Optimization Of Conversion Of Waste Cooking Oil Into Biodiesel

Optimisation of the Conversion of Waste Cooking Oil into Biodiesel

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 Conversion of Waste Cooking Oil into Biodiesel Page 1 of 80

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 Optimisation of Conversion of Waste Cooking Oil into Biodiesel Page 8 of 80

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

Stearic

Palmitoleic

Oleic

Linolei

Ricinic 12-

Other

16:0

18:0

16:1

18:1

c 18:2

OH-oleic

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

-

3.0

3.0

3.0

1.2

89.5

0.3

Castor oil

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 precombustion 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. Optimisation of Conversion of Waste Cooking Oil into Biodiesel Page 15 of 80

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]. Optimisation of Conversion of Waste Cooking Oil into Biodiesel Page 16 of 80

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]. Optimisation of Conversion of Waste Cooking Oil into Biodiesel Page 17 of 80

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. Optimisation of Conversion of Waste Cooking Oil into Biodiesel Page 21 of 80

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. Optimisation of Conversion of Waste Cooking Oil into Biodiesel Page 27 of 80

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. Optimisation of Conversion of Waste Cooking Oil into Biodiesel Page 28 of 80

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 unreacted 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: http://journeytoforever.org/biodiesel_aleksnew.html 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 Optimisation of Conversion of Waste Cooking Oil into Biodiesel Page 35 of 80

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 Optimisation of Conversion of Waste Cooking Oil into Biodiesel Page 36 of 80

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. Optimisation of Conversion of Waste Cooking Oil into Biodiesel Page 37 of 80

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

4

5.83

5.76

4.18

8.57

Weight (g) of free fatty acid in 100g of oil

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

11°C

12°C

11°C

12°C

12°C

12°C

11°C

12°C

11°C

4B

4C

5A

5B

6A

6B

6C

6D

7A

12°C

11°C

11°C

12°C

11°C

12°C

13°C

13°C

11°C

8A

8B

8C

8D

8E

9A

9B

9C

9D

Cloud point

11°C

12°C

11°C

12°C

11°C

11°C

12°C

12°C

11°C

Batch

10A

S1

S2

S3

S4

S5

Cloud point

11°C

10°C

11°C

11°C

11°C

12°C

Cloud point Batch Cloud point Batch

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 Boxplot of cloud point C, cloud point B 13.0 12.5

Data

12.0 11.5 11.0 10.5 10.0 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

Cloud point B Cloud point C

N 28 5

Mean 11.571 11.000

StDev 0.634 0.707

SE Mean 0.12 0.32

Difference = mu (cloud point B) - mu (cloud point C) Estimate for difference: 95% CI for difference:

0.571 (-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 Relative viscosity Batch Relative viscosity Batch Relative viscosity Batch Relative viscosity

1A

1B

1C

1D

2A

2B

3A

3B

4A

13’56” 12’26” 12’25” 12’03” 11’51” 12’35” 12’30” 14’06” 12’17” 4B

4C

5A

5B

6A

6B

12’28” 11’34” 12’02” 13’16” 13’31” 11’35” 8A

8B

10’59” 10’58” 10A

S1

8C

8D

9’09”

failed

S2

S3

8E

9A

6C

6D

7A

9’38”

9’23”

8’18”

9B

9C

9D

12’04

9’24”

10’23” 12’05” 11’15” S4

S5

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

1/27

4/27

4/27

4/27

10/27

3/27

1/27

Proportion 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

0/5

0/5

0/5

2/5

2/5

1/5

0/5

Proportion Mean

12’19”

The relative viscosity data for both groups were analysed by Minitab Figure 5: Boxplot of relative viscosity C, relative viscosity B Boxplot of relative viscosity C, relative viscosity B 14

13

Data

12

11

10

9 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 Probability Plot of relative viscosity C, relative viscosity B Normal - 95% CI

99

Variable relativ e v iscosity C relativ e v iscosity B

95 90

Mean 12.16 11.36

Percent

80

StDev N AD P 0.6556 6 0.373 0.288 1.436 26 0.648 0.081

70 60 50 40 30 20 10 5

1

6

8

10

12

14

16

Data

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

Q3

Maximum

Relative viscosity C

12.550

13.030

Relative viscosity B

12.265

14.060

Variable

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

N

Mean

StDev

SE Mean

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: 95% CI for difference:

0.799 (-0.020, 1.619)

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

Optimisation of Conversion of Waste Cooking Oil into Biodiesel Page 51 of 80

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

Optimisation of Conversion of Waste Cooking Oil into Biodiesel Page 52 of 80

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

standard methyl stearate GC calibration

y = 594587x + 3553.7 R2 = 0.995

700000 600000

peak area

500000 400000 300000 200000 100000 0 0

0.2

0.4

0.6

0.8

1

1.2

concentration Optimisation of Conversion of Waste Cooking Oil into Biodiesel Page 53 of 80

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

700000 600000 peak area

500000 400000 300000 200000 100000 0 0

0.2

0.4

0.6

0.8

1

1.2

concentration

Optimisation of Conversion of Waste Cooking Oil into Biodiesel Page 54 of 80

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

Optimisation of Conversion of Waste Cooking Oil into Biodiesel Page 58 of 80

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

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

Optimisation of Conversion of Waste Cooking Oil into Biodiesel Page 59 of 80

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 7080% 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 methyl esters concentration

c o n c e n t r a t i o n

0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0

Acidic esterification stage Basic transesterification stage Optimized stage

C 16:0(mg/ml)

