Optimization of Conversion of Waste Cooking Oil Into Biodiesel

Optimisation of Conversion of Waste Cooking Oil into Biodiesel

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CHEN XIAOMING, DR. DAVE WATSON, LORRAINE ALLEN, DR. WEI

LIANGQIAN, ZHANG TONG, WILMA WILSON, STEVE STEER, NORMAN

MACIVER.

Strathclyde Institute of Pharmacy and Biomedical Sciences, University of Strathclyde,

The John Arbuthnott Building, 27 Taylor Street, Glasgow, G4 0NR, Scotland.

[email protected]

Optimisation of the

Conversion of Waste Cooking Oil

into Biodiesel


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Acknowledgements

The author wishes to acknowledge Strathclyde Institute of Pharmacy and Biomedical

Sciences of the University of Strathclyde for financial and technical support.

Also Blue Apple Biodiesel Company for the supply of waste cooking oil as well as

biodiesel samples which were used as the control group.


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Contents

Abstract……………………..……………………………………………… page 6

Introductory…………….…………….……………………………………. page 8

1． Literature review…….………………………………………………….…page 8

1.1 biodiesel history…….………………………………………………….…. page 8

1.2 Concise Documentary Research of Biodiesel from 1937 till Present….…. page 8

1.3 Environmental, Economical and Political Views on Biodiesel Production.page12

1.4 Feedstock for Biodiesel Production………………………….……………page 13

2. Physiochemical Properties of Biodiesel………………………….……….. page 15

2.1 Why Biodiesel can be used as Surrogate Fuel for Diesel Engines……….. page 15

2.2 Four Methods to Derivatize Vegetable Oils into Biodiesel……………….page 16

2.3 What is Transesterification? ……………………………………………... page 17

2.4 Advantages and Limitations of both Virgin Vegetable Oils and Waste Cooking Oils

in Transesterification Biodiesel Production…………………………………...page 20

3. Method and Process used in the Optimization of this Biodiesel Production

Project…………………………………………………………………………page 20

4. Brief Introduction of Technology and Equipment Involved………………. page 22

5. Brief Introduction of Purpose and Objective of Biodiesel Production Optimization

Project - Why GC and Relative Viscosity and other Parameters are chosen to Evaluate

the quality of Biodiesel Batches……………………………………………… page 23

Material and Methods…………………………………………………... page 25

1． Materials …………………………………………………………………. page 25

2． Equipment………………………………………………………………… page 26


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2.1 Gas chromatography……………………………………………………… page 26

2.2 IR spectrometry …………………………………………………………. page 26

2.3 Other equipment………………………………………………………….. page 26

3． Sample preprocessing… ………………………………………………….page 27

4． Determination of Acid Value… ………………………………………….page 27

5．Preparation of Biodiesel………………………………………………….. page 28

5.1 First stage: acid esterification……………………………………………. page 28

5.2 Sodium methoxide preparation………………………………………….. page 30

6. Methanol recovery………………………………………………………… page 31

7. Separation ………………………………………………………………… page 32

8. Option: washing…………………………………………………………... page 33

9. Viscosity tests……………………………………………………………... page 33

10. Cloud point tests…………………………………………………………. page 34

11. Results and Discussion…………………………………………………... page 35

11.1 Methodologies for Biodiesel Production……………………………….. page 34

11.2 Safety…………………………………………………………………….page 36

11.3 Optimisation of Biodiesel Production…………………………………...page 37

11.4 GC analysis………………………………………………………………page 37

11.5 IR tests… ………………………………………………………………..page 40

Results and Discussion ………………………………………………. page 41

1．Description of Biodiesel and its Quality Standards……………………… page 41

2．Acid value Determination………………………………………………... page 43

3．Cloud point………………………………………………………………. page 44


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4．Relative viscosity……………………………………………………..… page 47

5．GC experiments………………………………………………………… page 51

5.1 Calibration curves and equations for the three methyl esters…………... page 52

5.2 The calibration equations generated by Excel above were used to calculate the

concentration of each of biodiesel sample and concentration data are listed in the tables

below ………………………………………………………………………. page 56

6 IR experiment……………………………………………………………. page 68

7 Excess methanol evaporation… ………………………………………….page 71

8. Results evaluation of optimized method of biodiesel production ……….page 72

Conclusion……………………………………………………………… page 74

Optimized method of biodiesel production using waste cooking oil was achieved and is

as follows: ……………………………………………………………….… page 75

References……………………………………………………………… page 77


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Abstract

Waste cooking oil with high free fatty acid content was used as the feedstock for

laboratory biodiesel production. In the optimised production method acidic value was

measured using the BP method before water was removed by heating it to 35°C and

then leaving it to settle.

The conversion of the free fatty acid and triglyceride into methyl esters was performed

in two stages:

1. The first stage was acidic esterification. Between 0.5 and 1.0% of free fatty

acid by weight of sulphuric acid was used as an acidic catalyst. Between 1:15

and 1:30 molar ratio of free fatty acid and methanol was mixed and heated to

finish the acidic esterification stage. The free fatty acid was converted to

methyl esters.

2. The second stage was basic transesterification. From 0.5 to 1.5% of

triglyceride by weight of sodium hydroxide was used as a basic catalyst.

Between 1:6 and 1:10 molar ratio of triglyceride was mixed with methanol,

stirred and heated to accomplish the basic transesterification stage. The

triglyceride was transformed into glycerol and methyl esters.

The amounts of sulphuric acid, sodium hydroxide and methanol were variables which

were controlled in examining the conversion rate of methyl esters. The optimized

method was obtained by monitoring the concentrations of total methyl esters in the

biodiesel samples. Viscosity and cloud point were important properties of the

biodiesel which were studied and evaluated.


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The optimized method of biodiesel production using waste cooking oil was realised by

using biodiesel samples from a local company as the control group and comparing

them to lab biodiesel samples. Minitab's 2 samples t test was used as the statistic

method to evaluate the important properties of cloud point, relative viscosity and

methyl esters concentration.


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Introduction

1． Literature review

1.1 Biodiesel History

Biodiesel vegetable oils, animal fats and used cooking oil; mostly including

triglycerides and free fatty acid and other small amounts of impurities [5].

Historically, since the diesel engine inventor Rudolf Diesel [4] used peanut oil as his

machine’s first fuel supply, there have been many trials to use plant oils as biofuel

notably during World War II. In some countries vegetable oils were used as

emergency fuels during times of energy supply shortages. There is documentary

recording that biodiesel transesterification technology experimentation was first

conducted as early as 1853 by scientists E. Duffy and J. Patrick [4], many years before

Rudolf’s diesel engine became functional.

1.2 Concise Documentary Research of Biodiesel from 1937 till

Present

The first public recognition of transesterification technology became a patent asset on

31st August 1937 when G. Chavanne of the University of Brussels (Belgium) [4] was

granted a patent licence for the alcoholysis (aka transesterification) of vegetable oils

using ethanol or methanol with the purpose of separating the fatty acids from the

glycerol by means of replacing the glycerol with short linear alcohols. It was the

earliest account of the production as well as the terminology “biodiesel”.

The petroleum crisis of the 1970s was the first point in time when energy prices hit the

global economy and this phenomenon was repeated in the early 1990s and again in the

present day. [10] On 17th

June 2008 oil prices soared to over 140 US dollars per barrel


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and look set to injure the global economy by triggering significant food inflation and

the resultant poverty to vulnerable sways of the populace.

More recently, in 1982 during the oil embargo on South Africa, it was reported in

Brazil that Caterpillar had made use of a 10% mix of vegetable oils along with 90%

traditional diesel to maintain the performance of engines without alteration or

adjustment [22].

In 1983 rapeseed oil was studied as a contemporary alternative to diesel fuel due to its

high yield of oil (45%). [20]. A blend of 25% sunflower oil and 75% of fossil diesel

was then tested in 1986. [21]

Schwab et al. used safflower oil as biodiesel in 1988 using pyrolysis technology; the

components produced being determined by GC-MS [23]. Copra oil and palm oil were

cracked with SiO2/Al2O3 as catalysts in experimentation in the course of 1993 [19].

Beef tallow was tested as a source to make biodiesel using transesterification with

methanol in 1994 [24]. Jackson and King reported a direct metholysis of triglycerides

using an immobilized lipase in flowing supercritical carbon dioxide with corn oil as the

source in 1996[31].

Using enzymes as catalysts to alcoholise soybean oil with methanol and ethanol was

investigated commercially by Bernardes [25].

Japan, as a country, has a scarcity of oil and other resources and Japanese scientists are

therefore enthusiastic to pursue alternative technology in order to solve this problem.

Enzymatic alcoholisation is relatively well developed in Japan. It is considered that

enzymatic alcoholisation is an effective and clean technology for transesterifying

vegetable oils into biodiesel. The water and free fatty acids contents do not greatly

affect the soap formation which is a negative factor in the viscosity of biodiesel. This

is however still too costly for the commercial energy market.


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Many other different vegetable oils and feedstocks have been explored by scientists as

sources to make biodiesel. Mustafa Balat et al., [3] 2008 compiled a clear and well

organized table to describe different vegetables main FFA contents in “Energy

Conversion and Management” magazine in March 2008 as shown in table 1:

Table 1: Fatty acid composition of some vegetable oils (%) [3]

Vegetable oil Palmitic

16:0

Stearic

18:0

Palmitoleic

16:1

Oleic

18:1

Linolei

c 18:2

Ricinic 12-

OH-oleic

Other

acids

Tallow 29.0 24.5 - 44.5 - - -

Coconut oil 5.0 3.0 - 6.0 - - 65.0

Olive oil 14.6 - - 75.4 10.0 - -

Groundnut oil 8.5 6.0 - 51.6 26.0 - -

Cotton oil 28.6 0.9 0.1 13.0 57.2 - 0.02

Corn oil 6.0 2.0 - 44.0 48.0 - -

Soybean oil 11.0 2.0 - 20.0 64.0 - 3.0

Hazelnut kernel 4.9 2.6 0.2 81.4 10.5 - 0.3

Poppy seed 12.6 4.0 0.1 22.3 60.2 - 0.8

Rapeseed 3.5 0.9 0.1 54.1 22.3 - 9.1

Safflower seed 7.3 1.9 0.1 13.5 77.0 - 0.2

Sunflower seed 6.4 2.9 0.1 17.7 72.8 - 0.1

Castor oil - 3.0 3.0 3.0 1.2 89.5 0.3

Investigating vegetable oils to make biodiesel has been pursued for almost a century

now and the first actual use of biodiesel was reported in 1937 in the Belgian Congo.

