Gasoline Samples Research Articles

Behavior of micro pillar array column in high pressure gas chromatography

Micro pillar array column with interpillar distance of 2.5 µm for pillars diameter of 5 µm has been introduced in high pressure gas chromatographic systems for online industrial analysis. Separation of gas mixtures have been performed under carrier gas pressure as high as 60 bar using rotating valve for gas injection without sample decompression stage prior to injection. A very low intrinsic height equivalent to a theoretical plate value of 14 µm has been obtained in few seconds. Instead of conventional gas chromatography, carrier gas nature such as helium, argon and carbon dioxide and pressure can be used to tune the selectivity. Liquid hydrocarbon samples have been successfully introduced in the column using a septum based split/splitless injector modified to work up to 40 bar. Separations of VOCs and gasoline samples have been successfully performed.

Preventing SOx Emissions through Process Control: Interdigital Capacitors for On-Site Monitoring of Thiophene-Based Environmental Pollutants in Oil Refineries

The presence of organosulfur compounds in fossil fuels is a major source of environmental pollution (SOx emissions) and deteriorates the catalytic exhaust systems of automobiles. Therefore, the development of miniaturized, low-cost, robust interdigital capacitors (IDC) is required to precisely monitor organosulfur compounds in petroleum products. Based on the Pearson concept of hard/soft acids/bases (HSAB), NiS nanoparticles were prepared and integrated into chemical, heat, and wear-resistant TiO2 coatings to fabricate sensitive layers on IDC for the detection of benzothiophene (BT) and dibenzothiophene (DBT) in gasoline samples. Compared to NiS nanoparticles and pristine TiO2 sol, TiO2-NiS nanocomposites exhibit distinctive morphology with homogeneous distribution of NiS nanoparticles, high surface roughness, and greater localized nanoscale variations. Therefore, HSAB chemistry and spatially distinctive features of TiO2-NiS/IDC sensors yield excellent response and sensitivity toward BT/DBT. The reproducibility of sensor layers, selectivity, repeatability, and stability of TiO2-NiS/IDC sensor were studied before calibrating the devices for real-time measurements in refined gasoline samples. TiO2-NiS/IDC sensors exhibit a wide-range linear response, high sensitivity, and low detection limits in gasoline. Real-time sensor measurements show a 90.7% recovery of BT/DBT from gasoline samples. The sensors were calibrated in gasoline samples for potential process and quality control applications during crude oil refining.

A Compact and Configurable Gasoline Detection System Using a Microwave Sensor

We propose a compact and configurable sensor system using the 4 GHz to 6 GHz frequency band. The proposed system can support three sensors and is designed to detect input samples by using intrinsic vector network analyzer (VNA) functions as well as a simple detection algorithm. The system is composed of three parts: a sensor interface, an RF resonance signal processing board and configurable graphical user interface (GUI) software for storing, processing and detecting the input signal. The resonant frequency and its root mean square (RMS) power are measured, and the margins of the frequency bandwidth and power are estimated by analyzing statistics of the measured bandwidth and power for sample detection. For evaluation of the proposed system, we used three rectangular cavity sensors for gasoline detection and obtained minimum margins of the resonant bandwidth and RMS power at 15.5 Mhz and 2.7837 dB, respectively. The subsequent experiments using the margins validated that the proposed system and algorithm flow show stable detection performance within two seconds for a maximum ten gasoline samples. Although this evaluation has been conducted for gasoline samples, it can be applied to other sensors for which resonance characteristics can be obtained within the proposed bandwidth.

