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Kinetics of thepre-treatment of used

cooking oil using Novozyme435 for biodiesel production

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Citation: HAIGH, K.F. ... et al, 2014. Kinetics of the pre-treatment of usedcooking oil using Novozyme 435 for biodiesel production. Chemical EngineeringResearch and Design, 92 (4), pp. 713�719.

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Chemical Engineering Research and Design

j ourna l h omepage: www.elsev ier .com/ locate /cherd

Kinetics of the pre-treatment of used cooking oilusing Novozyme 435 for biodiesel production

Kathleen F. Haigha, Goran T. Vladisavljevic a, James C. Reynoldsb,Zoltan Nagya, Basudeb Sahac,∗

a Department of Chemical Engineering, Loughborough University, Loughborough, Leicestershire LE11 3TU, UnitedKingdomb Department of Chemistry, Loughborough University, Loughborough, Leicestershire LE11 3TU, United Kingdomc Centre for Green Process Engineering, Department of Applied Sciences, Faculty of Engineering, Science and the BuiltEnvironment, London South Bank University, London SE1 0AA, United Kingdom

a b s t r a c t

The pre-treatment of used cooking oil (UCO) for the preparation of biodiesel has been investigated using Novozyme

435, Candida antarctica Lipase B immobilised on acrylic resin, as the catalyst. The reactions in UCO were carried

out using a jacketed batch reactor with a reflux condenser. The liquid chromatography–mass spectrometry (LC–MS)

method was developed to monitor the mono-, di- and triglyceride concentrations and it was found that the method

was sensitive enough to separate isomers, including diglyceride isomers. It was found that the 1,3 diglyceride isomer

reacted more readily than the 1,2 isomer indicating stereoselectivity of the catalyst. This work showed that Novozyme

435 will catalyse the esterification of free fatty acids (FFAs) and the transesterification of mono- and diglycerides

typically found in UCO when Novozyme 435 is used to catalyse the pre-treatment of UCO for the formation of

biodiesel. A kinetic model was used to investigate the mechanism and indicated that the reaction progressed with

the sequential hydrolysis esterification reactions in parallel with transesterification.

© 2014 The Institution of Chemical Engineers. Published by Elsevier B.V. All rights reserved.

Keywords: Biodiesel; Liquid chromatography; Used cooking oil; Novozyme 435; Kinetic model; Fatty acid methyl esters

(FAMEs); Esterification; Ping Pong Bi Bi mechanism

1. Introduction

Biodiesel is defined as mono-alkyl esters of long chain fattyacids derived from renewable sources, particularly vegetableoil and animal fats (Knothe, 2010; Zainal-Abidin-Murad et al.,2012). The most common commercial process is to convertvegetable oil to biodiesel by means of a transesterificationreaction, with methanol in the presence of a basic catalyst,such as sodium hydroxide, resulting in the formation of fattyacid methyl esters (FAME), as shown in Fig. 1. This reaction pro-ceeds in a stepwise manner with the triglycerides (TG) beingconverted to diglycerides (DG) and the DGs subsequently con-verted to monoglycerides (MGs).

Vegetable oil is an expensive raw material and there areethical concerns with using a potential food source for fuel.As a result alternative raw materials such as Jatropha curcas

∗ Corresponding author. Tel.: +44 02078157190; fax: +44 02078157699.E-mail address: b.saha@lsbu.ac.uk (B. Saha).Received 26 July 2013; Received in revised form 2 December 2013; Accepted 4 January 2014

(Patil et al., 2009), by-products from oil refining such as palmfatty acid distillate (Talukder et al., 2009), animal fats, algal oil(Semwal et al., 2011) and used cooking oil (UCO) (Akoh et al.,2007; Enweremadu and Mbarawa, 2009) are currently beinginvestigated to mitigate these issues. The advantage of UCO isthat a waste material is diverted from landfill, simultaneouslyeliminating the competition with food and reducing the cost.The cooking process causes the vegetable oil, TGs, to break-down to form, DGs, MGs, and free fatty acids (FFAs). The FFAsreact with the basic catalysts used during transesterificationin a saponification side reaction which can form an emulsionand reduce product yield. In addition, most biodiesel speci-fications impose an upper limit on the FFAs content as FFAscan cause deposits and engine damage (Knothe, 2005). Ester-ification can be used to convert the FFAs to biodiesel and aschematic of the esterification process is shown in Fig. 2.