Chavanne, made ethyl ester of palm oil using acid as a catalyst. However since the

first energy crisis came to the media’s attention in late 1970s more considerable

research has been carried out on vegetable oils as diesel fuel. The first International

Conference on Plant and Vegetable Oils as fuels was organised in Gargo, North

Dakota in August 1982. The primary concerns discussed were the cost of making

biodiesel, the effects of biodiesel on engine performance & durability and biodiesel


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preparation specifications and additives. Oil production, oilseed processing and

extraction were also discussed at that meeting [26].

A diesel fleet was powered by filtered frying oil by Anon in 1982 when a mix of 95%

used cooking oil and 5% diesel fuel were tested. Records show that there were no

coking or carbon build-up problems with the engines except that the lubricating oil

became contaminated. The researchers later concluded that it was beneficial to change

the lubrication oil every 4,000 - 4,500 miles.

There have been more recent experiments of biodiesel usage in diesel engines. In 1983,

degummed and dewaxed sunflower oils were tested using a single cylinder pre-

combustion chamber engine [27]. The long term performance was monitored using a

fuel blend of 75% unrefined mechanically expelled soybean oil and 25% diesel fuel

but this failed after 90 hours of engine run due to a 670% increase in the lubricating oil

viscosity [28]. Schelick et al. evaluated a 2.59 L, 3 cylinder 2600 series Ford diesel

engine’s performance with soybean and sunflower oil mixed with number 2 diesel at

the ratio of 25:75 by volume; the engine worked constantly throughout the 200 hour

assessment. However carbon deposits on all combustion chamber parts were recorded

as overly high and so prohibited the use of this blend of diesel fuel. Soybean oil was

thermally decomposed and distilled in air and nitrogen sparged with standard ASTM

distillation equipment to lower the viscosity [23]. Still later, a new catalytic procedure

for the cracking of vegetable oils to produce biodiesel fuels was studied [19].

There has been considerable development of more advanced technology and theories in

biodiesel production although most of this has been used for commercial purposes.

Biodiesel production has increasingly and has steadily been promoted since the early

1990s as a means to respond to the fast growing levels of energy demand. With the


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price of petroleum repeatedly hitting historical highs this year biodiesel production,

technology and research will become more important around the world.

Yet in real commercial practice there are still huge barriers to biodiesel technology for

practical use. Almost all the experiments and commercial production show that the

cost of biodiesel is between 1½ and four times the cost of conventional diesel. The

main barrier is the expense of the plant oils which normally account for 65 - 90% of

the overall cost of biodiesel production. Mounting food price inflation will only add to

the outlay of making biodiesel with virgin vegetable oils.

In recent years many researchers have employed different approaches to reduce the

cost of sources used to make biodiesel and seek alternatives to virgin plant oils. In

Germany, due to recycling laws and regulations, it is relatively cheap and efficient to

make biodiesel with waste cooking oils. This approach hugely cuts the cost in making

biodiesel. Some research papers claim that using waste cooking oil could cut the price

from 75% of the total cost down to around 20%. In America there are some recycling

companies which collect and process waste cooking oil and they classify this oil as

yellow grease and brown grease based loosely on how much FFA it contains. These

companies then sell it on to customers including biodiesel production companies

according to sundry pricing policies.

Leandro et al. in 2007 [11] produced some research on using defective coffee beans in

labs as a cheap source to make biodiesel and this technology may be worthy of further

consideration in coffee producing nations. For Europe it is not a practical or

commercial proposition.


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1.3 Environmental, Economical and Political Views on Biodiesel

Production

Another growing concern is the effect of greenhouse gases on the environment in

recent decades and this places the biodiesel business in an encouraging position for

many environmental friendly policies, countries and industries. Efforts have been

stepped up to develop biodiesel technology in relation to tax policy etc.

Biodiesel production is highest in the EU according to the European Biodiesel Board

(EBB), [12]. Germany is the prime mover with over 50% of the total EU production

[13]. Brazil and United States are another two important players in the biodiesel

industry. Two factors have led the EU to become the world leader in biodiesel

production; [14]. One is the reform of the Common Agricultural Policy (CAP), a

supranational and domestically oriented farm policy for EU member countries, adopted

in 1992 and implemented in 1993-1994[15]. The second factor is high fuel taxes which

have enabled indirect subsidies for biofuel production through limited or full

exemption of the fuel excise tax. In February 1994 the European Parliament adopted a

90% tax exemption for biodiesel [15].

1.4 Feedstock for Biodiesel Production

Biodiesel can be made of renewable feedstock and it is a cleaner, environmentally

friendlier replacement fuel for conventional diesel. Essentially biodiesel is made by

renewable sources such as new and or used vegetable oils (yellow grease), animal fats

(brown grease); sources which can be generated in large quantities annually. Various

studies show that fossil fuels might be depleted in the next 100 years at present


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consumption levels and many are pessimistic about the future availability of fossil fuel

lasting even that long.

Unlike the EU most biodiesel made in the United States is from virgin plant oils such

as rapeseed, sunflower seed and soybean. Rapeseed oil is probably the most widely

used source since it is planted extensively in farms in the United States and research

has shown that there is a low percentage of free fatty acid contained in rapeseed oil

which is a positive factor for producing good quality biodiesel. Some RBD (refined,

bleached and deodorized) [18] virgin plant oils are understood to contain less than

0.5% of free fatty acid and this makes it an ideal source for producing good quality

biodiesel. However, using virgin plant oils raises questions over food price inflation

and the impact on global hunger. Food price inflation leads to more expensive

production of biodiesel which, in turn, makes it difficult to compete with conventional

diesel on price to the detriment of the biodiesel business.

While the United States mainly uses virgin oils the European Union predominately

exploits used cooking oil and animal fats to make biodiesel. Reportedly Germany has

the largest biodiesel industry with an estimated 43% of the world’s production in 2006.

German production jumped from 1·67 to 2·66 million tons between 2005 and 2006

when it was estimated that 42% of the world’s total biodiesel production was

accounted for by the country [3]. Other EU countries have also significantly increased

production including France, Italy and the United Kingdom. There are EU laws and

regulations for classification and for collections of different recycled wastes and these

make it easier to collect cleaner used cooking oil which should contain less free fatty

acids. These regulations should make biodiesel production cheaper as well as

improving the quality of the final product. With improvements to production


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technology and tax exemption policies it is likely that biodiesel production will expand

considerably over the next 20 years.

Marine algae came to note as a biodiesel production source due primarily to their

economical farming cost and reduced competition with plant land thus lessening any

food inflation dilemma. As early as 1978, R.B.Johns. et al., P.D.Nichols investigated

fatty acid composition of ten marine algae from Australian waters [29]. It was reported

TLC, GC-MS technologies were used to separate and determine the free fatty acid

content after the treatment with H2S and appropriate work up conditions to convert

fatty acid to methyl esters. Donghui Song et al., investigated oil bearing microalgae

for biodiesel production and suggested in their conclusions that algae breeding farms

should strengthen their trade with oil refining companies[30]. These conclusions also

allude to further improvement of transgenic microalgae technology for biodiesel

production to integrate with methyl ester formation and extraction methods.

2. Physiochemical Properties of Biodiesel

2.1 Why Biodiesel can be used as Surrogate Fuel for Diesel Engines

Besides the economic advantages of biodiesel it is also rightly regarded as a greener

and cleaner fuel. Some research has been reported in the Biodiesel Production

magazine. In that report they concluded that biodiesel’s overall lifecycle emissions of

carbon dioxide (a major greenhouse gas) from biodiesel are 78% lower than from

petroleum diesel. Also, overall emissions of carbon monoxide were likewise reduced

by 35%. The study also found that biodiesel reduces the sulphur oxides (major

components of acid rain) which are 8% lower than from traditional diesel. Many other

variations were also reported for additional environmental benefits.


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However the most important physiochemical properties for biodiesel’s practical usage

as surrogate diesel energy is that their viscosity and energy efficiency ratios are

comparable to conventional diesel. So there is no need for modification to the diesel

engines in vehicles. However there are still a few barriers to using biodiesel as routine

transportation energy. One disadvantage is biodiesel’s higher cloud point compared to

diesel (whose cloud point is also higher than petroleum) so in cold climates biodiesel

might gel and interfere with the engine functioning. The other main drawback is that

biodiesel viscosity is higher than that of diesel so the tank injection of vehicles and

some other small parts might need to be maintained more regularly to reduce poor

functional performance.

2.2 Four Methods to Derivatize Vegetable Oils into Biodiesel

Considerable efforts have been made to develop derivatives of vegetable and animal

fat oils which approximate the physiochemical properties of conventional diesel. Most

vegetable and animal oils without proper derivatization would have much higher

viscosity than fossil diesel and this renders it impossible to use as fuel in diesel engines

without modification. The purpose of basic and acidic transesterification is to lower

the viscosity of the biodiesel production. In fact transesterification is one of the four

main methods to reduce the viscosity of vegetable oils. The other three major

derivatives of vegetable oils as diesel fuels have also been developed and studied.

a) Dilution: viscosity of vegetable oils can be lowered by blending with pure

ethanol; 25% of sunflower oil and 75% of diesel were blended as diesel [8].

b) Microemulsion: the formation of microemulsion is one of the four solutions for

solving high vegetable viscosity and gumming problems. It is quite a simple

method of blending various vegetable oils with conventional fuel to decrease

the viscosity of biodiesel [16].


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c) Pyrolysis: refers to chemical change caused by thermal energy in the presence

of air or nitrogen sparge. [9]. Thermal decomposition of triglycerides produces

the compounds of shorter chain alkanes, alkenes carboxylic acids etc, which

will diminish the viscosity of vegetable oil.

d) Transesterification (alcoholysis): is the reaction of vegetable oils or animal fats

with a short chain alcohol in order to derivatize the triglycerides and fatty acid

into esters. These contribute to the low viscosity property of derivatized

biodiesel. Alcoholysis can be carried out with or without a catalyst. In

catalytic transesterification acid base or enzyme catalysis is used to promote the

alcoholysis derivative reaction. Catalysts include sulphuric acid, hydrochloric

acid, sodium hydroxide, sodium methoxide, potassium hydroxide and Candida

Antarctica enzyme etc [17].