Baseline correction method for dynamic pressure gradient modulated comprehensive two-dimensional gas chromatography with flame ionization detection

A baseline correction method is developed for comprehensive two-dimensional (2D) chromatography (GC × GC) with flame-ionization detection (FID) using dynamic pressure gradient modulation (DPGM). The DPGM-GC × GC-FID utilized porous layer open tubular (PLOT) columns in both dimensions to focus on light hydrocarbon separations. Since DPGM is nominally a stop-flow modulation technique, a rhythmic baseline disturbance is observed in the FID signal that cycles with the modulation period (PM). This baseline disturbance needs to be corrected to optimize trace analysis. The baseline correction method has three steps: collection of a background “blank” chromatogram and multiplying it by an optimized normalization factor, subtraction of the normalization-optimized background chromatogram from a sample chromatogram, and application of Savitzky-Golay smoothing. An alkane standard solution, containing pentane, hexane and heptane was used for method development, producing linear calibration curves (r2 > 0.991) over a broad concentration range (7.8 ppm – 4000 ppm). Further, the limit-of-detection (LOD) and limit-of-quantification (LOQ) were determined for pentane (LOD = 2.5 ppm, LOQ = 8.2 ppm), hexane (LOD = 0.9 ppm, LOQ = 3.0 ppm), and heptane (LOD = 1.9 ppm, LOQ = 6.4 ppm). A natural gas sample separation illustrated method applicability, whereby the DPGM produced a signal enhancement (SE) of 30 for isopentane, where SE is defined as the height of the tallest 2D peak in the modulated chromatogram for the analyte divided by the height of the unmodulated 1D peak. The 30-fold SE resulted in about a 10-fold improvement in the signal-to-noise ratio (S/N) for isopentane. Additional versatility of the baseline correction method for more complicated samples was demonstrated for an unleaded gasoline sample, which enabled the detection (and visual appearance) of trace components.

Development of Crime Scene Intelligence Using a Hand-Held Raman Spectrometer and Transfer Learning.

The classification of ignitable liquids, such as gasoline, is critical crime scene intelligence to assist arson investigations. Rapid field gasoline classification is challenging because the current forensic testing standard requires gas chromatography-mass spectrometry analysis of evidence in an accredited laboratory. In this work, we reported a new intelligent analytical platform for field identification and classification of gasoline evidence. A hand-held Raman spectrometer was utilized to collect Raman spectra of reference gasoline samples with various octane numbers. The Raman spectrum pattern was converted into image presentations by continuous wavelet transformation (CWT) to facilitate artificial intelligence development using the transfer learning technique. GoogLeNet, a pretrained convolutional neural network (CNN), was adapted to train the classification model. Six different classification models were also developed from the same data set using conventional machine learning algorithms to evaluate the performance of our new approach. The experimental results indicated that the pretrained CNN model developed by our new data workflow outperformed other models in several performance benchmarks, such as accuracy, precision, recall, F1, Cohen's Kappa, and Matthews correlation coefficient. When the transfer learning model was challenged with the data collected from weathered gasoline samples, the classifier could still offer 73 and 53% accuracy for 50 and 25% weathered gasoline samples, respectively. In conclusion, wavelet transforms combined with transfer learning successfully processed and classified complex Raman spectral data without feature engineering. We envision that this nondestructive, automated, and accurate platform will accelerate crime scene intelligence development based on evidence's chemical signatures detected by hand-held Raman spectrometers.

Dibenzothiophene capture from model fuel by wild mustard stems derived activated carbon: kinetics and isothermal evaluations

ABSTRACT Wild mustard stems (WMS) are exploited as a potential and priceless feedstock for activated carbon (AC) synthesis through the optimised ZnCl2 activation method. Thermal Gravimetric Analysis (TGA), surface area (BET), Field Emission Scanning Electron Microscopy (FESEM-EDX), X-ray diffraction (XRD), Fourier Transform Infra-Red spectroscopy (FTIR), and Boehm titration method have employed in identifying the AC. The as-obtained AC was applied in the desulphurisation of dibenzothiophene (DBT) from synthetic gasoline and commercial gasoline samples. A 96.02% as a maximum removal efficiency of DBT from model gasoline was obtained at 30°C for a contact time of 30 minutes using 25 mL of 200 mg/L DBT solution and 0.40 g of the AC. The adsorption data have analysed for their adsorption isotherms, and the consequences followed the following order: Langmuir model > Freundlich model> Temkin model. The kinetics studies revealed that the pseudo-second-order kinetic model obeyed best the adsorption data. The desulphurisation study of the commercial gasoline through applying the best adsorption conditions gave a removal efficiency of 50.22% compared to 96.02% for the model gasoline. In conclusion, the present investigation offers a cheap and potential feedstock to create AC as an adsorbent for both model and commercial gasoline fuel desulphurisation.

