Fuel Properties of Biodiesel/Ultra-Low Sulfur Diesel (ULSD) Blends

Prediction of Oxidation Stability of Biodiesel Derived from Waste and Refined Vegetable Oils by Statistical Approaches

The oxidation stability (OX) of the biodiesel is an essential parameter mainly during storage, which reduces the quality of the biodiesel, thus affecting the engine performance. Moreover, many factors affect oxidation stability. Therefore, determining the most significant parameter is essential for achieving accurate predictions. In this paper, an empirical equation (Poisson Regression Model (PRM)), machine learning models (Multilayer Feed-Forward Neural Network (MFFNN), Cascade Feed-forward Neural Network (CFNN), Radial Basis Neural Network (RBFNN), and Elman neural network (ENN)) with various combinations of input parameters are utilized and employed to identify the most relevant parameters for prediction of the oxidation stability of biodiesel. This study measured the physicochemical properties of 39 samples of waste frying methyl ester and their blends with various percentages of palm biodiesel and refined canola biodiesel. To this aim, 14 parameters including concentration amount of WFME (X1), PME (X2), and RCME (X3) in the mixture, kinematic viscosity (KV) at 40 °C, density at 15 °C (D), cloud point (CP), pour point (PP), the estimation value of the sum of the saturated (∑SFAMs), monounsaturated (∑MUFAMs), polyunsaturated (∑PUFAMs), degree of unsaturation (DU), long-chain saturated factor (LCSF), very-long-chain fatty acid (VLCFA), and ratio (∑MUFAMs+∑PUFAMs∑SFAMs) fatty acid composition were considered. The results demonstrated that the RBFNN model with the combination of X1, X2, X3, ∑SFAMs, ∑MUFAMs, ∑PUFAMs. VLCFA, DU, LCSF, ∑MUFAMs+∑PUFAMs∑SFAMs, KV, and D has the lowest value of root mean squared error and mean absolute error. In the end, the results demonstrated that the RBFNN model performed well and presented high accuracy in estimating the value of OX for the biodiesel samples compared to PRM, MFFNN, CFNN, and ENN.

Physicochemical Properties Enhancement of Biodiesel Synthesis from Various Feedstocks of Waste/Residential Vegetable Oils and Palm Oil

The main aim of the present study was to improve the oxidation stability and cold flow properties of biodiesel produced from waste frying/cooking oil and palm oil. In this work, waste frying/cooking methyl ester (WFME) and palm methyl ester (PME) were prepared using an alkali-catalyzed transesterification process, and the physicochemical properties of the pure biodiesel as well as of binary blends among them were investigated. The results indicated that palm biodiesel and WFME18, produced from a mixture of frying, cooking, sunflower, and corn oils, can be used as antioxidant additives, enhancing biodiesel stability. Additionally, it was found that WFME1 and WFME12 derived from waste residential canola oil can be used as cold flow improvers for enhancing the cold flow properties of palm biodiesel. Moreover, ultra-low sulfur diesel fuel winter (ULSDFW), ultra-low sulfur diesel fuel summer (ULSDFS), kerosene (KF), and benzene (BF) were utilized to enhance the cold flow properties of the samples and meet the requirements of diesel fuel standards. The investigation of the experimental results indicated that blending WFME-PM with a low proportion of petroleum-based fuel (KF and BF) could significantly improve the cold flow properties (CP and PP) as well as oxidation stability of WFME.

Locally Sustainable Biodiesel Production from Waste Cooking Oil and Grease Using a Deep Eutectic Solvent: Characterization, Thermal Properties, and Blend Performance

As part of local sustainability efforts, biodiesel was synthesized via transesterification using a deep eutectic solvent (DES) without further washing from on-campus, dining facility waste cooking oil and grease. Before moving forward with repurposing used DES as a solvent in chemistry teaching labs, we determined the suitability of the biodiesel as an alternative fuel blended with diesel to power campus utility vehicles. Biodiesel components were characterized by gas chromatography-mass spectrometry (GC-MS), Fourier transform infrared spectroscopy (FTIR), nuclear magnetic resonance spectroscopy (¹H NMR), viscometer, differential scanning calorimetry (DSC), and evolved gas analysis during pyrolysis with a thermogravimetric analyzer coupled with FTIR (TGA-FTIR). The four major components of fatty acid methyl esters (FAMEs) in the biodiesel were methyl oleate, methyl linoleate, methyl palmitate, and methyl stearate. Kinematic viscosity over typical temperature ranges was within optimal values recommended by the American Biodiesel Standard (ASTM D6751), with a 30:70 biodiesel/diesel blend experimental viscosity of 3.43 cSt at 40 °C and a calculated viscosity of 10.13 cSt at 0 °C. The pure biodiesel's cold-temperature onset of crystal formation is -10.1 °C versus -16.4 °C for a 30:70 biodiesel/diesel blend. Pyrolysis indicates good thermal stability, however, with an increased CO₂ evolution in the blended fuel at higher temperatures as compared to that in the pure biodiesel and the pure diesel. Combustion gas analysis indicates virtually complete combustion of the blended fuel to CO₂ and H₂O with only trace amounts of CO. Overall results indicate that the biodiesel synthesized using DES is a suitable fuel for campus utility vehicles in the local moderate temperature climate and affords increased local sustainability by using used DES repurposed in our chemistry teaching labs.

Development of an Automated Column Solid-Phase Extraction Cleanup of QuEChERS Extracts, Using a Zirconia-Based Sorbent, for Pesticide Residue Analyses by LC-MS/MS

A new, automated, high-throughput, mini-column solid-phase extraction (c-SPE) cleanup method for QuEChERS extracts was developed, using a robotic X-Y-Z instrument autosampler, for analysis of pesticide residues in fruits and vegetables by LC-MS/MS. Removal of avocado matrix and recoveries of 263 pesticides and metabolites were studied, using various stationary phase mixtures, including zirconia-based sorbents, and elution with acetonitrile. These experiments allowed selection of a sorbent mixture consisting of zirconia, C18, and carbon-coated silica, that effectively retained avocado matrix but also retained 53 pesticides with <70% recoveries. Addition of MeOH to the elution solvent improved pesticide recoveries from zirconia, as did citrate ions in CEN QuEChERS extracts. Finally, formate buffer in acetonitrile/MeOH (1:1) was required to give >70% recoveries of all 263 pesticides. Analysis of avocado extracts by LC-Q-Orbitrap-MS showed that the method developed was removing >90% of di- and triacylglycerols. The method was validated for 269 pesticides (including homologues and metabolites) in avocado and citrus. Spike recoveries were within 70-120% and 20% RSD for 243 of these analytes in avocado and 254 in citrus, when calibrated against solvent-only standards, indicating effective matrix removal and minimal electrospray ionization suppression.