2.3 What is Transesterification?

The main components of biodiesel are free fatty acid methyl esters which are

derivatized from free fatty acids. The most common free fatty acids in soybean oil and

animal fats are palmitic(16:0), stearic, (18:0), oleic, (18:1), linoleic (18:2) and linolenic

(18:3). There is much less free fatty acid content in virgin vegetable oils and some

rapeseed oil contains less than 0.5%. The highest percentage of oil content in

vegetables is triglyceride; also termed as triolein. Free fatty acids and water content

are two major negative factors to producing good quality biodiesel as they promote

formation soaps and gels when employing basic catalysts. Manufacturers therefore

prefer to use virgin oil such as rapeseed to make biodiesel due to its consistent quality

and because only a single basic transesterification process is needed and it becomes

easier to control the biodiesel quality [2].


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The following equation - figure 1 - explains the basic transesterification process in

producing biodiesel using virgin vegetable oils:


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Figure 1: Basic transesterification equation

When making biodiesel from cooking oils or animal fats a major challenge is their

relative high content of free fatty acids which easily form soap and gel making

separation of the product and free fatty acids difficult. It can also have an effect on the

viscosity and conversion rate of biodiesel production.

For waste cooking oil to make biodiesel there is one more step needed after water

removal - either the free fatty acid is distilled or it is derivatized to methyl esters by

acidic esterification:

Figure 2: acidic esterification for equation


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Acidic esterification and basic transesterification are the main alcoholysis methods

which will be considered in this research paper.

2.4 Advantages and Limitations of both Virgin Vegetable Oils and

Waste Cooking Oils in Transesterification Biodiesel Production

Virgin vegetable oils are more widely used in biodiesel production because of their

comparative consistent quality compared to animal fat or waste cooking oil. Its

transesterification process mostly involves basic transesterification and it can be easily

designed as a continuous production process in industry. However a substantial barrier

is its high cost which leads to the biodiesel price of about 1.5 to 3 times that of fossil

diesel so making it less competitive compared to conventional diesel.

Animal fat and waste cooking oils seem more viable due to their meagre cost however

they contain more water and free fatty acid (some up to 50%) [1]which makes their

quality inconsistent. So more processes are needed to make an acceptable product.

Water has to be removed from feedstock, then acidic esterification is used to derivatize

free fatty acid to methyl esters, then basic transesterification is used to derivatize

triglycerides into methyl esters and glycerol. Feedstock such as waste cooking oil

quality is not consistent and may contain many other impurities which make this

biodiesel production process more complicated. It is virtually impossible to

continuously produce biodiesel in industry using low grade waste cooking oil as

feedstock. The quality control of this type of product is variable since it involves more

steps to transesterify the triglyceride and free fatty acid into methyl ester. This is a

proper method for batch to batch production in industry.


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3. Method and Processes used in the Optimization of this

Biodiesel Production Project

Although there are more complex steps in producing biodiesel from waste cooking oil

it is possible to improve the quality of the end product by optimizing the production

process. For a certain biodiesel company which has a stable feedstock supply it is

possible to design a standard operation procedure to control the quality of the biodiesel

production for a set period.

There has been little research published on the optimization of the biodiesel production

method for quality control in industrial practice. This is the main rationale in carrying

out this research.

A foolproof method to make good economic biodiesel with waste cooking oil was

published by Aleks Kac at this webpage link [1].

http://journeytoforever.org/biodiesel_aleksnew.html It was introduced by the author

and describes the following processes:

a) Water removal: heat the waste cooking oil to about 60 deg C in a settling tank

to remove the water in the feedstock oil

b) Acidic transesterification: use pure (99%+) methanol 8% by volume ratio with

oil, and mix with 1 ml of 95% H2SO4 by 1 litre of oil - heat and stir then let the

mixture sit overnight

c) Basic transesterification: mix 1 litre of oil with 2.6% v/m sodium methoxide

120ml. Heat to 55 deg C and stir then allow to settle

d) The reaction solution separates into two obvious layers. The top layer is

usually yellow or light brown colour methyl ester. The bottom layer is dark

brown colour and is mostly triglycerine with other minor components such as

salts soap etc.

http://journeytoforever.org/biodiesel_aleksnew.html


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e) Separate the different layers. Add 10% H3PO4 to warm water and wash the

biodiesel produced. Then settle for 24 hours until the biodiesel turns a light

yellow colour

f) Methanol recovery is introduced as well in this method as an option

4. Brief Introduction to Technology and Equipment Involved

The optimization process of this foolproof method to make biodiesel was designed to

be monitored by gas chromatography (GC). GC technology is particularly good at

separating free fatty acid esters because free fatty acids are volatile under the high

temperature oven and capillary column. GC has excellent separation power because of

the long narrow column. So, even with many impurities existing in the production

from waste cooking oil, it shows a clear narrow peak which is very accurate and is

advantageous when carrying out the quantification tests.

Infrared (IR) technology is also used to identify the different test batches and so

demonstrate that this foolproof method was basically reproducible.

The monitoring of free fatty acid value can be done before the acidic transesterification

process e.g. according to BP titration method and is helpful to calculate how much

H2SO4 is needed in the acidic estrification stage.


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5. Brief Introduction to Purpose and Objective of Biodiesel

Production Optimization Project - Why GC and Relative

Viscosity and other Parameters are chosen to Evaluate the

quality of Biodiesel Batches

As discussed earlier waste cooking oil feedstock is usually of inconsistent quality.

Batch production would be needed to control the quality of the final biodiesel product.

The aims and objectives of this research were to optimize this simple foolproof method

to make economically viable biodiesel and help to maintain consistency. Further

research can be carried out; a standard operating procedure (SOP) could be configured

for the biodiesel company’s production quality control.

In this research the biodiesel production method was mainly based on the one provided

by Aleks Kac at the link mentioned above. [1] However some reliable technology

sources were also referenced from Biodiesel Production Technology released by the

National Renewable Energy Laboratory operated for the U.S. Department of Energy

Office of Energy Efficiency and Renewable Energy. That report was published

between August 2002 and January 2004 by

J. Van Gerpen, B Shanks and R. Pruszko Iowa State University,

D. Clements Renewable Products Development Laboratory and

G. Knothe USDA/NCAUR [2]

During preparatory study using other research papers it was evident that several

variations were fundamental to optimise biodiesel production. These included the use

of different basic catalysts, molar ratio of methanol to oil and proper temperature

control.


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GC was run to compare the results of the various batches of biodiesel and some other

parameters were checked and monitored - including relative viscosity and IR

spectrometry. The purpose and objective of this project was to evaluate the

reproducibility of this batch biodiesel production method and to optimize it with some

practical changes within a practical cost range.

Methyl ester concentration and viscosity are two important parameters to evaluate the

biodiesel production samples in this method. The gas chromatography machine was

used with eight different methyl esters including palmitic, stearic, oleic, linoleic and

linolenic. The GC results of these standard methyl esters helped to identify the methyl

esters in the biodiesel batches. Standards also help to determine the concentration of

the methyl esters in the lab biodiesel. The concentration levels of methyl esters gave

an idea of the conversion rate of the waste cooking oil into methyl esters and by

comparing different batches it could be concluded which method was the optimized

one among those tested.

The relative viscosity of the different batches of biodiesel were tested and the results

measured against each other and also compared to the results from the Apple Fuels

biodiesel company samples. This company’s customer base is mainly taxi drivers who

are often concerned about engine performance when using the product. Viscosity is

one of the appropriate parameters to monitor the biodiesel quality.


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Material and Methods

1． Materials

Waste cooking oils were provided by the Apple Fuels biodiesel company of

Glasgow. These were obtained from local eateries such as fish & chip shops

and Chinese take away restaurants.

HPLC grade Methanol was provided by Fisher Scientific UK Ltd, Bishop

Meadow Road, Loughborough, Leicestershire LE11 5RG. Batch: 0872622

HPLC grade ethyl acetate and 95-98% sulphuric acid were provided by the

Sigma-Aldrich Company Ltd, The Old Brickyard New Road, Gillinghan SP8

4XT. Batch: 0884136.

Sodium hydroxide pellets and potassium hydroxide were provided by Fisher

Scientific, Hunter Boulevard, Magna Park, Lutterworth, Leicestershire LE17

4XN. Lot B277250831.

Methyl palmitate, methyl stearate, methyl oleate, methyl linoleate, methyl

linolenate, eicospentenoic acid methyl ester and methyl docosahexanoate were

provided by Sigma-Aldrich Company Ltd, The Old Brickyard New Road,

Gillinghan SP8 4XT.

99.5% of diethyl ether was provided by BDH Laboratory Supplies, Poole,

BH15 1TD. Lot. 1102029322.

99.5% alcohol was provided by VWR International, 201 rue Carnot-F-94126

Fontenay Sons, Bois, France. Batch No: 07c140532


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2． Equipment

2.1 Gas chromatography

Gas chromatography was carried out using a Hewlett Packard 5890 series II instrument

fitted with an AS800 autosampler and a FID detector. The instrument was fitted with a

Rtx Stabiliwax column 30 m x 0.25 mm i.d. x 0.25µm film (Thames Restek, UK).

The following GC conditions were used: Oven on equilibrium time: 0.5 min., injector

230 °C, detector 250 °C, FID detection frequency: 10 Hz, Runtime: 22 min. Oven

temperature: 160 °C. The carrier gas was helium.

Data was acquired with Chromquest software version 3.0.

2.2 IR Spectrometry:

A Jasco-4200 FTIR instrument was used (Jasco U.K.).

Samples were run using a diamond ATR attachment.

2.3 Other Equipment

A Mettiler Toledo AG 204 balance was used.

Samples were evaporated using a Buchi Rotavapor R-3000.

Heating blocks were provided by Corning Hot Plate and Bibby Sterilin Ltd.

A viscosity measuring U tube was from Volac Brand, serial no 5925 BS.U. M3.

Sonication was carried out using a Decon F5200 B sonic bath.

Flasks, magnet stirring bars and thermometer were provided by Strathclyde University

SIPBS lab 307


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3． Sample Preprocessing

After eliminating the solid non oil contaminants the waste oil was put in a deep V

shape settling flask and heated to a temperature of approximately 60 deg C which was

maintained for 30 minutes. This was then left to settle for 24 hours to allow the water

present in the sample to mass at the bottom of the flask. This action helped to

maximize the useful oil and 10% at the bottom of the flask was always discarded to

ensure there was no water contamination in the final feedstock oil.

