Optimization and Modeling of Process Variables of Biodiesel Production from Marula Oil Using Response Surface Methodology
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Christopher C Enweremadu and Hilary L Rutto J.Chem.Soc.Pak., Vol. 37, No. 02, 2015 256 Optimization and Modeling of Process Variables of Biodiesel Production from Marula Oil using Response Surface Methodology 1 Christopher C Enweremadu* and 2 Hilary L Rutto 1Department of Mechanical and Industrial Engineering, University of South Africa, UNISA Science Campus, Florida, Private Bag X6, Florida 1710, South Africa. 2Department of Chemical Engineering, Vaal University of Technology, Private Bag X021, Vanderbijlpark 1900, South Africa. [email protected]* (Received on 18th September 2013, accepted in revised form 23rd June 2014) Summary: This paper presents an optimization study in the production of biodiesel production from Marula oil. The study was carried out using a central composite design of experiments under response surface methodology. A mathematical model was developed to correlate the transesterification process variables to biodiesel yield. The transesterification reaction variables were methanol to oil ratio, x1 (10-50 wt %), reaction time, x2 (30-90 min), reaction temperature, x3 (30-90 °C) stirring speed, x4 (100-400 rpm) and amount of catalyst, x5 (0.5-1.5 g). The optimum conditions for the production of the biodiesel were found to be: methanol to oil ratio (29.43 wt %), reaction time (59.17 minutes), reaction temperature (58.80°C), stirring speed (325 rpm) and amount of catalyst (1.02 g). The optimum yield of biodiesel that can be produced was 95 %. The results revealed that the crucial fuel properties of the biodiesel produced at the optimum conditions met the ASTM biodiesel specifications. Keywords: Central composite design, Marula oil, Modeling, Optimization, Process variables, Response surface methodology. Introduction The world is no longer endowed with new Various feedstock from edible and non- sources of low cost energy fossil fuels and even as edible oils, waste and used vegetable oil, yellow the energy demands including for petroleum-based grease and animal fat have been used in biodiesel energy has been increasing due to growing production and found to be a good diesel substitute industrialization. According to the International [5-8]. One of the alternative sources of biodiesel Energy Outlook of 2011 [1], the world use of liquid which has not been considered can be from marula fuels will increase from 85.7 million barrels per day tree (Scelerocarya birrea), of subspecies caffera, in 2008 to 112.2 million barrels per day in 2035. Due which is a deciduous tree that grows naturally in to the growing number of transportation, agricultural many parts of South Africa, Botswana and Namibia and construction vehicles, petroleum is the single [9]. The natural marula nuts contain active anti- largest energy resource that has been consumed by oxidants which is likely to improve the oxidation the world's population, exceeding natural gas, coal, stability of the biodiesel produced from it. nuclear energy and renewable materials. Several optimization studies have been In addition, the transport sector will account carried out in the production of biodiesel. Meher et for 82% of the total increase in liquid fuel use, with al., [10], found that the yield of methyl ester from the remaining growth attributed to the industrial karanja oil under the optimal condition is 97–98%. sector [1]. Because of the progressive depletion of oil The optimization of biodiesel production has been resources in combination with increasing energy done using response surface methodology with consumption and the negative environmental impact different oils [11-15]. of fossil fuel use, there has been a shift toward Response surface methodology (RSM) is a alternative sources of energy that are renewable, mathematical/statistical based technique which is sustainable, efficient, cost-effective and generate useful for analyzing the effects of several reduced emissions [2, 3]. Biodiesel is among the independent variables on the response [16]. The most viable liquid transportation fuels for the eventual objective of RSM is to determine the foreseeable future and can contribute significantly to optimum operating conditions for the system, or to sustainable development in terms of socioeconomic determine the region, which satisfies the operating and environmental concerns [4]. specifications. Almost all RSM problems utilize one or both of these approximating polynomials [17]. *To whom all correspondence should be addressed. Christopher C Enweremadu and Hilary L Rutto J.Chem.Soc.Pak., Vol. 37, No. 02, 2015 257 RSM has an important application in the process The experiment sequence was randomized design and optimization as well as the improvement in