

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9 1

Act

ivit

y co

eff

icie

nt

Mol fraction

0

0.2

0.4

0.6

0.8

1

1.2

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9 1

Act

ivit

y co

eff

icie

nt

Mol fraction

0

0.2

0.4

0.6

0.8

1

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9 1

Act

ivit

y co

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icie

nt

Mol fraction

0

0.1

0.2

0.3

0.4

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0.7

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0

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0.3

0.4

0.5

0.6

0.7

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0.9 1

Act

ivit

y co

eff

icie

nt

Mol fraction

Figure 4-8: Variation of activity coefficients with mole fraction for the Organic Acids family in Methyl Stearate for a) Original

UNIFAC; b) Modified UNIFAC Bastos; c) Modified UNIFAC Larsen; Methyl Oleate for d) Original UNIFAC; e) Modified

UNIFAC Bastos; f) Modified UNIFAC Larsen

a) d)

a) e)

c) f)

Figure 4-8: The mole fraction variation of the Carboxylic Acid family in Methyl Stearate for a) Original

UNIFAC; b) Modified UNIFAC Bastos; c) Modified UNIFAC Larsen; Methyl Oleate for d) Original

UNIFAC; e) Modified UNIFAC Bastos; f) Modified UNIFAC Larsen

0

0.2

0.4

0.6

0.8

1

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9 1

Act

ivit

y co

eff

icie

nt

Mol fraction

0

0.2

0.4

0.6

0.8

1

1.2

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9 1

Act

ivit

y co

eff

icie

nt

Mol fraction

0

0.2

0.4

0.6

0.8

1

1.2

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9 1

Act

ivit

y co

eff

icie

nt

Mol fraction

0

0.2

0.4

0.6

0.8

1

1.20

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9 1

Act

ivit

y co

eff

icie

nt

Mol fraction

0

0.1

0.2

0.3

0.4

0.5

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0.8

0

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0.3

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0.8

0.9 1

Act

ivit

y co

eff

icie

nt

Mol fraction

0

0.2

0.4

0.6

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1

0

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0.3

0.4

0.5

0.6

0.7

0.8

0.9 1

Act

ivit

y co

eff

icie

nt

Mol fraction

Figure 4-9: Variation of activity coefficients with mole fraction for the Alcohols family in Methyl Palmitate for a) Original

UNIFAC; b) Modified UNIFAC Bastos; c) Modified UNIFAC Larsen; Methyl Linolenate for d) Original UNIFAC; e) Modified

UNIFAC Bastos; f) Modified UNIFAC Larsen

a) d)

b) e)

c) f)

Figure 4-9: The mole fraction variation of the Alcohol family in Methyl Palmitate for a) Original

UNIFAC; b) Modified UNIFAC Bastos; c) Modified UNIFAC Larsen; Methyl Linolenate for d) Original

UNIFAC; e) Modified UNIFAC Bastos; f) Modified UNIFAC Larsen

0

0.2

0.4

0.6

0.8

1

1.2

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9 1

Act

ivit

y co

eff

icie

nt

Mol fraction

0

0.2

0.4

0.6

0.8

1

1.2

0

0.1

0.2

0.3

0.4

0.5

0.6

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0.8

0.9 1

Act

ivit

y co

eff

icie

nt

Mol fraction

0

0.2

0.4

0.6

0.8

1

1.2

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9 1

Act

ivit

y co

eff

icie

nt

Mol fraction

0

0.2

0.4

0.6

0.8

1

1.2

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9 1

Act

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y co

eff

icie

nt

Mol fraction

0

0.1

0.2

0.3

0.4

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0.8

0.9

0

0.1

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0.3

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Act

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nt

Mol fraction

0

0.1

0.2

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0.9

0

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0.3

0.4

0.5

0.6

0.7

0.8

0.9 1

Act

ivit

y co

eff

icie

nt

Mol fraction

Figure 4-10: Variation of activity coefficients with mole fraction for the Alcohols family in Methyl Stearate for a) Original

UNIFAC; b) Modified UNIFAC Bastos; c) Modified UNIFAC Larsen; Methyl Oleate for d) Original UNIFAC; e) Modified

UNIFAC Bastos; f) Modified UNIFAC Larsen

a) d)

b) e)

c) f)

Figure 4-10: The mole fraction variation of the Alcohol family in Methyl Stearate for a) Original

UNIFAC; b) Modified UNIFAC Bastos; c) Modified UNIFAC Larsen; Methyl Oleate for d) Original

