Determination of sulphur in liquids obtained by thermal cracking of waste polymers and commercial fuels with different analytical methods

Low sulphur concentration in hydrocarbon products as fuels or lubricants is an important requirement for the high quality standards of refineries. A non-polarised energy dispersive X-ray fluorescence spectroscopy (EDXRFS) and sample combustion technique (ASTM D6428-99) was compared. A new application of energy dispersive X-ray spectrometry as analytical method for the determination of sulphur in fuels and fuel-like fractions was investigated. Low sulphur containing fuels and hydrocarbon mixtures obtained by thermal cracking of waste polymers were measured and the influence of C/H ratio on accuracy was studied. The concentration of sulphur in samples was measured with calibration graphs of different hydrocarbon matrices (commercial gasoline, diesel oil and white oil were used). Good correlation was observed between the different methods, but the correlation was depending on the characteristics of the matrices. Detection limits of 1.0 ppm, 1.1 ppm and 0.9 ppm were obtained for S in gasoline, diesel oil and white oil, respectively.     

A high-temperature sensor analyzer: Determination of difficult volatile organic impurities in solvents

It was shown that an automated analyzer with solid-electrolyte sensor cells can be used to determine difficult volatile organic impurities (technical oils, gasoline, and kerosene) in organic solvents (alcohols, acetone, and turpentine) by their two-stage oxidation with atmospheric oxygen at 100 °C (evaporation of a light fraction) and at a temperature of 900 °C and higher (burning impurities). Optimum conditions are found for the rapid determination of trace amounts of MS-20 oil in washing solvents (ethanol, benzene): time of determination, 5 min/sample; aliquot portion, 10 μL; linearity range of the calibration graph, from 20 to 100 mg/L of organic impurity; detection limit, 2.5 mg/L; RSD ≥ 8%. The results of determining the concentrations of gasolines of different grades and other organic mixtures for identifying substance grades are discussed. The novelty and advantages of the developed method consist in the rapid and quantitative determination of the octane number and other parameters of hydrocarbon fuels without preliminary sample preparation and also in the possibility of analyzing liquid samples of any other origin without resorting to the chemical methods of analysis. The ecological safety of the method is also important.     

Effect of Feed Composition Changing at Naphtha Catalytic Reforming Unit Due to Involvement of Gasoline Fraction Obtained by Diesel Fuels Hydrodewaxing into the Processing

One of the primary products of hydrodewaxing process is stable gasoline, which is characterized by low octane number on the one hand. On the other hand, it contains a significant amount of iso-paraffins (on average 45% wt.) and naphthenes (on average 25% wt.), which are reagents in the naphtha catalytic reforming process primary reactions. Feasibility of stable gasoline obtained by means of diesel fuel catalytic hydrodewaxing process involving into the processing at the naphtha catalytic reforming unit has been estimated using naphtha catalytic reforming mathematical model. Technological scheme of stable gasoline from hydrodewaxing unit supply to the reforming unit is presented. Naphtha catalytic reforming and diesel fuels hydrodewaxing processes resource efficiency increases by 15–20% due to rise in catalytic reforming feed source.     

Quantitative determination of sulfur compounds in FCC gasolines by AED. A study of the effect of catalyst type and catalytic conditions on sulfur distribution

The identification and quantification of sulfur-containing compounds in gasoline has become an area of interest because of impending legislation regulating total sulfur levels in these fuels. To study the effects of catalyst type and catalytic conditions on gasoline sulfur distribution, a method has been developed employing both the compound-independent and element-specific response of the atomic emission detector (AED). Calibration and quantification can be accomplished even where standards are not available, owing to the nature of the AED response. Compounds were separated on a thick film polydimethylsiloxane column. An external calibration curve was applied to the area responses of individual sulfur components in the sulfur chromatogram, and the concentrations of each were calculated. Summation of these sulfur concentrations over the gasoline range yields the total sulfur content of the gasoline. The method is applicable to the determination of these compounds in raw crude oils, finished gasolines, fluid cracking catalyst (FCC) unit gasolines, and fluid catalytic cracking “model” compound studies. A prefractionating column was employed to remove heavy (>C₁₃) materials; prefractionation is not, however, necessary for distilled or commercial gasoline samples. Detection limits, linearity, detector stability, and accuracy are discussed.     