4． Determination of Acid Value

The acid value of the waste cooking oil was determined in order to estimate the free

fatty acid content and give an idea of how much acid catalyst and methanol would be

needed to push the acid esterification chemical towards methyl ester production. In

earlier published research it was recommended that 0.5 - 1.5% (based on the weight of

free fatty acid in the oil) of pure (95-98%) sulphuric acid should be used as a catalyst.

Acid value titration method was used according to BP monograph. The method is

described here:

The acid value is the number of mg of potassium hydroxide required to

neutralise the free fatty acid in 1g of the substance when determined by the

following method, unless otherwise specified in the BP monograph. A portion

of the substance being examined (10g) and was mixed with 50 ml of a mixture

of equal volumes of ethanol (96%) and ether which had been neutralised with

0.1M potassium hydroxide VS using 0.5ml of phenolphthalein solution R1as

indicator. When the substance was completely dissolved it was titrated with

0.1M potassium hydroxide VS shaking constantly until a pink colour persisted

for at least 15 seconds.


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The acid value was calculated from the expression 5.610v/w where v was the

volume, in ml, of potassium hydroxide solution required and w was the weight,

in g of substance taken.

5．Preparation of Biodiesel

For each production batch of biodiesel in these experiments about 100ml of waste

cooking oil was used in a conical flask with a tight fitting stopper.

5.1 First Stage: Acid Esterification

Figure 3：Acidic esterification equation:

The waste oil was heated to 35 deg C on the laboratory heating block until all the

solids liquefied and the temperature was then maintained between 35 and 50 deg C.

Sulphuric acid (95 – 98%) was used in the batches at levels varying between 0.1ml and

0.3ml per100ml oil. In the opening few experiments the sulphuric acid was first added

to the oil but this technique scorched some of the oil and discoloured it to a dark brown.

Earlier research had suggested that this could reduce the catalytic function so, in later

experiments, the sulphuric acid was first mixed with methanol before adding to the

waste cooking oil. After adding the methanol / sulphuric acid solution to the waste

cooking oil magnetic stirring bars were used to mix the solvents until they became

murky. This was then heated to about 35 deg C for between 1 and 2 hours. Stirring

continued throughout this process and for a further hour before the mix was left to

settle overnight.


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In order to optimize this method the following variables were controlled and monitored

during the acidic esterification:

As recommended in earlier research papers the sulphuric acid catalyst in the

esterification stage was maintained at 0.5 to 1.5% of the free fatty content by weight as

determined the acid value equation according to the BP monograph.

It was suggested in previously published research papers that the methanol to oil molar

ratio was best between 10:1 to 40:1 and that 80ml of methanol was used per litre of oil.

However no mention was made of the amount of free fatty acid which might be

contained in the spent cooking oils which fluctuated a great deal due the varying

sources and qualities of the oils.

Other variables which could impinge on the outcome include heat and mixing. A

higher temperature or a faster stirring rate may push the acidic esterification equation

to convert free fatty acid to methyl ester.

Methanol can be absorbed through skin and can damage the eyes and clothing.

Evaporation of methanol could also affect the acidic esterification process as well as

polluting the laboratory atmosphere and causing harm to personnel. Care was

therefore taken to properly and securely fit the stopper to the flask.

95-98% sulphuric acid is a highly corrosive substance so protective glasses were worn

when carrying out these experiments and a running water source was nearby.

Great care was taken to steer clear of the heating blocks and the wearing of protective

latex gloves added to the precautions.


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5.2 Sodium methoxide preparation

a. Weigh 15.035g of sodium hydroxide and mix with 500ml of HPLC grade pure

methanol in a 500ml flask, then the ultra sonic bath was used to assist in the

dissolution sodium hydroxide in the methanol solvent for 30 minutes. The

concentration for this sodium methoxide stock solution was 30.1mg of sodium

hydroxide per ml of methanol.

b. Sodium hydroxide (20.06 g) was weighed and mixed with 500ml of HPLC

grade methanol in a 500 ml flask, and then ultra sonic was used to dissolve the

sodium hydroxide in the solvent for 30 minutes. Concentration for this sodium

methoxide stock solution was 40.1mg of sodium hydroxide per ml of methanol.

c. Sodium hydroxide (13.335 g) was weighed and mixed with 250ml of HPLC

grade pure methanol in a 250 ml flask, and then ultra sonic was used to dissolve

the sodium hydroxide in the solvent for 30 minutes. The concentration for this

sodium methoxide stock solution was 53.34mg of sodium hydroxide per ml of

methanol.

d. Potassium hydroxide (4.218g) was weighed and mixed with 100ml of HPLC

grade pure methanol in a 100 ml flask, and then ultra sonication was used to

dissolve the potassium hydroxide in the solvent for 30 minutes. The

concentration for this potassium methoxide stock solution was 42.18mg of

potassium hydroxide per ml of methanol.


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5.3 Second Stage: Basic Catalyzed Transesterification

Figure 4: basic transesterification equation

The following general procedure was used.

1) Each batch of oil mixture was heated to temperatures which were controlled

between 55 and 70 deg C for the whole of this basic transesterification stage.

2) Between 6 and 15 ml of alkali methoxide was added to each 100ml batch of

heated oil mixture which was stirred for 15 to 30 minutes.

3) Then another 6 to 15 ml of alkali methoxide was added and stirring continued

for another ½ to 2 hours using the same lowest speed of the magnetic stirring

bars to facilitate the settling of biodiesel and glycerine layers while settling.

6. Methanol Recovery

In order to keep the costs to a minimum it was decided to recover the un-reacted

methanol from the biodiesel. A Rotavapor R-3000 was used to evaporate the un-

reacted methanol and running water generated the vacuum condition in the pipe of the


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Rovac. Temperature was maintained at 55 deg C during the evaporation process and

the flask of biodiesel was rotated at a constant slow speed. Three lots of un-reacted

methanol were reclaimed taking between 20 and 30 minutes to finish each methanol

recovery process.

7. Separation

Following the basic transesterification process and any methanol evaporation the

resultant biodiesels were left to lie for at least 8 hours or, in the main, overnight.

Separation funnels were used to separate the top (methyl ester) and bottom (glycerol)

layers of the biodiesel samples. Two layers could clearly be seen in the successful

basic transesterified biodiesel samples. The top layer was mainly composed of free

fatty acid methyl esters. The bottom deposit was mostly made up of glycerol, salts,

soap, other impurities and excess methanol as it is a very polar compound i.e. it

partitions more with polar glycerol as opposed to the non-polar methyl esters. The

density of the methyl esters is less than the bottom glycerol and soap etc layer.

1ml of 10% phosphoric acid was added to one of the biodiesel samples in an attempt to

neutralize the excess basic catalyst in the oil. This was to facilitate the extraction of

the glycerol in the bottom layer for recycling purposes. This was not of significance in

this project as the quantities of the test samples were too small and made it impractical

to collect the glycerol from the bottom layer. There would also have been many

unknown impurities in the layer to complicate this proposition.


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8. Option: Washing

The top methyl ester layer was separated and removed from every production sample.

The water washing process was then used on some of the biodiesel batches. Only one

of the biodiesel samples was neutralised with 10% phosphoric acid as the original

method instructed because of the small volumes of the lab samples.

One part water was used with three parts of the top layer (methyl esters) biodiesel for

washing. Warm water was used to help combat formation of any solids as the cloud

points of the biodiesel samples are high

9. Viscosity Tests

After the washing process, a viscosity U tube was used to measure the relative

thickness of the biodiesel samples. A dropper was used to transfer each biodiesel test

sample to this U shaped tube which was filled to the same mark for each analysis. It

was then noted exactly how long it took for the sample to drop to a lower mark through

a capillary pipe connecting to the opposite side of the U tube. This time was the

quoted relative viscosity value. All the biodiesel samples were subject to this test and

the control group was a sample from the local Glasgow biodiesel company. The

shorter the time taken to drop to the low mark, the lesser the sample’s relative viscosity.

The viscosity U tube has similar characteristics to an hourglass so the resultant values

cannot be assumed to be absolute. Even so, care should be taken to make best use of

the resource. This can be achieved by standardising the fixing of the U tube at the

same position, in a regular temperature and, if possible, in the water bath tank. The

information obtained was relative data; used to compare the comparative viscosity of


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the different biodiesel samples. Absolute viscosity values are important international

standards for biodiesel quality and more precise testing apparatus is available for the

manufacturing situation.

10. Cloud Point Tests

Cloud point might reflect two important properties of biodiesel. A high cloud point

could be caused by too much saturated fatty acid methyl ester in biodiesel. It may

additionally be more stable in storage and have a reduced probability for oxidization.

However it invariably creates additional problems for many diesel engines. Larger

amounts of saturated fatty acid methyl esters in biodiesel raises the cloud point and it

can easily clog the diesel engine and injection cylinder resulting in a machine with

running problems. A relatively straightforward experiment was used to measure the

cloud point for this project. The biodiesel samples were moved to flasks which were

set in large beakers full of ice. A thermometer was used to monitor the point when

crystals of biodiesel formed and that temperature was recorded. There may be some

inaccuracy with this method of measuring the cloud point because the test was carried

out in a room without temperature control possibly leading to imprecise thermometer

readings.

Biodiesel samples from the local Glasgow biodiesel company were used as the control

group to compare the biodiesel samples made in batches of waste cooking oil in the

laboratory.


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11. Results and Discussion

11.1 Methodologies for Biodiesel Production

The basic production method for biodiesel using waste cooking oil was acquired from

the internet from the following link source:


Ten weeks of experiments were carried out with the objective to optimize biodiesel

production from waste cooking oil based on this particular method. Several important

variables were reviewed and monitored for the purpose of working out a definite and

reliable method to recycle the discarded cooking oil and provide functional biodiesel.

The spent cooking oils had been collected from various eateries, fish and chip shops,

Chinese restaurants etc. The waste oils had been pre-treated by basic filtering to

reduce contaminants.

The four different concentrations of sodium methoxide and potassium methoxide

solutions were prepared and completely dissolved then left to settle overnight before

their use for basic transesterification. The application of this alkali methoxide was

monitored as it was an important variable to control during the optimization of

biodiesel production.

Sodium methoxide (CH3ONa) was chosen ahead of sodium hydroxide (NaOH) and

methanol (CH3OH) for a number of reasons:

o It enhances and speeds up the basic transesterification

o It reduces the formation of soap and water during the reaction

o It is less likely to form the undesirable monoglycerides and diglycerides

o CH3O- (from CH3ONa) is the function group which attacks the ester moieties

in the glycerol molecule



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All of which result in a superior conversion rate of waste cooking oil to biodiesel.

