Modeling and optimization of Thevetia peruviana (yellow oleander) oil biodiesel synthesis via Musa paradisiacal (plantain) peels as heterogeneous base catalyst: A case of artificial neural network vs. response surface methodology
Introduction
The need for a more environmentally friendly and renewable source of fuel is not only borne out of concern to protect the environment from greenhouse gases and other pollutants like NOx and particulates but also because of the depletion in the world reserve of fossil fuel as a result of over dependence on this resource due to industrial expansion and human population explosion. Hence, the interest in converting biomass resources, which are derived from carbon (IV) oxide and water via photosynthesis, to alternative fuels such as biodiesel and bioethanol (Kouzu and Hidaka, 2012). Biodiesel, an alternative, non-toxic, biodegradable and a renewable diesel fuel, is receiving more attention in recent times (Vicente et al., 2004, Kitakawa et al., 2007).
Some problems associated with biodiesel are its inherent higher price than the petro-diesel, which in many countries, is offset by legislative and regulatory incentives or subsidies in the form of reduced excise taxes, slightly increased NOx exhaust emissions, stability when exposed to air (oxidative stability), and cold flow properties that are especially relevant in North America (Knothe et al., 2005). The higher price can also be reduced by the use of inexpensive feedstock, which has sparked interest in materials such as waste oils (Encinar et al., 2007, Guan et al., 2009) and non-edible oils (Tiwari et al., 2007, SathyaSelvabala et al., 2011). In Africa, Nigeria in particular, the notable among non-edible oilseeds are Azadirachta indica, castor, Jatropha curcas, Jatropha gossipifolia, Calophyllum inophyllum, Hura crepitan and Thevetia peruviana. Although the use of cheap and non-edible seed oils is one of the effective ways of reducing the cost of biodiesel production, this has its own shortcoming of high free fatty acid (FFA) content, which poses problems of catalyst depletion, high purification cost and reduced yield in alkali-catalyzed transesterification (Veljkovíc et al., 2006, Shu et al., 2007).
One other way of lowering the cost of biodiesel production aside the use of non-edible oils is the use of heterogeneous catalysts instead of homogeneous ones. Due to the attendant problems (i.e. saponification, excess reactant consumption, environmental pollution, high alcohol-to-oil molar ratios and additional separation costs) associated with homogeneous catalysts such as minerals acids and alkalis, which drive high the cost of biodiesel production, heterogeneous catalysts are now receiving wide attention (Balbaşi et al., 2011). This is because heterogeneous catalysts are recoverable, less corrosive, produce no soap and can be reused (Kim et al., 2004). Some of the solid acid catalysts, which have been investigated as possible replacements of homogeneous catalysts in esterification and transesterification reactions are modified β-zeolite (SathyaSelvabala et al., 2011), ferric sulfate (Zhang et al., 2010), CaO (Zhang et al., 2010), KNO3/Al2O3 (Vyas et al., 2009), eggshell modified with magnesium and potassium nitrates to form a composite (Olutoye et al., 2011), sulfated zirconia (Muthu et al., 2010), ion exchange resins (Kitakawa et al., 2007, Marchetti et al., 2007) and wood ash (Sharma et al., 2012).
In recent time, biodiesel production using wastes-based heterogeneous catalysts are receiving attention due to availability and environmental issues (Olutoye et al., 2011, Chouhan and Sarma, 2013). Musa paradisiacal (plantain) belongs to the natural order, plantaginaceae, which contains more than 200 species (Ighodaro, 2012). Nigeria is one of the leading plantain producing countries in the world (FAO, 2006). In 2004, the country produced 2.103 × 109 kg harvested from 3.89 × 106 m2 (FAO, 2006). The high demand for plantain fruits generates wastes in form of peels, which are often discarded and sometimes used as animal feed. Although, the use of plantain peels ash as catalyst in biodiesel production has not been reported but the ash has been reported to contain oxides of potassium and sodium, which when dissolved in water; yield the corresponding hydroxides (Onyegbado et al., 2002, Olabanji et al., 2012). Thus, the presence of both potassium and sodium oxides in plantain peels are important sources of alkali production, which have been successfully applied in soap making (Onyegbado et al., 2002, Olabanji et al., 2012).
Response surface methodology (RSM) is a statistical tool and mathematical techniques used for developing and optimizing processes in which responses are optimized based on the influencing parameters (Baş and Boyaci, 2007). It is an important tool, which has proved useful in industrial research, most especially where variables influencing the system are many (Gopinath et al., 2010). RSM has the advantage of reducing the number of experimental runs, which is sufficient to provide statistically acceptable results (Betiku et al., 2012). An optimized process of biodiesel production from jatropha oil was carried out by Tiwari et al. (2007) using RSM while Betiku and Adepoju (2013) applied the tool to the optimization of Sesamum indicum oil biodiesel production in another study. Artificial neural networks (ANNs) have been in use to solve myriads of problems in science, engineering, mathematics, medicine, metrology, neurology, biology and psychology (Sulaiman et al., 2011). Rajendra et al. (2009) optimized the pretreatment process parameters for biodiesel production using ANN whereas Ebrahimpour et al. (2008) applied the tool in optimization studies of lipase production while optimization studies of biogas production from saw dust and other co-substrates was reported by Gueguim Kana et al. (2012) using the tool. However, Desai et al. (2008) compared the performance of ANN and RSM in the fermentative production of scleroglucan and reported that ANN has an edge over RSM.
In this present work, an effort was made to optimize the process variables (methanol–oil ratio, reaction time, catalyst amount and reaction temperature) for esterification of T. peruviana oil also known as yellow oleander oil (YOO) due to its high FFA using RSM. This work also aimed at preparing an active heterogeneous base catalyst from plantain peels, which was subsequently used for transesterification of the pretreated YOO. The process variables (methanol–oil ratio, reaction time and catalyst amount) for the transesterification reaction were also optimized using both ANN and RSM with a view to test their efficacies. The catalyst characterization and quality tests of the yellow oleander oil biodiesel (YOOB) produced were also reported.
Section snippets
Materials
The matured oilseeds of T. peruviana (yellow oleander) used were handpicked at the staff quarters of Obafemi Awolowo University, Ile-Ife, Osun State, Nigeria. The fleshy mesocarps/epicarps of the oilseeds were removed and sundried for two weeks, after which the fruits were shelled and decorticated. These kernels were further sundried for five days until constant weight. The kernels were ground to powder using a manual grinding machine. The unripe M. paradisiacal (plantain) fruits used in this
Results and discussion
YOOB was produced using a two-step process optimization i.e. esterification and transesterification. The efficacy of both RSM and ANN were tested in the optimization studies of the transesterification step.
Conclusions
This work demonstrated that the developed CPP is a potential catalyst for biodiesel production. The catalytic activity of the CPP can be attributed to high proportion of potassium (54.73%) and the problem of leaching of other metallic constituents such as sodium and calcium into the biodiesel product was not observed probably due to low levels of these metals in the CPP. The acid value of YOO with high FFA (7 ± 0.05%) was reduced to less than 2 mgKOH g−1 by esterification. Transesterification of
Acknowledgements
E. Betiku thanked World University Service, Germany for equipment donation and DAAD for provision of relevant literature.
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