0263-8762/$ – see front matter © 2014 The Institution of Chemical Engineers. Published by Elsevier B.V. All rights reserved.http://dx.doi.org/10.1016/j.cherd.2014.01.006

714 chemical engineering research and design 9 2 ( 2 0 1 4 ) 713–719

Fig. 1 – A schematic representation of the transesterification reaction.

Fig. 2 – A schematic representation of the esterification reaction.

The heterogeneous catalysts used to investigate esterifi-cation for biodiesel production can be classified as inorganicacid catalysts (Cordeiro et al., 2008; Park et al., 2010), ion-exchange resin catalysts (Ozbay et al., 2008; Russbueldt andHoelderich, 2009) and immobilised enzymes (Talukder et al.,2009; Souza et al., 2009). Ion-exchange resins and immobilisedenzymes are more suitable for an environmentally benignprocess because relatively high conversions are possible at rel-atively benign conditions (Enweremadu and Mbarawa, 2009;Zainal-Abidin-Murad et al., 2012)

Novozyme 435, Candida antarctica Lipase B immobilisedon acrylic resin, was investigated for the esterificationpre-treatment of biodiesel from UCO and the catalytic per-formance was compared to an ion-exchange resin catalyst,Purolite D5082 (Haigh et al., 2013). It was found a faster conver-sion was possible at more benign conditions when Novozyme435 was used compared to Purolite D5082. In addition, it wasfound that at the higher reaction temperatures (50–60 ◦C) theamount of FAME formed was greater than the amount of FFAsconsumed based on the esterification reaction as shown inFig. 2. Lipases including Novozyme 435 have also been inves-tigated for transesterification and hydrolysis (Ganesan et al.,2009; Lam et al., 2010; Tongboriboon et al., 2010) althoughit has been found that the reaction rate is slow comparedto esterification. In order to determine if Novozyme 435 cansimultaneously catalyse esterification and transesterificationreactions in UCO, it is necessary to monitor the MG, DG andTG concentrations in addition to FAME and FFAs. Gas chro-matography (GC) and liquid chromatography (LC) are the mostcommon methods for investigating the production of biodiesel(Li et al., 2008). Substances with high molecular weights, highboiling points and low volatility are not easily vapourisedand separated by GC, although this problem can be over-come by means of a silylation reaction and the use of internalstandards (Holcapek et al., 1999; Li et al., 2008). LC is a ver-satile analytical technique and most samples do not requirederivatisation and as a result numerous methods have beeninvestigated for the separation and quantification of biodieselcomponents (Holcapek et al., 1999; Li et al., 2008; Santori et al.,2009). Ultra violet (UV) and mass spectrometry (MS) detectorshave been investigated for the detection of biodiesel compo-nents (Holcapek et al., 1999; Türkan and Kalay, 2006; Santoriet al., 2009). The disadvantage of UV detectors for complex

mixtures is that the response is based on the concentrationand number of double bonds. MS detectors are useful becausethey can also provide structural information.

Kinetic modelling has been used to investigate the esterifi-cation of FFAs to form biodiesel. In most cases a model system,with a single fatty acid is used and it has been found thatthe reaction follows a Ping Pong Bi Bi kinetic model (Al-Zuhairet al., 2006; Mahmud et al., 2010). A schematic of the Ping PongBi Bi mechanism for esterification is shown in Fig. 3 with anFFA first reacting with the enzyme to form a complex (E·FFA)leading to the formation of water. Methanol (MeOH) can thenreact with the surface to form the E·FAME and the FAME issubsequently released.

Three mechanisms were assessed for the transesterifi-cation of palm oil, using immobilised Pseudomonas sp. andethanol based on the variation of the TG, MG, DG, biodiesel andalcohol concentrations (Cheirsilp et al., 2008). Mechanism 1assumed hydrolysis followed by esterification with the overallreactions following a Ping Pong Bi Bi mechanism. Mechanism 2assumed that the complexes bound the enzyme surface reactfast and was a simplified version of Mechanism 1. Mechanism3 assumed that transesterification (direct alcoholysis) of thetriglycerides occurred in parallel with the hydrolysis esterifi-cation reaction sequence. The mechanism which best fittedthe experimental data was Mechanism 3.