order to minimize the effects of the uncontrolled of existing design. factors. Each response of the biodiesel yield (Y) was used to develop a mathematical model that correlates Although biodiesel has been produced using the yield of biodiesel to the experimental variables non-edible and edible oils, no study has been found through first order, second order, third order and on the production of biodiesel from marula oil. The interaction terms, according to the following third main objective of this work is to produce biodiesel order polynomial equation. from marula oil using transesterfication process. A 4 4 4 4 4 central composite design (CCD) was used to study 2 3 (2) YO jXj ijXiXj jjXj kijXkXiXj jjjXj the effects of five transesterification process j1 j,i 1 j1 j,i,k 1 j1 variables: methanol to oil ratio, reaction time, where is offset term, is linear effect, is reaction temperature, stirring speed, and amount of 0 j ij first-order interaction effect, is squared effect, catalyst on the yield of biodiesel. A mathematical jj kjj is second-order interaction effect. model was developed and used to correlate the transesterification process to the yield of biodiesel. The experiments were repeated four times Numerical optimization was used to determine the and the average result was chosen. optimal conditions that can be used for the biodiesel production. Some of the important fuel properties of Table-2: Levels of transesterification process biodiesel produced at optimum conditions were variables. Variable Coding Unit Levels compared with fuel properties of biodiesel using -2 -1 0 1 2 ASTM standard. Methanol-oil ratio x1 wt % 10 20 30 40 50 Time x2 min 30 45 60 75 90 Experimental Temperature x3 ⁰C 30 45 60 75 90 Stirring speed x4 rpm 100 175 250 325 400 Marula oil was supplied by Marula Pty Ltd. Amount of catalyst x5 g 0.5 0.75 1.0 1.25 1.5 The fatty acid composition of marula oil is given on Production of biodiesel Table-1. Sodium methoxide and methanol were The marula oil was heated to 100 °C to purchased from Rochelle Chemical Suppliers, South eliminate residual water and speed up the Africa and were of analytical grade. A reference transesterification reaction. As there was no adequate standard of fatty acid methyl ester FAME Mix (C8- information on biodiesel synthesis from marula, the C24) catalogue number (18918.1 AMP) was alkali transesterification and the “foolproof” methods purchased from the Sigma Chemical Co. Ltd. were tested. The foolproof method is essentially a Table-1: Fatty acid composition of Marula oil (wt %). two-step transesterification process. As the alkali Fatty acid Marula oil transesterification method was not successful due to Saturated: the high free fatty acid content, a two-step acid-alkali Palmitic C16:0 10.2±2.31 production method was adopted. Transesterification Stearic C18:0 6.3±3.58 of waste vegetable oil was carried out in a Eicosanoic C20:0 1.6±1.07 Monounsaturated: temperature-controlled hot plate equipped with a Palmitoleic C16:1 1.1±0.59 reflux condenser and magnetic stirrer. During the Oleic C18:1 74.1±3.56 Polyunsaturated: acid-catalyzed stage, the amount of methanol used Linoleic C18:2 2.4±1.41 was 20% of the volume of oil plus 60% excess Alpha Linolenic C18:3 1.2±0.71 methanol. One liter of marula oil and 40% of the Values are mean ± SD of triplicate determinations required volume of methanol was measured and Design of experiment added to the heated marula oil at 60oC. The mixture was stirred gently for 5 min using a magnetic stirrer A Central Composite Design (CCD) was until it becomes murky. 1 ml of 95% sulfuric acid used to investigate the linear, quadratic, cubic and was added to the mixture. Holding the temperature at cross-product effects of the five experimental 60oC, the mixture was stirred gently for 1hr at 500- parameters on the yield of biodiesel. Table-2 lists the 600 rpm. The heat was removed and stirring range and levels of the five independent variables continued for another hour after which the mixture studied. The CCD comprises of a two-level full was allowed to settle for 2 hrs. The free fatty acid factorial design (24), eight axial or star points and five content was measured and found to be below 2 %. center points. In CCD the value of was held at 218. The normal alkali transesterification process The complete design matrix of the experiments followed. The experiments were carried out employed and results are presented on Table-3. according to experimental design matrix shown in Table-3. Christopher C Enweremadu and Hilary L Rutto J.Chem.Soc.Pak., Vol. 37, No. 02, 2015 258 Table-3: Experimental design matrix and results. Process variables Methanol-oil ratio Stirring speed Amount Time (hr) Temperature (°C) Biodiesel yield (%) (wt %) (rpm) of catalyst 20 45 45 175 1.25 61.29±1.20 40 45 45 175 0.75 66.92±1.15 20 75 45 175 0.75 61.65±0.77 40