11.2 Safety

Sodium hydroxide and potassium hydroxide pellets are highly caustic substances.

Methanol can be absorbed through the skin and is a serious contaminant to eyes

therefore a lab coat, gloves and protective glasses must be worn when preparing these

solutions as well as having a nearby running water supply.

11.3 Optimisation of Biodiesel Production

11.3.1 Acidic Esterification

On the day following acidic esterification:

Several variables were adjusted and monitored during each minor modification in order

to optimize the method. Experience gained from this experiment was that warm water

was beneficial for bathing the biodiesel oil before separating with the funnel. Because

there is too much saturated free fatty acid methyl esters in the oil samples the bottom

layer can easily become solid even at room temperature after settling for a long time.

It would be difficult to separate the top and bottom layers with the funnel once it partly

solidified. Both the top and bottom layers of each biodiesel sample were stored in

different labelled vials for further examination.

11.3.2 Temperature Variation

In some of the biodiesel production batches temperature was controlled in order to

optimize the method. However this could not be strictly and accurately managed due

to heating block limitations. Likewise in some production batches heating and stirring


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times were reviewed to optimize the biodiesel production. Results and observation

will be discussed later in this research paper.

11.3.3 Variation in the Basic Catalyst

Potassium methoxide was used in just one of the batch biodiesel production samples.

The processes using the potassium methoxide were exactly the same as for the sodium

methoxide basic transesterification method.

11.4 GC Analysis

Using GC 8 different free fatty acid methyl esters were identified according to their

retention time which was based on their molecular weight (table 2).

Table 2: Retention time of free fatty acid methyl esters:

Free fatty acid methyl ester Retention time (min)

Methyl palmitate 4.870

Methyl palmitoleic 5.193

Methyl stearate 7.515

Methyl oleate 7.820

Methyl linoleate 8.553

Methyl linolenate 9.620

Eicospentenoic acid methyl ester 14.013

Methyl docosahexanoate 18.092

Before testing any of the biodiesel samples a repeat (x5) injection of the same free fatty

acid methyl ester standard solution was run to test precision. Then a five point

calibration series of eight free fatty acid methyl esters mixed standard solution was also

run to test the reliability of the GC performance and accuracy. Microsoft Excel was

utilized to draw a calibration and generate the calibration equation.


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Gas chromatography was used to monitor the free fatty acid methyl ester concentration

of the biodiesel samples during the basic transesterification stage.

Small amounts of:

methanol,

methanol and sodium mixture, or

potassium hydrate and methanol mixture

were trickled into the mixture oil and the sample was then examined using the GC.

The major free fatty acid methyl esters peak areas were monitored in the GC

chromatogram. This monitoring finished at the point when there was no change in

peak area reading of the GC machine. It was assumed that the reaction reached its

peak conversion rate at that value.

Important variables were found to be:

the quantity of 95-98% sulphuric acid

different concentration of sodium methoxide

the quantity of methanol, and

different types of alkali methoxide

During the basic transesterification stage different batches of biodiesel production were

initially estimated by observation before proceeding to GC testing. There were a total

of 27 batches of biodiesel experiments. Three of these failed due to significant

amounts of soap and gel formation which made the biodiesel/glycerol layers difficult

to separate. The remaining 24 samples were seen with a clear liquid top layer which

indicated biodiesel since its density was lower than the bottom layer which contained

mostly glycerine, soap, salt and methanol.

Gas chromatography was used to monitor the method of optimizing biodiesel

production during the basic transesterification process. Several important variations


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such as methanol, sodium methoxide and temperature were reviewed and altered in

order to achieve a better conversion rate of biodiesel from waste cooking oil. After

each measured change of these variants every biodiesel sample was run with GC. Peak

areas of major methyl esters were collected and compared to previous runs until there

was no growth in the peak area value. This indicated that the conversion rate of waste

cooking oil to biodiesel had reached its peak.

There were 36 batches of biodiesel samples produced in this project. GC sequence

runs were used to monitor the optimization of the biodiesel production method.

Sequence runs were set up in every GC run through the GC machine operating

software ChromQuest version 3.0. The vial labels were double checked and

coordinated with the ChromQuest sequence run order control and the positions on the

GC injection panel.

As a standard operational procedure that a blank and the mixed methyl esters standard

solutions should be run prior to analysing every batch of biodiesel sample solution on

the GC machine. In this research project both mixed standard methyl esters solutions

and biodiesel sample solutions from the local biodiesel company were used as control

groups.

The mixed standard methyl esters solution was used to help identify the methyl esters

in the biodiesel samples based on their retention time under the same GC method and

conditions. A calibration series was also run for the purpose of quantification of the

methyl esters peak area.


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11.5 IR Tests

Biodiesel samples from the numerous experiments were tested using a Jasco-4200

FTIR with Pike Technologies MIRACLE IR machine. The samples were tested under

Diamond ATR condition and, since they were in liquid state, these tests were used to

identify the free fatty acid methyl esters. There was an inadequate amount of standard

free fatty acid methyl esters for IR test in this project so IR spectrometry of standard

methyl esters was acquired from the chemistry reference book Beilstein. The results

data was valuable in identifying the methyl esters.


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Result and Discussion

1．Description of Biodiesel and its Quality Standards

In the report published by National Renewable Energy Laboratory for the U.S.

Department of Energy (mentioned in the introduction) Biodiesel is defined as: a fuel

comprised of mono-alkyl esters of long chain fatty acids derived from vegetable oils or

animal fats, designated B100.

Biodiesel can be used as B100 which means pure 100% alcoholised mono alkyl esters

of long chain fatty acid. It can be blended with conventional diesel when a mix of 20%

biodiesel with 80% fossil diesel is termed B20. A combination of 5% biodiesel with

95% traditional diesel is B5 and so on.

The American Society for Testing and Materials is an international standards

organization which has set the property requirements, testing criteria and quality

control methods for biodiesel B100. This is known as ASTM6751 [2] and some of the

more relevant components for this paper are:

Flash point which is defined as the lowest temperature, corrected to a

barometric pressure of 101.3 kPa, at which application of an ignition sources

causes the vapours of a specimen to ignite under specific conditions in a test.

Water and sediment is a test which determines the volume of free water and

sediment in the middle distillate fuels having viscosities at 40 deg C in the

range 1.0 to 4.1 mm2/s and densities in the range of 700 to 900 kg/m3.

Sulphated ash is the residue remaining after a sample has been carbonized.


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The cetane number is a measure of the ignition performance of a diesel fuel

obtained by comparing it to reference fuels in a standardized engine test. It is a

measure of how easily the fuel will ignite in an engine.

Free glycerine is the glycerol present as molecular glycerol in the fuel.

The storage stability standard for B100 is still in the development stage within the

ASTM process.

The acid values of different feedstock sources were tested and, during this project, the

parameters below were monitored to evaluate the quality of the biodiesel lab batches,

30 batches consisting of 100ml of waste cooking oil were produced in the experiments.

27 batches produced biodiesel but 3 were unsuccessful due to excessive soap formation

and the resultant difficulty in separating the layers.

In the results and discussion section the biodiesel samples made in the lab were

labelled as:

1A, 1B, 1C, 1D,

2A, 2B,

3A, 3B,

4A, 4B, 4C,

5A, 5B,

6A, 6B, 6C, 6D,

7A,

8A, 8B, 8C, 8D, 8E,

9A, 9B, 9C, 9D and

10A


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The biodiesel samples from the local company and used as the control group were

labelled:

S1, S2. S3. S4 and S5.

2．Acid Value Determination

Acid values of the waste cooking oils were tested according to BP monograph. Most

of the batches were from the same oil source with the exception of those labelled 6A,

6B, 6C and 6D.

Table 3: Acid value for different sources of waste cooking oil

WCO sources 6A 6B 6C 6D Other Batches

Acid value 5.31 7.74 7.66 5.56 11.38

Weight (g) of free fatty

acid in 100g of oil

4 5.83 5.76 4.18 8.57

RSD =1% (only for other batch tests)

The acid values were percentages, by weight, of free fatty acid in the waste cooking oil

feedstock. This was a good indicator in calculating how much acidic catalyst was

needed in the acidic esterification stage. As suggested, by previous research, between

0.5% and 1.5% of the weight of the free fatty acid as amount of acidic catalyst was

used in the acidic esterification stage in the biodiesel production from used cooking oil.

It was important to calculate the free fatty acid content before the acidic esterification

stage because the waste cooking oil quality varied greatly from batch to batch.

Previous experiments showed up to 50% content of free fatty acid in the waste cooking


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oils. To reduce the possibility of failed biodiesel production the exact amount of acidic

catalyst needed for different feedstocks can be calculated based on acid value [1].

At this stage the correct amount of acidic catalyst, in proportion to the amount of free

fatty acid methyl esters, was crucial to optimising the production of quality biodiesel

by reducing the prospect of soap formation.

3．Cloud point

Cloud point: is the temperature at which a cloud of wax crystals first appears in a

liquid when it is cooled down under conditions prescribed in this test method. This

property is critical factor in cold weather performance of biodiesel engines.

Table 4: Cloud point of lab biodiesel batches (°C)

Batch 1A 1B 1C 1D 2A 2B 3A 3B 4A

Cloud point 11°C 12°C 11°C 12°C 12°C 12°C 11°C 12°C 11°C

Batch 4B 4C 5A 5B 6A 6B 6C 6D 7A


Batch 8A 8B 8C 8D 8E 9A 9B 9C 9D


Batch 10A S1 S2 S3 S4 S5

Cloud point 11°C 10°C 11°C 11°C 11°C 12°C

Table 5: Cloud point of lab biodiesel group classed into 3 groups (°C)

Cloud point 11°C 12°C 13°C

Number of batches 14 12 2

Proportion 1/28 4/28 4/28

Mean 11.57°C


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Table 6: Cloud point of controlled group classed into 3 groups (°C)

Cloud point 11°C 12°C 13°C

Number of batches 0 0 0

Promotion 0/5 0/5 0/5

Mean 11°C

Tables 5 and 6 above show that the mean value of the biodiesel batches cloud point

was slightly different from that of the local biodiesel company’s control group samples

How the cloud point of different groups of biodiesel would affect the performance of

diesel engines can be further tested in colder temperature condition. It is advisable to

conduct further experiments for biodiesel production quality control purposes.