This work has investigated the use of LC–MS to determinethe concentration of TG, DG and MGs in the reaction mixtureduring the esterification pre-treatment of UCO for the produc-tion of biodiesel. This data was subsequently analysed basedon the model proposed by Cheirsilp et al. (2008) for simulta-neous esterification and transesterification, i.e., Mechanism3. The aim of this work was to determine the componentsand reactions that contribute to the additional FAME forma-tion during the esterification pre-treatment of UCO for the

Fig. 3 – Schematic representation of the Ping Pong Bi Bimechanism for esterification of UCO.

chemical engineering research and design 9 2 ( 2 0 1 4 ) 713–719 715

production of biodiesel using Novozyme 435 and develop anovel model to describe the reactions.

2. Experimental

2.1. Materials

Methyl ester, mono-, di- and triglyceride standards werepurchased from Aldrich, UK. Novozyme 435 was donatedby Novozyme UK Ltd. and used as supplied. The UCO wassupplied by GreenFuel Oil Co., Ltd., UK and had an aver-age molecular weight of 278 g mol−1 and FFAs content ofapproximately 6.4 wt%. Analytical grade methanol, tolueneand 2-propanol were purchased from Fisher Scientific UK Ltd.HPLC grade 2-propanol and acetonitrile were used for the HPLCwork and purchased from Fisher Scientific UK Ltd. All solventswere used as supplied.

2.2. Esterification of UCO

The esterification reactions were carried out using a jacketedbatch reactor with a reflux condenser. The stirrer motor was aEurostar Digital IKA-Werke. The temperature was monitoredby means of a Digitron, 2751-K thermocouple and this infor-mation was used to set the temperature on the Techne, TE-10DTempette water bath. The UCO and methanol were addedto the reactor and heated to the required temperature, aftersampling, the catalyst was added to initiate the esterifica-tion reaction. The sample tube was fitted with metal gauze toprevent withdrawal of catalyst when taking samples and thesamples were withdrawn by means of a syringe. All sampleswere analysed for FFAs, FAME, MG, DG and TG concentrations.

2.3. FAME and FFA analysis

FAME concentration was determined using gaschromatography–mass spectrometry (GC–MS) (HewlettPackard HP-6890), equipped with a DB-WAX (J & W Scientific)capillary column (30 m × 0.25 mm) packed with polyethyleneglycol (0.25 �m film thickness); helium gas at a flow rate of1.1 mL min−1 was used as the carrier gas. The amount ofsample injected was 2 �L. The temperature of the injectorand detector was 250 ◦C. The initial oven temperature of70 ◦C was held for 2 min, then increased at 40 ◦C min−1 up to210 ◦C, then increased at 7 ◦C min−1 up to 230 ◦C and the finaltemperature was held for 11 min. Methyl heptadecanoate wasused as the internal standard.

The %FFAs in all samples was determined by titration usingthe ASTM D974 method. 2 g of sample was dissolved in 100 mLof a solution of toluene:2-propanol:water (volume ratio of100:99:1) and titrated using p-naphtholbenzein as an indicator.

2.4. Details of the Ultra performance liquidchromatography–mass spectrometry (UPLC–MS) method

The LC–MS was carried out using a Waters Acquity ultra per-formance liquid chromatography (UPLC) system interfaced toa Waters Synapt HDMS quadrupole time-of-flight (TOF) massspectrometer, using an electrospray ionisation source oper-ating in the positive ion mode. A Phenomenex Kinetix C18UPLC column (150 mm × 2.1 mm × 2.1 �m) was used for theseparation. The chromatography used a binary method withacetonitrile as solvent A and 2-propanol as solvent B. The sep-aration was carried out using a binary gradient with a flow

Fig. 4 – Conceptual scheme of the reaction mechanisminvestigated.

rate of 0.15 mL min−1 starting with 90% acetonitrile and 10%2-propanol changing to 30% acetonitrile in 20 min.

3. Development of the model

The model used in this work was based on the model pro-posed by Cheirsilp et al. (2008), i.e., Mechanism 3. In order tosimplify the model it was assumed that the components canbe grouped together. It was also assumed that the inhibitionof the enzyme by alcohol followed the competitive inhibitionmodel. It has been shown that for the reaction conditionsinvestigated, there are no mass transfer limitations (Haighet al., 2013) and as a result this model applies to the intrinsicreaction kinetics.