UNIFAC; e) Modified UNIFAC Bastos; f) Modified UNIFAC Larsen

0

0.2

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1

1.2

0

0.1

0.2

0.3

0.4

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Act

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icie

nt

Mol fraction

0

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1.2

0

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0.3

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Act

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icie

nt

Mol fraction

0

0.2

0.4

0.6

0.8

1

1.2

0

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0.2

0.3

0.4

0.5

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0.8

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Act

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icie

nt

Mol fraction

0

0.2

0.4

0.6

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1

1.2

0

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0.2

0.3

0.4

0.5

0.6

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0.9 1

Act

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nt

Mol fraction

0

0.1

0.2

0.3

0.4

0.5

0.6

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0.9

0

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0.2

0.3

0.4

0.5

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0.9 1

Act

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icie

nt

Mol fraction

0

0.1

0.2

0.3

0.4

0.5

0.6

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0.9

0

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0.3

0.4

0.5

0.6

0.7

0.8

0.9 1

Act

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Mol fraction

V. CONCLUSION

This paper discusses the interactions of 25 volatile organic

compounds with biodiesel. The Original UNIFAC:

Fredenslund et al, 1975; Modified UNIFAC: Bastos et al,

1988 and the Modified UNIFAC (Larsen et al., 1981) were

used to compute the desired phase equilibria. Biodiesel was

found to be thermodynamically suitable for the physical

absorption of the selected VOCs.

ACKNOWLEDGMENT

The authors wish to acknowledge University of Johannesburg

and the CSIR for the financial and technical support.

REFERENCES

[1] N.P. Cheremisinoff,. Handbook of Air Pollution Prevention and

Control, Elsevier Science, 2002

[2] Biodiesel [online]. 2012 [cited 2012 Sept]. Available from URL:

http://www.wikipedia.com [3] Jianbo H, Zexue D, Zhong Tang, E Min. Study on the Solvent Power of

a New Green Solvent: Biodiesel. Ind. Eng. Chem. Res. 2004, 43, 7928-

7931 [4] K. Bay, H. Wanko, J. Ulrich,. Absorption of Volatile Organic

Compounds in Biodiesel: Determination of Infinite Dilution Activity

Coefficients by Headspace Gas Chromatography, Chem. Eng. Res. Des,2006, Vol. 84, 22–27

[5] Wilson A, Canas M, Uriel EG, Julian D., Comparison of different cubic

equations of state and combination rules for predicting residual chemical potential of binary and ternary Lennard–Jones mixtures:

Solid-supercritical fluid phase equilibria. Fluid Phase Equilibria 2005,

42–50 [6] Voustas E.C, D.P Tassios., Prediction of infinite dilution activity

coefficient in binary mixtures with the UNIFAC. A critical evaluation.

Ind Eng. Chem Res.1996,35,1438-1445 [7] Herber RP, Soares RP,. Assessing the reliability of predictive activity

coefficient models for molecules consisting of several groups. Braz. J.

Chem Eng 2013, Vol 30, 1 [8] Activity coefficient [online]. 2012 [cited 2012 Sept]. Available from

URL: http://www.wikipedia.com

[9] H.K Hansen, P. Rasmussen, A. Fredenslund, M. Schiller, J. Gmehling,. Vapor-Liquid Equilibria by UNIFAC Group Contribution. 5. Revision

and Extension, Ind. Eng. Chem., 1991, Vol. 30,2355–2358

[10] Fredenslund, A. Jones, R. L., Prausnitz,. J. M. Group Contribution Estimation of Activity Coefficients in Non-ideal Liquid Mixtures.

AIChE J. 1975, 21, 1086

[11] Soave Redlich Kwong EOS- Department of Energy and Mineral

processing. [online]. 2012 [cited 2012 Sept]. Available from URL:

http://www.eme.psu.edu

[12] Somaieh S, Marc A. Dub,. Biodiesel: a green polymerization solvent. The Royal Society of Chemistry, Green Chem., 2008, 10, 321–326

[13] Larsen, B. L. Rasmussen, P. Fredenslund,. UNIFAC Parameter Table

for Prediction of Liquid-Liquid Equilibria. Ind. Eng. Chem. Process Des. Dev. 1981, 20, 331

[14] H.O. Paksoy, S. Örnektekin, B. Bilgin, Y. Demirel,. The Performance

of UNIFAC and Related Group Contribution Models Part I. Prediction of Infinite Dilution Activity Coefficients, Thermochimica Acta, 1996,

Vol. 287, 235–249

[15] Bastos, J.C. Soares,. M. E., Medina, A. G. Infinite Dilution Activity Coefficients by UNIFAC Group Contribution. Ind. Eng. Chem. Res.