Determination of single photon ionization cross sections for quantitative analysis of complex organic mixtures

Soft single photon ionization (SPI)-time-of-flight mass spectrometry (TOFMS) is well suited for fast and comprehensive analysis of complex organic gas mixtures, which has been demonstrated in various applications. This work describes a calibration scheme for SPI, which enables quantification of a large number of compounds by only calibrating one compound of choice, in this case benzene. Photoionization cross sections of 22 substances were determined and related to the yield of benzene. These substances included six alkanes (pentane, hexane, heptane, octane, nonane, decane), three alkenes (propene, butane, pentene), two alkynes (propyne, butyne), two dienes (butadiene, isoprene), five monoaromatic species (benzene, toluene, xylene, styrene, monochlorobenzene) and NO. The cross sections of organic compounds differ by about one order of magnitude but the photoionization properties of compounds belonging to one compound class are rather similar. Therefore, the scheme can also be used for an approximate quantification of compound classes. This is demonstrated by a fast characterization and pattern recognition of two gasoline samples with different origins (Germany and South Africa) and a diesel sample (Germany). The on-line capability of the technique and the scheme is demonstrated by quantitatively monitoring and comparing the cold engine start of four vehicles: a gasoline passenger car, a diesel van, a motorbike and a two-stroke scooter.     

主成分回归残差神经网络校正算法用于近红外光谱快速测定汽油辛烷值

根据汽油辛值预测体系本身的非线性特点,提出主成分回归残差神经网络校正算法（principal component regression residual artificial neural network,PCRRANN)用于近红外测定汽油辛烷值的预测模型校正,该方法给合了主成分回归算法（PC）,与经典的线性校正算法（PLS（Partial Least Square),PCR, 以及非线性PLS（NPLS,Non-linear PLS)等相比,预测明显的改善,文中还讨论了PCR主成分数及训练参数对预则模可能的影响。     

Determination of motor gasoline adulteration using FTIR spectroscopy and multivariate calibration

In this paper, an attempt has been made to develop a feasible procedure for the prediction of quality parameters of motor gasoline and to discriminate between the different adulterated motor gasoline samples using density values, distillation temperatures and Fourier transform infrared (FTIR) analyses along with multivariate calibrations without the need for using chromatographic separation or other expensive instruments such as an octane number analyser. Ten blend mixtures of regular and super motor gasoline were prepared in order to study density, distillation temperatures and FTIR spectra characteristics for each blend. Distillation temperatures for the pure and blend mixtures of regular and super motor gasoline at initial boiling point (IBP) to final boling point (FBP) at 5%Vol. interval were obtained. Accurate and complete distillation data on the uncontaminated fuel would be essential for comparison. Thirteen peaks of the absorbance at the wavenumbers: 434, 461, 484, 673, 694, 1030, 1086, 1217, 1231, 1460, 1497, 1606 and 3028 cm(-1) were chosen to perform the multivariate calibration. The results obtained were expected to be useful in determination and differentiation purposes, providing information on whether the density values, distillation temperatures and FTIR analyses along with multivariate method could be an appropriate feature for differentiating a particular pure motor gasoline sample from the others. The observed differences in the specific spectral bands are investigated and discussed. They have proven to be an effective combination in the pursuit of management's differentiation goals.     

Ethanoled gasoline bubble pressure determination: Experimental and Monte Carlo modeling

In this work, we present some experimental and modeling studies of ethanoled gasoline bubble pressures (ethanol + gasoline blends) at various temperatures and ethanol contents. Modelings are carried out using Monte Carlo simulations in a specific bubble-point pseudo ensemble and using the AUA4 force field. This method is first validated on the prediction of binary mixture bubble pressures (ethanol + n-hexane, ethanol + propylene, ethanol + toluene, ethanol + isooctane). It is shown that a good accuracy is reached without introducing empirical binary interaction parameter, demonstrating the predictivity of the approach. Then, simulations of ethanoled gasolines have been performed. The molecular representation of the gasoline is obtained using a lumping scheme from the detailed composition of a commercial gasoline. Simulation results are compared to experimental bubble pressures measured in this work on this commercial gasoline in which various proportions of ethanol have been added. From a qualitative point of view, the azeotropic behavior of such fuels is observed both experimentally and by simulations. From a quantitative point of view, an average deviation of 15% between experimental and simulation data is found. Such results show that Monte Carlo simulation using an accurate force field is an efficient method to predict phase equilibrium of complex mixtures such as oxygenated gasolines. This methodology can thus be seen as an efficient tool that can be used by engineers for fuel formulation or for equation of state or process model calibration.     