C 18:0(mg/ml)

C 18:1(mg/ml)

total(mg/ml)

0.0053 0.0798 0.2625

0.0044 0.0662 0.2112

0.001 0.0981 0.3025

0.0107 0.2441 0.7742

acidic basic and optimized stage

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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

Relative conversation rate

methyl esters (mg/ml) 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

concentration

concentration

concentration

(16:0) mg/ml

(18:0) mg/ml

(18:1) mg/ml

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

concentration

concentration

concentration

(16:0) mg/ml

(18:0) mg/ml

(18:1) mg/ml

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

Concentration

Concentration

Concentration

(16:0) mg/ml

(18:0) mg/ml

(18:1) mg/ml

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 N

Mean

StDev

SE Mean

conc1

2

0.01560

0.00693

0.0049

conc2

2

0.2441

0.0316

0.022

Difference = mu (conc1) - mu (conc2) Estimate for difference: 95% CI for difference:

-0.2285 (-0.5192, 0.0623)

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 Optimisation of Conversion of Waste Cooking Oil into Biodiesel Page 62 of 80

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.

Two-Sample T-Test and CI: conc1, conc3 Two-sample T for conc1 vs conc3 N

Mean

StDev

SE Mean

conc1

2

0.01560

0.00693

0.0049

conc3

4

0.6565

0.0299

0.015

Difference = mu (conc1) - mu (conc3) Estimate for difference: 95% CI for difference:

-0.6409 (-0.6910, -0.5908)

T-Test of difference = 0 (vs not =): T-Value = -40.71 P-Value = 0.000 DF = 3

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.

Two-Sample T-Test and CI: conc2, conc3 Two-sample T for conc2 vs conc3 N

Mean

StDev

SE Mean

conc2

2

0.2441

0.0316

0.022

conc3

4

0.6565

0.0299

0.015

Difference = mu (conc2) - mu (conc3) Estimate for difference: 95% CI for difference:

-0.4125 (-0.7542, -0.0707)

T-Test of difference = 0 (vs not =): T-Value = -15.33 P-Value = 0.041 DF = 1

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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 conclude that the result was significant. The mean concentration of methyl esters of biodiesel samples after basic transesterification and biodiesel samples after optimized method were not the same.

Optimisation of Conversion of Waste Cooking Oil into Biodiesel Page 64 of 80

Table 20: Total concentration of methyl esters of controlled group and lab biodiesel group prepared by the optimised method Controlled

Total methyl esters

Lab biodiesel

Total methyl esters

group

concentration (mg/ml)

group

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

Optimisation of Conversion of Waste Cooking Oil into Biodiesel Page 65 of 80

Variable

N

N*

Mean

SE Mean

StDev

Minimum

Q1

5

0

0.69232

0.00738

0.01651

0.66900

0.67725

24

0

0.75447

0.00968

0.04743

0.62450

0.72778

Median Controlled group 0.69140 Lab batches 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 Boxplot of controlled group, lab batches 0.90 0.85

Data

0.80

0.75 0.70

0.65 0.60 controlled group

lab batches

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Figure 18: Probability Plot of controlled group, lab batches Probability Plot of controlled group, lab batches Normal - 95% CI

99

Variable controlled group lab batches

95 90

Mean 0.6923 0.7545

Percent

80

StDev N AD P 0.01651 5 0.189 0.796 0.04743 24 0.534 0.154

70 60 50 40 30 20 10 5

1

0.60

0.65

0.70

0.75 Data

0.80

0.85

0.90

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 Lab batches

N

Mean

StDev

SE Mean

5

0.6923

0.0165

0.0074

24

0.7545

0.0474

0.0097

Difference = mu (controlled group) - mu (lab batches) Estimate for difference: 95% CI for difference:

-0.0622 (-0.0876, -0.0367)

T-Test of difference = 0 (vs not =): T-Value = -5.11 P-Value = 0.000 DF = 19

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

Optimisation of Conversion of Waste Cooking Oil into Biodiesel Page 67 of 80

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

Optimisation of Conversion of Waste Cooking Oil into Biodiesel Page 68 of 80

Figure 19: lab biodiesel sample 6A IR spectrum

Optimisation of Conversion of Waste Cooking Oil into Biodiesel Page 69 of 80

Figure 20: Lab biodiesel sample 6B IR spectrum

Optimisation of Conversion of Waste Cooking Oil into Biodiesel Page 70 of 80

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

Weight after

Difference(g)

Evaporation(g)

Evaporation(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 Optimisation of Conversion of Waste Cooking Oil into Biodiesel Page 71 of 80

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 % FFA

Acidic esterification stage CH3OH (ml) 12

Basic transesterification stage KOH (mg)

Total CH3OH

Methyl esters (mg/ml) rank

1B

8.5

H2SO4 (ml) 0.35

NaOH (mg) 870

CH3OH (ml) 54

CH3OH (ml) 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

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

50

80

0.7005

1D

8.5

0.10

8

29

37

0.6245

1638

1890 870

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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 0.51.0% 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 Optimisation of Conversion of Waste Cooking Oil into Biodiesel Page 75 of 80

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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