Biodiesel has been referred to as a perfect substitute for diesel fuel due to its numerous promising properties. They are renewable, clean, increases energy security, improves the environment and air quality and also provides some good safety benefits. This study is focused on the investigation of the use of natural heterogeneous catalysts for production of biodiesel from jansa seed oil, as well as the implementation of artificial neural network (ANN) for the prediction of biofuel yield and process parameters. The biodiesel was produced through transesterification reaction by reacting jansa seed oil (FFA) with methanol (alcohol) to yield methyl ester. Waste periwinkle shell was prepared in 3 different forms; raw, calcined and acidified. The percentage yield of the methyl ester obtained were calculated and tabulated. The process parameters considered were methanol-oil mole ratio, catalyst concentration, agitation speed, reaction temperature and reaction time. The results of this research work revealed that the calcined periwinkle shell catalyst produced higher yield of biodiesel, compared to the yield obtained from the raw and acidified catalyzed process. The properties of the fatty acid methyl esters were within the standard range. The experimental and predicted yield were marginally the same. Hence, the model accurately predicted the yield with acceptable coefficient of determination and low mean squared error (MSE). The results demonstrate the flexibility of ANN model and the improvement of the model in terms of performance prediction when solving problems with stochastic dataset, especially the transesterification of biodiesel.
Polycyclic aromatic hydrocarbons (PAHs) and heavy metals (HMs) are predominant pollutants linked with anthropogenic activities across a host of environmental mediums. The level of pollution, ecological and health risk were assessed in surface water from Ekulu in Enugu metropolis, Nigeria for 17 PAHs and selected HMs (As, Cd, Cr, Cu, Pb, Ni, Zn) components. PAHs and HMs were determined using a gas chromatography-flame ionization detector (GC-FID) and atomic adsorption spectrophotometer (AAS). The total PAHs in station A (3.17mg/l), B (1.51mg/l), and C (1.83mg/l) were due to high molecular weight (HMW) PAHs than low molecular weight (HMW) PAHs. HMs contents were within USEPA and WHO minimum contamination levels (MCL) except Cr and Pb. The molecular diagnostics of PAHs showed that incomplete combustion of carbonaceous compounds was dominant, while petrogenic was insignificant across all samples. The ecological indices of PAHs and HMs varied from medium to high pollution due to anthropogenic activities that pose a threat to the ecosystem. The non-carcinogenic models showed that hazard index (HI) ranged from PAHs (0.027 – 0.083) and HMs (0.0067 – 0.087) which is less than unity implying no adverse health issues. The lifetime cancer risk (LCR) for PAHs (4.21×10–4 – 9.61×10–4) and HMs (1.72×10–5 – 3.98×10–5) suggested significant cancer risk is possible over some time for a population of 1 in 10,000 and 100,000 for both PAHs and HMs exposure for 70 years. Therefore, there is an urgent need for proper pollution control and mitigation plan to preserve both age groups from being continuously exposed to anthropogenic activities in the Ekulu River and further study should be carried out to monitor the available toxicants.
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