Minitab statistical software was used to calculate the cloud points of the biodiesel

samples made in the lab and compare them with the control group samples from the

local Glasgow company. 2 sample t-test was run:

Figure 4: Boxplot of cloud point for two groups of biodiesel samples

cloud point Bcloud point C

13.0

12.5

12.0

11.5

11.0

10.5

10.0

Da

ta

Boxplot of cloud point C, cloud point B


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Figure 4 shows that the cloud points for both groups of biodiesel samples were

normally distributed.

Two-Sample T-Test and CI: cloud point lab Batches biodiesel, cloud point

Controlled group

Two-sample T for cloud point B Vs cloud point C

N Mean StDev SE Mean

Cloud point B 28 11.571 0.634 0.12

Cloud point C 5 11.000 0.707 0.32

Difference = mu (cloud point B) - mu (cloud point C)

Estimate for difference: 0.571

95% CI for difference: (-0.298, 1.441)

T-Test of difference = 0 (vs not =): T-Value = 1.69 P-Value = 0.152 DF = 5

Using the 5% level, the value of 2.571 was found in the t-table under column 0.025 and

across row DF=5. Since t=1.69 does lie in the range -2.571 to +2.571 we conclude that

the result was not significant. The mean cloud point of controlled group biodiesel

samples and lab batches biodiesel samples may well be the same.

The cloud points of two failed biodiesel samples were not tested as excessive soap

formation made it unfeasible to observe methyl esters crystallisation.

The cloud point experiments were controlled manually using constant equipment and

conditions. However there was room for uncontrolled errors such as variations in

room temperature, deviations in test times and system errors with the thermometer etc.

The number of unsaturated free fatty acid chains in the biodiesel should affect the

cloud point readings; the more unsaturated chain fatty acid esters in the biodiesel the

lower the cloud point. This was confirmed by the biodiesel samples from the local


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company whose gas chromatography results show a greater percentage of unsaturated

methyl stearate (18:1) compared to the other lab biodiesel production samples.

Waste cooking oil which has been heated to a high temperature has a higher proportion

by weight of polymers than virgin vegetable oil and this can affect the cloud point of

the final product; more polymers result in a higher cloud point. This is why 90% of

industrial biodiesel is manufactured from virgin vegetable oil and diesel from used

cooking oil cannot be used as B100 in engines below 13°C.

4．Relative Viscosity

A U tube was the equipment used to measure the relative viscosity. The time taken for

the biodiesel to drop to the same mark on the U tube was measured in minutes and

seconds as the measure of relative viscosity. Both the controlled group of biodiesel

samples and the lab biodiesel samples were measured.

This experiment’s readings were relative and not absolute values. The purpose of the

experiments was to compare the viscosity of both groups.

Table 7: Relative viscosity of biodiesel samples (unit: minutes and seconds)

Batch 1A 1B 1C 1D 2A 2B 3A 3B 4A

Relative viscosity 13’56” 12’26” 12’25” 12’03” 11’51” 12’35” 12’30” 14’06” 12’17”

Batch 4B 4C 5A 5B 6A 6B 6C 6D 7A

Relative viscosity 12’28” 11’34” 12’02” 13’16” 13’31” 11’35” 9’38” 9’23” 8’18”

Batch 8A 8B 8C 8D 8E 9A 9B 9C 9D

Relative viscosity 10’59” 10’58” 9’09” failed 10’23” 12’05” 11’15” 12’04 9’24”

Batch 10A S1 S2 S3 S4 S5

Relative viscosity 10’14” 12’39” 11’21” 13’03” 12’35” 11’57”


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Table 8: Relative viscosity of lab biodiesel samples classed into 7 groups

Relative viscosity 8’00”- 9’00”- 10’00”- 11’00”- 12’00”- 13’00”- 14’00”-

Number of batches 1 4 4 4 10 3 1

Proportion 1/27 4/27 4/27 4/27 10/27 3/27 1/27

Mean 11’34”

Table 9: Relative viscosity of control biodiesel samples classed into 7 groups

Relative viscosity 8’00”- 9’00”- 10’00”- 11’00”- 12’00”- 13’00”- 14’00”-

Number of batches 0 0 0 2 2 1 0

Proportion 0/5 0/5 0/5 2/5 2/5 1/5 0/5

Mean 12’19”

The relative viscosity data for both groups were analysed by Minitab

Figure 5: Boxplot of relative viscosity C, relative viscosity B

relative viscosity Brelative viscosity C

14

13

12

11

10

9

Da

ta

Boxplot of relative viscosity C, relative viscosity B


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It was suggested from the boxplot that the mean value of relative viscosity of biodiesel

batches produced in the lab was lower than the mean value of relative viscosity of

biodiesel samples provided by the local biodiesel company.

Figure 6: Probability Plot of relative viscosity C, relative viscosity B

1614121086

99

95

90

80

70

60

50

40

30

20

10

5

1

Data

Pe

rce

nt

12.16 0.6556 6 0.373 0.288

11.36 1.436 26 0.648 0.081

Mean StDev N AD P

relative v iscosity C

relative v iscosity B

Variable

Probability Plot of relative viscosity C, relative viscosity BNormal - 95% CI

The trend in the plot is roughly linear and most of the data lies within the confidence

interval so it can be reasonably accepted that normal distribution is valid.

Descriptive Statistics: relative viscosity C, relative viscosity B

Variable N N* Mean SE Mean StDev Minimum Q1 Median

Relative viscosity C 6 0 12.157 0.268 0.656 11.210 11.480 12.370

Relative viscosity B 26 0 11.357 0.282 1.436 8.780 10.208 11.765

Variable Q3 Maximum

Relative viscosity C 12.550 13.030

Relative viscosity B 12.265 14.060


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Two-sample T for relative viscosity C vs relative viscosity B


relative viscosity C 6 12.157 0.656 0.27

relative viscosity B 26 11.36 1.44 0.28

Difference = mu (relative viscosity C) - mu (relative viscosity B)

Estimate for difference: 0.799


T-Test of difference = 0 (vs not =): T-Value = 2.06 P-Value = 0.055 DF = 17

On close examination, using the 5% level, the value of 2.11 was found in the t-table

under column 0.025 and across row DF=17. Since t=2.06 does lie in the range -2.11 to

+2.11 we conclude that the result was not significant. The mean relative viscosities of

controlled group biodiesel samples and lab biodiesel samples may well be the same.

Based on the measured mean value it was clear that the lab biodiesel batches had

marginally better viscosity test results. A concern over the results from the local

biodiesel company samples was the relative small number of tests; more samples being

tested would have been helpful and, perhaps, more credible.

Viscosity of the biodiesel is closely related to the concentration of the methyl esters.

Higher levels of methyl esters concentration resulted in better conversion rates of used

cooking oil into biodiesel. Also, high content of unsaturated fatty acids in the biodiesel

lowered the viscosity. In some of the biodiesel samples excess methanol was not

evaporated; this might possibly reduce the relative viscosity reading as well. It is

commonly accepted that methanol is a very polar molecule so most of the excess

methanol would be partitioned to the bottom layer of glycerine instead of the top

methyl esters layer.


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The viscosity of biodiesel is also affected by the number of unsaturated free fatty acid

chains in the biodiesel; the more unsaturated free fatty acid chain in biodiesel the less

time for the relative viscosity measurement. In a small number of published research

apers another approach to monitoring the viscosity of biodiesel production samples

revealed the correlation between the conversion rate of biodiesel production using

waste cooking oil and its viscosity. Viscosity monitoring can play an important role in

industrial biodiesel production quality control.

5．Gas Chromatography (GC) Experiments

The type of methyl esters in used cooking oil derived biodiesel can fluctuate because

the quality of feedstock varies from batch to batch. There were also some polymer

triglycerides formed during high temperature cooking which were difficult to detect by

GC technology and impossible to identify without standard substances. Previous

research papers noted that these polymer forms of triglyceride can be hard to alcoholise

into alkyl esters. In every biodiesel sample tested with GC there were three peaks

identified by testing an 8 standard methyl esters mixture using the same GC method

according their retention time. Three identified methyl esters were methyl palmitate

(C16:0), methyl stearate (C18:0) and methyl oleate (C18:1). There were some other

small peaks present in the gas chromatogram but these were ignored as insignificant.

For the convenience of quantification only these three methyl esters concentrations

were determined and compared. These three peaks of methyl palmitate (C16:0),

methyl stearate (C18:0), and methyl oleate (C18:0) were monitored in GC and used to

evaluate the optimization method of the biodiesel production. The three peak area

readings were converted into concentrations with calibration curves prepared using


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methyl ester standards. When the concentrations of the three methyl esters were added

up their total value was assumed to indicate the degree of conversion of free fatty acid

and triglyceride into methyl esters. The concentrations from the controlled group were

compared with those of the lab .

The optimized method of biodiesel production using waste cooking oils was obtained

by monitoring the methyl esters’ peak area with GC runs. In order to get precise and

convincing results every biodiesel sample solution concentration prepared for GC was

within the range of the calibration curve. The biodiesel sample solutions were diluted

with HPLC grade ethyl acetate solvent before they were run in the GC machine.

Calibration equations were then used to determine the actual concentration of the

methyl esters in the biodiesel samples.

5.1 Calibration curves and equations for the three methyl esters

The calibration curves were plotted for the three methyl esters. They were found to be

linear over the range 0.25-1 mg/ml. The calibration curves are shown in figures 3-5

and the data used to plot the curves is given in tables 8-10.

5.1.1 Methyl palmitate (16:0) calibration equation

Table 10: Methyl palmitate peak area series data

Methyl palmitate retention time=4.870 min

concentration mg/ml peak area

0 0

0.25 169392

0.5 360903

0.7 466369

1 675233


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standard methyl stearate GC calibration y = 594587x + 3553.7

R2 = 0.995

0

100000

200000

300000

400000

500000

600000

700000

0 0.2 0.4 0.6 0.8 1 1.2

concentration

peak a

rea

Figure7: Methyl palmitate calibration curve and equation

5.1.2 Methyl stearate (18:0) calibration equation

Table 11: Methyl stearate peak area series data

Methyl stearate retention time=7.515min

concentration (mg/ml) peak area

0 0

0.25 142888

0.5 307278

0.7 444173

1 580167

Figure8: Methyl stearate calibration curve and equation


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5.1.3 Methyl stearate (18:0) calibration equation

Table 12: Methyl oleate peak area series data

Methyl oleate retention time=7.820min

concentration mg/ml peak area

0 0

0.25 155607

0.5 333262

0.7 428243

1 628933

Figure 9: Methyl oleate calibration curve and equation

standard methy oleate GC caliration y = 625704x + 2614

R2 = 0.9979

0

100000

200000

300000

400000

500000

600000

700000

0 0.2 0.4 0.6 0.8 1 1.2

concentration

peak a

rea


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Figure 10: Methyl esters standard gas chromatography (0.25mg/ml)

Figure 11: Methyl esters standard gas chromatography (0.7mg/ml)


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5.2 The calibration equations generated by Excel above were used

to calculate the concentration of each of biodiesel sample and

concentration data are listed in the tables below.