It was found that the water (W) concentration increasedwhen using UCO and Novozyme 435 as the catalyst. Thisis because the FFAs initially present in UCO lead to theesterification reaction and water formation. In addition, itis not necessary to add water to the reaction mixture whenNovozyme 435 is used as the catalyst. As a result, the modelproposed by Cheirsilp et al. (2008) was amended to allow forwater formation and the resulting conceptual scheme for thereaction is shown in Fig. 4. According to this reaction scheme,the free enzyme (E) reacts with alcohol (Al), triglycerides (T),diglycerides (D), monoglycerides (M) and FFAs (F) to form theassociated complexes E·Al, E·T, E·D, E·M and E·F, respectively.The hydrolysis and esterification reactions are then expectedto occur in parallel with the E·T, E·D and E·M complexes reac-ting with W to form F or with Al to form esters (Es) eventuallyleading to the formation of glycerol (G).

The rate expressions have been developed by assum-ing that the hydrolysis and esterification reactions are ratelimiting and the resulting rate equations are:

d[T]dt

= −(VmT[W] + VeT[Al])[T][E∗] (1)

d[D]dt

= ((VmT[W] + VeT[Al])[T] − (VmD[W] + VeD[Al])[D])[E∗]

(2)

d[M]dt

= ((VmD[W] + VeD[Al])[D] − (VmM[W] + VeM[Al])[M])[E∗]

(3)

716 chemical engineering research and design 9 2 ( 2 0 1 4 ) 713–719

d[G]dt

= (VmM[W] + VeM[Al])[E∗] (4)

d[F]dt

= −d[W]dt

= ((VmT[T] + VmD[D] + VmM[M])[W] − VeEs[F][Al])[E∗] (5)

d[Es]dt

= −d[Al]dt

= (VeT[T] + VeD[D] + VeM[M] + VeEs[F])[Al][E∗]

(6)

where the [E*] is:

[E∗] = [ET]1 + KmT[T] + KmD[D] + KmM[M] + KmF[F] + (Al/KI)

(7)

VmT, VmD and VmM are the hydrolysis rate constants and aredefined as: VmT = k3k1/k2, VmD = k7k5/k6 and VmM = k11k9/k10.VeEs is the esterification rate constant and is defined asVeEs = k15k13/k14. VeT, VeD and VeM are the rate constantsfor transesterification and are defined as: VeT = k4k1/k2,VeD = k8k5/k6 and VeM = k12k9/k10. The equilibrium constantsKmT, KmD, KmM, KmF and the inhibition constant KI are definedas: KmT = k1/k2, KmD = k5/k6, KmM = k9/k10, KmF = k13/k14 andKI = k17/k16.

The unknown parameters were determined by fitting themodel equations to the batch experimental data using MAT-LAB.

4. Results and discussion

4.1. Results of the LCMS analysis

A typical chromatogram generated by LC–MS for UCO is shownin Fig. 5 using the base peak ion (BPI) setting. UCO is knownto consist of a mixture of various MG, DG and TGs, and as aresult the chromatogram for UCO has a large number of peaks.The analysis was carried out using a mass spectrometer and

Fig. 5 – A typical UPLC chromatogram of used cooking oil(UCO) using the base peak ion (BPI) setting. The insetshows the extracted ion chromatogram for the 1,2 and 1,3isomers of dioleoyl-glycerol which gives a sodiatedmolecular ion [M+Na]+ at m/z 643.5.

Fig. 6 – Selected ion LC–MS chromatograms showingdepletion of 1,3 positional isomer of dioleoyl-glycerol[M+Na]+ ion at m/z 643.5 and comparison with thedioleoyl-glycerol standard containing predominantly 1,3positional isomers.

therefore an extracted ion chromatogram for each species canbe generated based on the mass-to-charge (m/z) ratio. Eachcomponent has a positive charge due to the incorporation ofan environmental Na+ ion. The extracted ion chromatogramfor dioleoyl-glycerol is shown as an inset in Fig. 5.

UCO has a complex composition and in order to simplifythe method it has been assumed that each component of agiven species gives a similar mass spectrometric response.Two calibration standards were used for each of the MG, DGand TG species. It can be seen from the inset in Fig. 5 thatmany of the components form multiple peaks due to isomersand as a result the total area under all peaks for the relevantcomponent was used as the peak area.