X荧光光谱技术在油品硫分析中的应用

选择校正曲线法定量，在能量色散X荧光光谱仪上建立汽油、柴油和重油中硫分析方法。方法重复性、再现性符合国家标准要求，分析效率高。     

Determination of trace elements in automotive fuels by filter furnace atomic absorption spectrometry

The determination of Cd, Cr, Cu, Pb and Ni was performed in gasoline and diesel fuel samples by electrothermal atomic absorption spectrometry using the Transverse Heated Filter Atomizer (THFA). Thermal conditions were experimentally defined for the investigated elements. The elements were analyzed without addition of chemical modifiers, using organometallic standards for the calibration. Forty-microliter samples were injected into the THFA. Gasoline samples were analyzed directly, while diesel fuel samples were diluted 1:4 with n-heptane. The following characteristic masses were obtained: 0.8 pg Cd, 6.4 pg Cr, 12 pg Cu, 17 pg Pb and 27 pg Ni. The limits of determination for gasoline samples were 0.13 μg/kg Cd, 0.4 μg/kg Cr, 0.9 μg/kg Cu, 1.5 μg/kg Pb and 2.5 μg/kg Ni. The corresponding limit of determination for diesel fuel samples was approximately four times higher for all elements. The element recovery was performed using the addition of organometallic compounds to gasoline and diesel fuel samples and was between 85 and 105% for all elements investigated.     

Liquid Chromatography/Electrochemistry/Mass Spectrometry as Screening Technique for Alcohols and Phenols in Fuels

Liquid chromatography (LC)/electro-chemistry/mass spectrometry (MS) with atmospheric pressure chemical ionization (APCI) and electrospray ionization (ESI) has been used for the determination of several alcohols and alkylphenols in gasoline and diesel fuels. After rapid sample preparation and a derivatization step with ferrocenecarboxylic acid chloride, the LC separation resulted in complex chromatograms. Selected mass traces helped to identify several groups of alcohols and phenols. Only a sum parameter could be obtained for alcohols and phenols of the same molecular mass because of the large number of structural isomers that were not chromatographically resolved in the mass traces. The results for qualitative screening of seven gasoline and four diesel fuel samples are presented. Apart from alcohols and phenols, several other compounds were also found in the samples. Many of these unknown compounds could be arranged in four series of homologues with a mass difference of 14 mass units. The potential of the method to analyze alcohol and phenol patterns without chromatographic separation was studied using both nanospray and electrospray ion sources in combination with tandem-MS.     

分子筛催化FCC混合C4烯烃液相水合反应

Methyl tert-butyl ether (MTBE) as an octane promoter in automobile fuels has been phased out in some countries due to environmental problems. This motivates substantial interest in finding new ways for upgrading gasoline[1,2]. The use of a replacement for MTBE, such as ethanol, is a feasible method to enhance the oxygenates and increase the octane number of gasoline[3].     

Wavelength selection for multivariate calibration using a genetic algorithm: a novel initialization strategy

Genetic algorithms and other procedures mimicking natural processes are being increasingly used for variable selection, to improve the predictive ability of partial least-squares multivariate calibration. Two issues are critical for the success of genetic algorithms: initialization (setting the first candidates for solving the problem at hand) and overfitting (the tendency to produce excellent results when training, but poor predictions toward fresh samples). A new procedure is presented for sensor selection problems, involving iterative reinitialization based on a statistical analysis of the included sensors. It is shown to give excellent results without the requirement of preparing independent test data sets. Monte Carlo simulations using a theoretical three-component example illustrate how partial least-squares regression greatly benefits from variable selection when the analyte of interest is diluted, and how the new initialization method compares with other strategies. The new genetic algorithm was applied to five experimental data sets. The target parameters were the concentrations of diluted analytes in four pharmaceutical mixtures studied by UV-visible spectrophotometry and the octane number in gasolines analyzed by near-infrared spectroscopy.     