Table 13: Concentration of methyl esters of biodiesel samples from local company.

Concentration of sample analysed 1mg/ml.

Control Group

Biodiesel C16:0 (mg/ml) C18:0 (mg/ml) C18:1 (mg/ml) Total (mg/ml)

S1 0.0826 0.3203 0.2661 0.669

S2 0.0903 0.2545 0.3602 0.705

S3 0.0958 0.2658 0.3298 0.6914

S4 0.0845 0.3355 0.2907 0.7107

S5 0.0919 0.274 0.3196 0.6855

Figure 12: Biodiesel sample 1 (controlled group from local company) gas

chromatography (4.375mg/ml)


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Figure 13: Biodiesel sample 2 (controlled group from local company) gas

chromatography (5.86 mg/ml)


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Table 14: Concentration of methyl esters (1mg/ml) of lab biodiesel samples.

Lab Biodiesel Samples

Biodiesel C16:0 (mg/ml) C18:0 (mg/ml) C18:1 (mg/ml) Total (mg/ml)

1A 0.2544 0.2198 0.312 0.7862

1B 0.3175 0.2342 0.3277 0.8794

1C 0.261 0.2256 0.3201 0.8067

1D 0.209 0.1653 0.2502 0.6245

2A 0.2515 0.2159 0.2968 0.7642

2B 0.1825 0.1456 0.209 0.5371

3A 0.2365 0.2067 0.2871 0.7303

3B 0.227 0.1996 0.2739 0.7005

4A 0.2464 0.2114 0.2953 0.7531

4B 0.1259 0.1079 0.1543 0.3881

4C 0.2246 0.2027 0.2982 0.7255

5A 0.2533 0.2242 0.3134 0.7909

5B 0.1463 0.1218 0.1746 0.4427

6A 0.1983 0.198 0.3553 0.7516

6B 0.2346 0.2053 0.2712 0.7111

6C 0.3446 0.1089 0.337 0.7905

6D 0.356 0.1176 0.3075 0.7811

7A 0.2339 0.2006 0.2799 0.7144

8A 0.2384 0.1991 0.292 0.7295

8B 0.2394 0.2002 0.2934 0.733

8C 0.2479 0.2107 0.3071 0.7657

8D / / / /

8E 0.2484 0.2101 0.3088 0.7673

9A 0.2542 0.2179 0.3147 0.7868

9B 0.2349 0.2012 0.2911 0.7272

9C 0.2569 0.2145 0.3153 0.7867

9D 0.244 0.206 0.2991 0.7491

10A 0.2465 0.2051 0.3004 0.752


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Figure 14: Lab biodiesel sample 6A gas chromatography (2.705mg/ml)

Figure 15: Lab biodiesel sample 6B gas chromatography (2.705mg/ml)


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0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8c

o

n

c

e

n

t

r

a

t

i

o

n

acidic basic and optimized stage

methyl esters concentration

Acidic esterification stage 0.0053 0.0044 0.001 0.0107

Basic transesterification stage 0.0798 0.0662 0.0981 0.2441

Optimized stage 0.2625 0.2112 0.3025 0.7742

C 16:0(mg/ml) C 18:0(mg/ml) C 18:1(mg/ml) total(mg/ml)

All the concentrations of the three methyl esters were determined using the calibration

equation. Then concentration of the three methyl esters were summed and used for

comparison with other samples. It was evident that the amounts of 16:0 were higher in

the test batches which had high levels of free fatty acid. It was apparent that only 70-

80% of the composition of the oil could be accounted for by methyl esters. Both

mathematical and statistical methods were used to evaluate the optimized method of

biodiesel production with waste cooking oils.

The total concentrations of methyl esters were compared after the acidic esterification,

the basic transesterification and the optimized method stages.

Table 15: Concentration of methyl esters in different stages of biodiesel production

Methyl esters concentration (mg/ml) (mean value)

Batches C 16:0 C 18: C 18:1 Total RSD

Acidic esterification stage 0.0053 0.0044 0.001 0.0107 6.7%

Basic transesterification stage 0.0798 0.0662 0.0981 0.2441 2.8%

Optimized stage 0.2625 0.2112 0.3025 0.7742 3.2%

Figure 16: Concentration of methyl esters column chart


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The conversion rate of free fatty acid and triglycerides to methyl esters can be seen

from table 15 and figure 16 above. After each of the three stages of biodiesel

production all the samples were monitored with GC. These results demonstrate that

the optimized method had the highest conversion rate. There were only small amounts

of methyl esters created after the acidic esterification stage and the conversion rate of

methyl esters after the basic transesterification from the original method was also

unsatisfactory. This is deduced from the readings and more statistical evaluation will

be discussed later.

The relative conversion rate of methyl esters at the optimized stage was assumed to be

100%. Table 16 shows the conversation rate of the three stages.

Table 16: Relative conversion rate of methyl esters

3 batches Mean concentration of Total

methyl esters (mg/ml)

Relative conversation rate

Acidic esterification stage 0.0107 1.38%

Basic transesterification stage 0.2441 31.53%

Optimized stage 0.7742 100.00%

Table 17: Methyl esters concentration after the acidic esterification stage (group

labelled as conc1)

Biodiesel concentration

(16:0) mg/ml

concentration

(18:0) mg/ml

concentration

(18:1) mg/ml

concentration

mg/ml in total

A1 0.0058 0.0044 0.0103 0.0205

A2 0.0053 0.0044 0.0010 0.0107


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Table 18: methyl esters concentration after the basic transesterification stage (group

labeled as conc2)

Biodiesel concentration

(16:0) mg/ml

concentration

(18:0) mg/ml

concentration

(18:1) mg/ml

concentration

mg/ml in total

B1 0.0723 0.0600 0.0894 0.2217

B2 0.0873 0.0723 0.1068 0.2664

Table 19: Methyl esters concentration after optimized method stage (group labelled as

conc3)

Biodiesel Concentration

(16:0) mg/ml

Concentration

(18:0) mg/ml

Concentration

(18:1) mg/ml

Concentration

mg/ml in total

O1 0.2090 0.1653 0.2502 0.6245

O2 0.2312 0.1832 0.2669 0.6813

O3 0.2147 0.1721 0.2507 0.6375

O4 0.2273 0.1865 0.2689 0.6827

Minitab statistical software was used to evaluate the different groups of data above.

Two-Sample T-Test and CI: conc1, conc2

Two-sample T for conc1 vs conc2


conc1 2 0.01560 0.00693 0.0049

conc2 2 0.2441 0.0316 0.022

Difference = mu (conc1) - mu (conc2)

Estimate for difference: -0.2285


T-Test of difference = 0 (vs not =): T-Value = -9.98 P-Value = 0.064 DF = 1

Using the 5% level, the value of 12.706 was found in the t-table under column 0.025

and across row DF=1. Since t=-9.98 does lie in the range -12.706to +12.706 we


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conclude that the result was not significant. The mean concentration of methyl esters

of biodiesel samples after acidic esterification and biodiesel samples after the original

basic transesterification step may well be the same.




conc1 2 0.01560 0.00693 0.0049

conc3 4 0.6565 0.0299 0.015



95% CI for difference: (-0.6910, -0.5908)


Using the 5% level the value of 3.182 was found in the t-table under column 0.025 and

across row DF=1. Since t=-40.71 does not lie in the range -3.182 to +3.182 we

conclude that the result was significant. The mean concentration of methyl esters of

biodiesel samples after acidic esterification and biodiesel samples after optimized

method is not the same.




conc2 2 0.2441 0.0316 0.022

conc3 4 0.6565 0.0299 0.015






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Using the 5% level, the value of 12.076 was found in the t-table under column 0.025

and across row DF=1. Since t=-15.33 does not lie in the range -12.076 to +12.076 we


biodiesel samples after basic transesterification and biodiesel samples after optimized

method were not the same.


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Table 20: Total concentration of methyl esters of controlled group and lab biodiesel

group prepared by the optimised method

Controlled

group

Total methyl esters

concentration (mg/ml)

Lab biodiesel

group

Total methyl esters

concentration (mg/ml)

S1 0.669 1A 0.7862

S2 0.705 1B 0.8794

S3 0.6914 1C 0.8067

S4 0.7107 1D 0.6245

S5 0.6855 2A 0.7642

3A 0.7303

3B 0.7005

4A 0.7531

4C 0.7255

5A 0.7909

6A 0.7516

6B 0.7111

6C 0.7905

6D 0.7811

7A 0.7144

8A 0.7295

8B 0.733

8C 0.7657

8E 0.7673

9A 0.7868

9B 0.7272

9C 0.7867

9D 0.7491

10A 0.752

Minitab was used as statistic software to evaluate the two data groups in table 18.

Descriptive Statistics: controlled group, lab batches


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Variable N N* Mean SE Mean StDev Minimum Q1

Median

Controlled group 5 0 0.69232 0.00738 0.01651 0.66900 0.67725

0.69140

Lab batches 24 0 0.75447 0.00968 0.04743 0.62450 0.72778

0.75255

Variable Q3 Maximum

controlled group 0.70785 0.71070

lab batches 0.78658 0.87940

Figure 17: Boxplot of two groups of data

lab batchescontrolled group

0.90

0.85

0.80

0.75

0.70

0.65

0.60

Da

ta

Boxplot of controlled group, lab batches


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Figure 18: Probability Plot of controlled group, lab batches

0.900.850.800.750.700.650.60

99

95

90

80

70

60

50

40

30

20

10

5

1

Data

Pe

rce

nt

0.6923 0.01651 5 0.189 0.796

0.7545 0.04743 24 0.534 0.154

Mean StDev N AD P

controlled group

lab batches

Variable

Probability Plot of controlled group, lab batchesNormal - 95% CI

Both boxplot and probability plot of two groups showed the data was normally

distributed. 2 sample t-test was used to evaluate the lab experiment results.