It has been found that individual diglycerides can beseparated into two peaks corresponding to the 1,2 and 1,3 posi-tional isomers of the diglyceride. During the reaction thesepeaks disappear at different rates, an example of this is shownin Fig. 6. The peaks at two reaction times for dioleoyl-glycerolhave been compared to the 1,3 diolein standard which is com-posed predominantly of the 1,3 isomer. These data show thatthe second peak corresponds to the 1,2 isomer, and that thisisomer is transesterified preferentially over the 1,3 isomer bythe Novozyme 435 enzyme catalyst. A comparison of the con-centration of the two palmitoyl-oleoyl-glycerol isomers duringthe reaction is shown in Fig. 7. The concentration data hasbeen calculated for this species because there is better sep-aration of the isomers than dioleoyl-glycerol and it has been

Fig. 7 – A comparison of the rate of disappearance ofdiglyceride peaks (palmitoyl-oleoyl-glycerol at m/z 617.5).

chemical engineering research and design 9 2 ( 2 0 1 4 ) 713–719 717

Table 1 – Details of the composition of UCO.

Property Value

Fatty acid composition (wt%)Linoleic acid 43Oleic acid 36Palmitic acid 13Stearic acid 3.8Linolenic acid 3.6

Molar mass, average TGs (g mol−1) 867.4FFA (wt/wt%) 8.42Acid value (mg KOH g−1) 16.6TG concentration (%) 84DG concentration (%) 7.0MG concentration (%) 0.3

assumed that the isomers elute in the same order. An enzymecatalyst, Novozyme 435, is being used to catalyse the reactionand this data shows that this catalyst has some stereoselec-tivity. Enzymes have been investigated for the manufactureof biodiesel, but this data indicates that information on thefatty acid composition of a particular oil may not be sufficientto determine how well the enzyme will catalyse a particularreaction. The isomer composition can also determine the rateand extent of reaction.

4.2. Results of the batch experiments

A summary of the composition of the UCO used for theseexperiments is given in Table 1. A comparison of the FAMEformation compared to FFAs consumption at 50 ◦C usingNovozyme 435 as the esterification catalyst is shown in Fig. 8.A schematic of the esterification of FFAs to FAME for the pre-treatment of UCO is shown in Fig. 2. From this data it can beseen that the FAME formation exceeds the FFAs consumptionby a factor of approximately 2.

It has been proposed that the additional FAME forma-tion is due to transesterification side reactions and an overallschematic for the transesterification reaction is shown inFig. 1. This reaction proceeds in a stepwise manner with theTGs converted to DGs and the DGs converted to MGs. A com-parison of the change in concentration of MG, DG, TG, FAMEand FFAs is shown in Fig. 9. The MG concentration increasesslightly and then decreases, which is typical of a reactionintermediate. The DG concentration decreases steadily dur-ing the course of the reaction. At the end of the 6 h reactiontime most of the MG and DGs have been consumed and this

Fig. 8 – A Comparison of the FFAs consumption and FAMEformation using Novozyme 435 as the esterification catalystat 50 ◦C.

Fig. 9 – Change in the concentration of triglycerides (TG),diglycerides (DG), monoglycerides (MG), fatty acid methylesters (FAME/biodiesel) and fatty acids (FFAs) during thepretreatment of UCO for biodiesel production. Thisexperiment was carried out using Novozyme 435 as thecatalyst at 50 ◦C.

would account for the additional FAME formation. In contrastthe change in TG concentration is very small. Overall, thereis a slight decrease in the concentration of triglycerides. Thuswhile the TGs will react in the transesterification reaction, therate is much slower when compared to the transesterificationof MGs and DGs. This is consistent with previous experimentswhere it was found that when Novozyme 435 was used as atransesterification catalyst, the transesterification of triglyce-rides was the rate limiting step with no accumulation of MGor DGs during the reaction (Türkan and Kalay, 2006).

4.3. Kinetic modelling results

The differential equations (1)–(6) were solved by means of theMATLAB “ode23s” function. This was combined with the MAT-LAB “fminsearch” function to minimise the residual of thesum of squares, i.e., the difference between the experimen-tal and calculated values. A comparison of the experimentallydetermined concentrations compared to those predicted bythe model is shown in Fig. 10 for the MG, DG, TG and FAMEconcentrations. From Fig. 10 it can be seen that some of theconcentration data is scattered particularly the TG and FAMEconcentrations. Overall the data followed a reasonable trendand as a result the scatter has been attributed to experimentalerror. These experiments have been repeated and the overallresults are reproducible. In the case of the UPLC work a qualitycontrol sample was injected periodically during the run andthis confirmed that the instrument performance remainedconsistent. There is a reasonable fit between the model andthe experimental data.