气相色谱-氮化学发光检测法分析催化汽油中含氮化合物类型的分布

建立了催化汽油馏分中各种含氮化合物类型分布的气相色谱-氮化学发光检测分析方法,考察了各种色谱条件对含氮化合物分离的影响。采用化学预处理的方法浓缩了催化汽油中的含氮化合物,并结合气相色谱-质谱检测以及部分含氮化合物标准样品,对某催化汽油中的20多个含氮化合物进行了定性(或归类)。催化汽油中几种主要含氮化合物(苯胺、2-甲基苯胺、二甲基苯胺)含量测定值的相对标准偏差(RSD)均不大于2.5%。当信噪比(S/N)为3时,苯胺氮的检出限为1.0 mg/L。该方法可用于不同来源和不同加工工艺的汽油馏分中各种含氮化合物类型分布的研究。     

小波变换结合多维偏最小二乘方法用于近红外光谱定量分析

将小波变换和多维偏最小二乘法相结合用于近红外光谱定量校正模型的建立。首先将原始光谱进行小波变换分解，得到系列小波细节系数，通过选取一组受外界因素少、信息强的小波系数组成三维光谱阵，然后再采用多维偏最小二乘法建立校正模型。实验结果表明，该方法所建近红外校正模捌的预测能力更强，并更具稳健性。     

Determination of benzene in gasoline using direct injection-mass spectrometry

A high-speed determination of benzene in gasoline samples using a non-separative method based on direct injection into the mass spectrometer is proposed. The results obtained are very similar to those provided with fast GC-MS.The calibration set was made up of gasoline samples in which the benzene was determined chromatographically and samples of gasoline subjected to a process of evaporation - until the complete disappearance of the original benzene - to which known concentrations of this compound had been added. A PLS1 multivariate calibration model was constructed. Cross-validation was used to select the optimum number of PLS components. The prediction capacity of the model was checked with an additional group of gasoline samples that had not been used either in the construction or in the validation of the model.With the direct injection method proposed here it was possible to analyse 24 samples over a period of 1 h. The direct injection method is rapid, simple and - in view of the results - highly suitable for the determination of benzene in gasoline samples.     

人工神经网络用于近红外光谱预测汽油辛烷值

本文对BP人工神经网络(ANN)方法在汽油的辛烷值与其近红外光谱光谱吸光度的关系之间进行关联预报方面进行了研究。采用35个汽油实际样本数据,建立了利用汽油的近红外光谱光谱吸光度预测汽油辛烷值的BP人工神经网络模型。对所有辛烷值的计算结果与实测值进行了比较,得到的预测值与实测值计算误差小于1.55%。     

Determination of total sulfur in diesel fuel employing NIR spectroscopy and multivariate calibration

A method for sulfur determination in diesel fuel employing near infrared spectroscopy, variable selection and multivariate calibration is described. The performances of principal component regression (PCR) and partial least square (PLS) chemometric methods were compared with those shown by multiple linear regression (MLR), performed after variable selection based on the genetic algorithm (GA) or the successive projection algorithm (SPA). Ninety seven diesel samples were divided into three sets (41 for calibration, 30 for internal validation and 26 for external validation), each of them covering the full range of sulfur concentrations (from 0.07 to 0.33% w/w). Transflectance measurements were performed from 850 to 1800 nm. Although principal component analysis identified the presence of three groups, PLS, PCR and MLR provided models whose predicting capabilities were independent of the diesel type. Calibration with PLS and PCR employing all the 454 wavelengths provided root mean square errors of prediction (RMSEP) of 0.036% and 0.043% for the validation set, respectively. The use of GA and SPA for variable selection provided calibration models based on 19 and 9 wavelengths, with a RMSEP of 0.031% (PLS-GA), 0.022% (MLR-SPA) and 0.034% (MLR-GA). As the ASTM 4294 method allows a reproducibility of 0.05%, it can be concluded that a method based on NIR spectroscopy and multivariate calibration can be employed for the determination of sulfur in diesel fuels. Furthermore, the selection of variables can provide more robust calibration models and SPA provided more parsimonious models than GA.     

Quantitative Near-infrared Spectroscopic Analysis of Trimethoprim by Artificial Neural Networks Combined with Modified Genetic Algorithm

A novel method for rapid,accurate and nondestructive determination of trimethoprim in complex matrix was presented.Near-infrared spectroscopy coupled with multivariate calibration（partial least-squares and artificial neural networks） was applied in the experiment.The variable selection process based on a modified genetic algorithm with fixed number of selected variables was proceeded,which can reduce the training time and enhance the predictive ability when coupled with artificial neural network model.