Two-Sample T-Test and CI: controlled group, lab batches

Two-sample T for controlled group vs lab batches


Controlled group 5 0.6923 0.0165 0.0074

Lab batches 24 0.7545 0.0474 0.0097

Difference = mu (controlled group) - mu (lab batches)




Using the 5% level, the value of 2.093 was found in the t-table under column 0.025 and

across row DF=19. Since t=-5.11 does not lie in the range -2.093 to +2.093 we


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controlled group biodiesel samples and lab batches biodiesel samples was not the same;

the yield of methyl esters was higher in the batches prepared in the lab using the

optimised method.

6 IR Experiment

Every biodiesel sample was examined with the IR machine; the finger print region of

the IR spectrum was compared for each biodiesel sample. All the peaks of the bands in

the 900-1500cm-1 region were carefully checked and compared. They were very

similar between samples and along with the GC identification run based on standard

methyl esters, it is possible to be confident that these materials can be identified as the

same, namely; methyl palmitate, methyl stearate and methyl oleate.


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Figure 19: lab biodiesel sample 6A IR spectrum


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Figure 20: Lab biodiesel sample 6B IR spectrum


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7 Excess Methanol Evaporation

Rovatary evaporation was used to remove any excess methanol in the lab produced

biodiesel samples. Excess methanol was evaporated of three lab biodiesel samples.

Rovac was set at the condition: water bath temperature at 55°C, rotate at 100rpm

evaporation time 30 minutes. A balance was used to weigh the difference of the

biodiesel samples before and after this process.

Table 21: Weight difference of biodiesel samples before and after evaporation

Label Weight before

Evaporation(g)

Weight after

Evaporation(g)

Difference(g)

2A 35.4503 35.1401 0.3102

2B 24.6442 19.0616 5.5826

3A 332.40 332.27 0.13

3B 136.10 121.09 15.01

4A 149.79 149.06 0.73

The data in table 21 shows that more excess methanol was evaporated from biodiesel

sample 2B and 3B. These results matched with the low conversion rate of methyl

esters based on the GC experiments when lower conversion rates resulted in greater

methanol being left in the biodiesel samples.

Some of the other biodiesel samples were evaporated and unexpectedly turned solid.

More methanol was mixed with these solid biodiesel samples and stirred however they

could not be returned to a liquid state.

This problem had been discussed and explored in earlier research papers. One

possibility was that, because the saturated methyl esters take over the majority of


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biodiesel methyl esters, the cloud point can be pretty high and it might form solid state

biodiesel even at room temperature after evaporating the surplus methanol. This

hypothesis raises the prospect for further research in order to explain the formation of

solid biodiesel at room temperature. Alternatively the saturated methyl esters may

exist in different polymorphic forms and heating interconverts between a low melting

and a high melting form. Such a conversion might have implications for long term

storage.

8. Results evaluation of optimized method of biodiesel

production

Table 22 shows some of the variations in the production methodology along with the

yield of fatty acid methyl esters in the samples. The table was reordered according to

the values of total methyl esters concentrations in the right column. The best yield of

methyl esters may not reflect the optimised method as other factors such as methanol

requirement may reduce the viability. There was clearly a best possible set of

conditions and, with more advanced statistical modelling techniques, it might be

possible to optimise the yield further.


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Table 22: Summary of biodiesel production variables using 100 ml batches of waste

cooking oil

Batch

(100ml)

Acid

value

Acidic

esterification

stage

Basic

transesterification stage

Total

CH3OH

Methyl

esters

(mg/ml)

rank

% FFA H2SO4 (ml)

CH3OH (ml)

KOH (mg)

NaOH (mg)

CH3OH (ml)

CH3OH (ml)

1B 8.5 0.35 12 870 54 66 0.8794

1C 8.5 0.10 12 870 54 66 0.8067

5A 8.5 0.3 30 1200 40 70 0.7909

6C 5.76 0.38 24.6 522 16.3 40.9 0.7905

9A 8.5 0.15 12 1065 25 37 0.7868

9C 8.5 0.15 15 865 25 40 0.7867

1A 8.5 0.10 10 870 39 49 0.7862

6D 4.18 0.28 18 1029 32.2 40.2 0.7811

8E 8.5 0.10 20 677 14 34 0.7673

8C 8.5 0.15 20 640 22.5 42.5 0.7657

2A 8.5 0.10 10 360 37 47 0.7642

4A 8.5 0.3 30 450 15 45 0.7531

10A 8.5 0.15 15 1060 25 40 0.752

6A 4 0.26 17 619.2 19.3 36.3 0.7516

9D 8.5 0.15 15 865 25 40 0.7491

8B 8.5 0.15 15 815 27.5 42.5 0.733

3A 8.5 0.15 15 1638 58 73 0.7303

8A 8.5 0.23 15 915 27.5 42.5 0.7295

9B 8.5 0.15 15 865 20 35 0.7272

4C 8.5 0.3 30 600 20 50 0.7255

7A 8.5 0.4 23 1500 40 63 0.7144

6B 5.83 0.38 25 505 15.8 40.8 0.7111

3B 8.5 0.3 30 1890 50 80 0.7005

1D 8.5 0.10 8 870 29 37 0.6245


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Conclusion

There were thirty biodiesel samples produced and three of these failed due to excessive

soap formation leading to low methyl esters conversion rates and an excess of gel

made it difficult to separate the top and bottom layers. It was thought that the cause for

this unsuccessful biodiesel production very likely occurred during the acidic

esterification step. It was suggested in the original method that 8 ml of methanol be

used during the acidic esterification stage for every 100 ml of waste cooking oil but,

noticeably, this method did not work properly because of too much soap development.

Based on the optimised method, developed later, it was recommended that at least 12

ml of methanol for every 100 ml of waste cooking oil feedstock should be used at this

stage. Despite this three production samples still failed, possibly, due equipment

limitations resulting in them not being heated or stirred accurately. This could be the

subject of a future investigation.

Three groups of methyl esters were analysed by GC for their methyl esters

concentration:

Two batches of biodiesel samples after the acidic esterification stage

Two batches of biodiesel samples after basic transesterification stage, and

Four batches of biodiesel after optimized stage

Minitab’s 2 samples t-test method was used to evaluate the results and, according to

the statistic assessment, we can conclude that the optimized stage of biodiesel

production produced a better conversion rate of methyl esters than the other two stages.

Five controlled group samples and twenty four lab produced samples of biodiesel were

studied for their important properties such as cloud point and relative viscosity using

Minitab statistical software. The data was analysed with 2 sample t-test and the results


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showed no significant differences in the cloud point and relative viscosities of both

sample groups.

The methyl esters concentration of controlled groups and lab groups biodiesel were

estimated by GC experiment and calibration equation. Both groups’ concentration

values were investigated by 2 samples t-test which showed a significant difference in

their methyl esters concentration. NaOH as a basic catalyst generated a better methyl

esters conversion rate than KOH. We can conclude that the optimised method of lab

biodiesel production group has a better methyl esters conversion rate than the current

commercial method. The balance of the composition was the main unresolved issue

although it was probably due to unconverted triglyceride. This problem could be

resolved by NMR.

An optimized method of biodiesel production using waste

cooking oil was achieved and is as follows:

Step1: Examine the acid value of waste cooking oil feedstock using BP method;

calculate the free fatty acid content in the oil

Step 2: Heat the waste cooking oil (100ml) to 60°C and maintain the temperature for

about half an hour then settle the oil over night to eradicate water

Step 3: Acidic esterification stage: Heat the oil to between 35 and 45°C; add 0.5-

1.0% by weight of free fatty acid (calculated by step one) of sulphuric acid to the oil

(100ml). Then add 1:15 to1:20 molar ratio of oil to methanol to the heated oil while

constantly stirring at the speed about 500 rpm. Keep heating for at least an hour before

letting settle overnight


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Step 4: Prepare sodium methoxide solution: Prepare pure sodium hydroxide and

methanol as solvent to make stock solution at the concentration 30mg/ml. Shake or

sonicate it for 30 minutes and leave to settle overnight

Step 5: Basic esterification. Heat the mixed oil to 60°C. Add first half of 16 - 18%

by weight of waste cooking oil of sodium methoxide to the oil. Maintain the heat

while stirring at a slower speed for 5 minutes. Then add another half of sodium

methoxide. Maintain heat while stirring for another 30 to 60 minutes before turning

off the heat and let settle over night

Step 6: Separate the top layer and bottom layer with a separating funnel

Step 7: Washing: Use warm water of one third the volume of biodiesel and wash

three times before letting the biodiesel settle for future use.


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References

[1] The FOOLPROOF way to make biodiesel By Aleks Kac Ljubljana

Slovenia http://journeytoforever.org/biodiesel_aleksnew.html (2001)

[2] Biodiesel Production Technology August 2002-January 2004 By J.Van Gerpen, B

Shanks, and R. Pruszko, D. Clements, G. Knothe National Renewable Energy

Laboratory Operated for the U.S. Department of Energy. (2004)

[3] A critical review of the bio-diesel as a vehicular fuel by Mustafa Balat, Havva

Balat Sila Science and Energy Unlimited Company, University Mahallesi, Tranbzon,

Turkey. www.sciencedirect.com (2008)

[4] Origin of Biodiesel http://en.wikipedia.org/wiki/Biodiesel

[5] Knothe, G., Historical Perspectives on Vegetable Oil-Based Diesel Volume 12 •

November 2001Fuels

http://www.biodiesel.org/resources/reportsdatabase/reports/gen/20011101_gen-346.pdf

[6] Bernardes OL, Bevilaqua JV, Leal MCMR, Freire DMG, Langone MAP. Biodiesel

fuel production by the transesterification reaction of soybean oil using immobilized

lipase. Apple Biochem Biotechnol 2007;137–140:105–14.

[7] Monitoring biodiesel production (transesterification) using in situ viscometer by

Naoko Ellis, Feng Guan, Tim Chen, Conrad Poon Department of Chemical and

Biological Engineer, University of British Columbia, Vancouver, Canada

www.sciencedirect.com (2008)

[8] Demirbas A Biodiesel production via non-catalytic SCF method and biodiesel fuel

characteristics. Energy Conv Mgmt 2006;74:2271-82 Demirbas A Biodiesel

production via catalytic and non-catalytic supercritical alcohol transesterification and

other methods: a sirveu. Energy Conv Mgmt 2003;44:2093-109


http://www.sciencedirect.com/

http://en.wikipedia.org/wiki/Biodiesel

http://www.biodiesel.org/resources/reportsdatabase/reports/gen/20011101_gen-346.pdf

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Optimization of Conversion of Waste Cooking Oil Into Biodiesel

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