In the case of DG concentrations it can be seen that themodel predicts a faster initial decrease in the concentrationthan the experimental data. One of the assumptions made aspart of the model development was that all the DG speciescould be treated as a single component. However, it can beseen from Figs. 6 and 7 that the 1,2 and 1,3 positional isomersreact at different rates and the DG trend is the sum of thesetwo trends. The model could be improved by allowing for bothDG isomers, however, this would increase the complexity ofthe model and substantially increase the complexity of thecomponent analysis.

The parameters predicted by the model for this system areshown in Table 2. These values have been compared to values

718 chemical engineering research and design 9 2 ( 2 0 1 4 ) 713–719

Fig. 10 – A comparison of the concentrations from theexperiments compared to those predicted by the modelwith (a) the MG, DG and TG concentrations and (b) showingthe FAME concentrations.

found in the literature (Cheirsilp et al., 2008). From this datait can be seen that there are substantial differences betweenthese values, as expected, because the systems investigatedare different. Novozyme 435 was used instead of immobilisedPseudomonas sp., methanol was used in place of ethanol, waterwas not added to the reaction mixture and the model has beenmodified to allow for water formation during the esterificationreaction. Novozyme 435 is known to result in slow reactionswith TGs (Tongboriboon et al., 2010; Ganesan et al., 2009) andthe parameters for the TG reactions (VmT and VeT) are lower

Table 2 – The model parameters.

Parameters Predicted values(mol−1 min−1)

Literature valuesa

(mol−1 min−1)

VmT 0.0130 1.27VmD 0.447 1.35VmM 78.6 3.25VeEs 48.4 23.1VeT 0.00430 45.9VeD 25.5 19.6VeM 18.5 16.1KmT 0.00770 0.482KmD 0.00290 0.387KmM 3.92 0.329KmF 0.00410 0.187KI 764 14.7

Key experimental parameters

Catalyst type Novozyme 435 Pseudomonas sp.Reagent Methanol EthanolWater addition No Yes

a Cheirsilp et al. (2008).

than the literature values. From this data it can be seen thatthe DGs and MGs react more readily than the TGs. As expectedthe parameter of the esterification of FFAs (Ves) is greater thanthe literature value because Novozyme 435 has been shown tofavour the esterification reaction (Tongboriboon et al., 2010).Overall the data indicates that Novozyme 435 can catalysethe transesterification reaction in parallel with the hydroly-sis esterification reaction sequence. The value for the alcoholinhibition constant (KI) is greater than the literature value andthis can be accounted for because methanol was used insteadof ethanol. The two catalysts exhibit different levels of alcoholtolerance.

5. Conclusions

The pre-treatment of UCO, with Novozyme 435 as a catalyst,for the preparation of biodiesel has been investigated usingLC–MS to monitor the mono-, di- and triglyceride concentra-tions with kinetic modelling to assess the mechanism. It hasbeen shown that the LC–MS method has sufficient sensitivityto monitor the progress of specific isomers with the 1,3 DGisomers being consumed faster than the 1,2 isomer.

This work was carried out because earlier experimentsfocused on the esterification pre-treatment of UCO to formbiodiesel showed that there was an excessive formation ofFAME at high temperatures. From the MG, DG and TG datait can be seen that the MGs and DGs are consumed duringthe reaction while the TG concentrations decreases slightly.Cheirsilp et al. (2008) proposed that enzyme catalysed reac-tions proceed with transesterification in parallel with thehydrolysis esterification sequence of reactions. The model wasamended to allow for water formation and it was found thatthere was a good fit between the model and the experimentalresults. These results show Novozyme 435 can simultaneouslycatalyse the hydrolysis, esterification and transesterificationreactions in UCO.

Novozyme 435 has been investigated as an esterificationpre-treatment catalyst for the production of biodiesel. How-ever, these results indicate that alternative uses of Novozyme435 during biodiesel production may be more suitable. Enzymecatalysts are less sensitive to FFAs compared to their chem-ical counterparts. As a result, enzymatic transesterificationcould be carried out first followed by a simultaneous esteri-fication and transesterification reaction using Novozyme 435.This process could be used to ensure that all FFAs as well asunreacted MGs and DGs are removed from the product stream.

Acknowledgements

We would like to thank EPSRC for the PhD scholarship to KH.We would also like to thank GreenFuel Oil Co., Ltd., UK forsupplying the UCO and Novozymes UK Ltd. (Dr. David Cowan)for supplying the enzyme catalyst and his help and advicewith using Novozyme 435 for this project.

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