The world needs to increase renewable and alternative fuel sources such as Biomass, Bioethanol, and Biodiesel to compete with fossil fuels. Biodiesel is an important renewable fuel source since it can be used in regular diesel vehicles without requiring engine modifications. Conventional biodiesel production takes around 90 min of reaction time. A longer reaction time is not suitable for commercial production. Furthermore, traditional products such as oil react with biodiesel methoxide to produce a maximum of 90% biodiesel yield. As the catalyst is not involved with the reaction, pure methanol and methoxide (methanol with KOH catalyst) are separately added to the system to enhance the pre-reaction step. By changing the methanol to methoxide ratio, biodiesel is produced, and yield is calculated. The highest yield, which is 95%, is obtained with a 5:15% methanol to methoxide ratio. The total reaction time with the new experimental procedure is only 20 min. That is a significant reduction by saving operating costs such as energy consumption. Produced biodiesel show similar properties to that of standard biodiesel.

This paper for the first time synthesizes novel biodiesel experimentally using low-cost feedstocks of coconut oil, caustic soda, and fermented palm wine contaminated by microorganisms. The alkaline catalyzed transesterification method was used for biodiesel production with minimal glycerol. The produced biodiesel was biodegradable and effective in cleaning a shoreline oil spill experiment verified by our developed oil spill radial numerical simulator. For the first time, an adaptive neuro-fuzzy inference system (ANFIS) was hybridized with invasive weed optimization (IWO), imperialist competitive algorithm (ICA), and shuffled complex evolution (SCE-UA) to predict biodiesel yield (BY) using obtained Monte Carlo simulation datasets from the biodiesel experimental seed data. The test results indicated ANFIS-IWO (MSE = 0.0628) as the best model and also when compared to the benchmarked ANFIS genetic algorithm (MSE = 0.0639). Additionally, ANFIS-IWO (RMSE = 0.54705) was tested on another coconut biodiesel data in the literature and it outperformed both response surface methodology (RMSE = 0.72739) and artificial neural network (RMSE = 0.68615) models used. The hybridized models proved to be robust for biodiesel yield modeling in addition to the produced biodiesel serving as an environmentally acceptable and cost-effective alternative for shoreline bioremediation.

The purpose of this study is to experimentally investigate the effect of unsaturation of the biodiesels obtained from grapeseed oil, wheat germ oil and coconut oil (reference fuel) for compression ignition (CI) engine application. Fatty acid profile analysis and physio-chemical properties were determined by standard test procedures. Engine testing was carried out in a 5.2-kW single-cylinder CI engine and the combustion, performance and emission characteristics were analysed. The effect of fuel property variation and the combustion reaction kinetics due to unsaturation difference have been discussed. The maximum brake thermal efficiency at full load for diesel was found to be 32.3% followed by 31.3%, 30.2% and 27.4 %, respectively, for coconut biodiesel (CBD), grapeseed biodiesel (GSBD) and wheat germ biodiesel (WGBD). Maximum heat release rate as observed for diesel, CBD, GSBD and WGBD are 63.2 J/°CA 60.7 J/°CA and 59 J/°CA and 43.4 J/°CA respectively. The brake-specific NO emission at full load is higher for CBD followed by GSBD, WGBD and diesel having values of 9.23 g/kWh, 8.91 g/kWh, 8.21 g/kWh and 7.6 g/kWh respectively. Conversely, the smoke emission is lower for CBD compared to the other tested fuels.

Diesel emissions contain high levels of particulate matter (PM) which can have a severe effect on the airways. Diesel PM can be effectively reduced with the substitution of diesel fuel with a biofuel such as vegetable oil. Unfortunately, very little is known about the cellular effects of these alternative diesel emissions on the airways. The aim of this study was to test whether coconut oil substitution in diesel fuel reduces the adverse effect of diesel emission exposure on human bronchial epithelial cells. Human bronchial epithelial cells were cultured at air-liquid interface for 7 days and exposed to diesel engine emissions from conventional diesel fuel or diesel fuel blended with raw coconut oil at low (10%), moderate (15%) and high (20%) proportions. Cell viability, inflammation, antioxidant production and xenobiotic metabolism were measured. Compared to conventional diesel, low fractional coconut oil substitution (10% and 15%) reduced inflammation and increased antioxidant expression, whereas higher fractional coconut oil (20%) reduced cell viability and increased inflammation. Therefore, cellular responses after exposure to alternative diesel emission are dependent on fuel composition.