1988, 27, 116

[16] Graham Solomoins TX,. Organic Chemistry Solomons 6th Edition. August, 1995, Chap 14, 614-654

S. Ramdharee: The author was born in 1984 in

Newcastle, Kwa-Zulu Natal, South Africa. This author became a member of ECSA (Engineering

Council of South Africa) in 2010. He successfully

completed a NDip: Chemical Engineering at Durban

University of Technology, Kwa-Zulu Natal, South Africa in 2007. After

which he pursued a BTech: Chemical Engineering at the same institution in

2008, graduating Cum Laude, with the Deans Merit award for being the top

student in year 2008, and also received the award for Mathematics, Statistics

and Physics Year 2008. Currently he is studying towards a MTech: Chemical Engineering at the University of Johannesburg, Gauteng, South Africa and

completing the PMP® certification with the American based Project

Management Institute.

He has worked at African Amines: Junior production engineer; Karbochem

ltd: Junior projects engineer; International Furan Technology: Chemical engineer; Sasol Synfuels: Senior as-built auditor; Sasol Synfuels: Process

technologist; National Cleaner Production Centre of South Africa: Regional

project manager: Energy systems optimization.

Mohamed Belaid obtained Msc Chemical Engineering, UKZN South Africa (2001), BSC

Industrial Chemical Engineering, Engineering of

organic processes (1994), University of Blida, Algeria, currently is doing PhD at Wits University

(South Africa). Mohamed is a senior lecturer at the

University of Johannesburg, worked as a lecturer at the University of Kwazulu Natal for over 8 years, a

quality control Engineer for Energy Engineering PTY

(South Africa) for two years and Elangeni oil and soap (South Africa) for a period of two years, process Engineer (SAIDAL, antibiotic company, Algeria)

for one year.

Mr. Belaid is a member of SAIChE (2003, South Africa institute of

Chemical Engineers) and He is a research member at the department of Chemical Engineering, authored and contributed to various publications, both

journals and conferences proceedings in environmental engineering,

separation processes, mineral processing, fluidized beds, activated carbon and engineering Education

Edison Muzenda is a Full Professor of Chemical and Petroleum Engineering, and Head of

Chemical, Materials and Metallurgical Engineering Department at Botswana

International University of Science and

Technology. He is also a Visiting Professor in the Department of Chemical Engineering, Faculty of

Engineering and Built Environment, University of

Johannesburg. He was previously a Full Professor of Chemical Engineering, the Research and

Postgraduate Coordinator as well as Head of the Environmental and Process

Systems Engineering and Bioenergy Research Groups at the University of Johannesburg. Professor Muzenda holds a PhD in Chemical Engineering from

the University of Birmingham, United Kingdom. He has more than 16 years’

experience in academia which he gained at various institutions including the National University of Science and Technology, Zimbabwe, University of

Birmingham, University of Witwatersrand, and most importantly the

University of Johannesburg. Through his academic preparation and career, He has held several management and leadership positions such as member of the

student representative council, research group leader, university committees’

member, staff qualification coordinator as well as research and postgraduate coordinator. Edison’s teaching interests and expertise are in unit operations,

multi-stage separation processes, environmental engineering, chemical

engineering thermodynamics, professional engineering skills, research methodology as well as process economics, management and optimization. He

is a recipient of several awards and scholarships for academic excellence. His

research interests are in green energy engineering, integrated waste management, volatile organic compounds abatement and as well as phase

equilibrium measurement and computation. He has contributed to more than

280 international peer reviewed and refereed scientific articles in the form of

journals, conferences books and book chapters. He has supervised more than

30 postgraduate students and over 250 Honours and BTech research students.

He serves as reviewer for a number of reputable international conferences and journals. Edison is a member of several academic and scientific organizations

including the Institute of Chemical Engineers, UK and South African Institute

of Chemical Engineers. He is an Editor for a number of Scientific Journals and Conferences. He has organized and chaired several international

conferences. He currently serves as an associate Editor of the South African

Journal of Chemical Engineering. His current research activities are mainly

focused on WASTE to ENERGY projects particularly bio-waste to energy for

vehicular application in collaboration with SANEDI and City of Johannesburg

PIKITUP as well as waste tyre and plastics utilization for fuels and valuable

chemicals in collaboration with Recycling and Economic Development Initiative of South Africa (REDISA). He has been in the top 3 and 10 research

output contributors in the faculty of Engineering and the Built Environment

and the University of Johannesburg respectively since 2010. In 2013, Prof Muzenda was the top and number 2 research output contributor in the Faculty

of Engineering and Built Environment, and University of Johannesburg

respectively. Edison is a member of the South African Government Ministerial Advisory Council on Energy and Steering Committee of City of

Johannesburg – University of Johannesburg Biogas Digester Project.