Rapid prediction of fuel research octane number and octane sensitivity using the AFIDA constant-volume combustion chamber

Current research octane number (RON) and motor octane number (MON) gasoline performance characterization techniques use dated, complex engine testing methodology and limit researchers’ ability to easily characterize small volumes of experimental fuels. A novel methodology is presented that correlates measured ignition delay (ID) time to RON in an Advanced Fuel Ignition Delay Analyzer (AFIDA) constant-volume combustion chamber device at a single pressure/temperature condition, with an r2 of 0.99 and standard error (SE) of 1.0. The correlation of the slope of the ID time between two additional temperature points to octane sensitivity (S) produces an r2 of 0.97 and SE of 0.69; however, fuels with S > 12 are indistinguishable. These results are based on methodology calibration using 31 primary and toluene reference fuels containing 0%─40% ethanol with RON values ranging from 85 to 113. Validation of these methods using a 102-sample fuel matrix spanning an array of base fuels and additive chemistry designed to test the robust applicability of the method, along with pump gasoline and high-octane surrogate blend samples, demonstrates an r2 of 0.94 and SE of 1.3 for the RON correlation over all samples, whereas the equivalent S correlation produces an r2 of 0.78 and SE of 1.2 by excluding two additives, 3-pentanone and diisobutylene, which displayed poor S correlation results. This novel AFIDA analysis method can be performed in 1 h and with 40 mL of fuel, offering significant improvements in time and volume requirements over traditional techniques.

Data reconciliation applied to the conformity assessment of fuel products

The discrepant measurement results regarding the conformity assessment of diesel and gasoline fuels may lead to commercial dispute between producers (refinery) and consumers (storage terminal). The aim of this work was to apply data reconciliation in order to solve the discrepancy between producers’ and consumers’ measurements and allow to make decisions regarding the conformity/non-conformity assessment. Diesel and gasoline samples were analyzed in respect to total sulfur content and flash point and for sulfur content and final boiling point, respectively. Discrepant results between consumers’ and producers’ measurements were subject to data reconciliation. Data reconciliation was perform using a MS Excel spreadsheet. The sheet was divided into five sections: ‘Specification limits’, ‘Producer’s measurement’, ‘Consumer’s measurement’, ‘Reconciled measurement’, and ‘Histograms’. Data reconciliation was useful to solve the discrepancy between producer’s and consumer’s measurements in most of the studied cases, since provided reconciled values inversely weighted as function of measurement uncertainty. In addition, data reconciliation provided a reduced measurement uncertainty.

A foundational study of fire debris interpretation using quantitative measures of chromatographic features in gasoline and the use of graphical display to demonstrate data sufficiency

The analytical process for identifying ignitable liquids is based on fundamental chemical properties; however, the current interpretation of these properties as chromatographic data relies on subjective pattern recognition techniques. The subjectivity of these pattern recognition techniques increases with the presence of complex matrix contribution. To make the fire debris interpretation process more standardized and objective, a novel method is proposed for analyzing fire debris Gas Chromatography-Mass Spectrometry (GC–MS) data using quantitative measures of chromatographic features of interest. These features are represented by peak height ratios observed in the Total Ion Chromatograph and Extracted Ion Profiles.Chromatographic features of interest in 150 gasoline samples were evaluated and 64 chromatographic peak height ratios were selected for study. Statistical analysis was conducted to determine the variation observed for each of these ratios in the gasoline samples and to determine the frequency of these features in negative matrix samples. This information was evaluated to determine relative significance, as represented by the assigned points for each of these features. When summed and used as plot values, these cumulative scores graphically display the separation of gasoline samples from negative matrix samples using this methodology. The scores were used to create a sufficiency graph, which is a graphical display detailing the totality of data supporting a potential gasoline identification. The sufficiency graph also identifies the “gray” area where analysts are more likely to form differing opinions.The methodologies introduced are a step toward a documentation process that ensures greater transparency in fire debris examinations and comparisons. The methods generate a quantitative sufficiency graph for consistent data interpretation and documentation.

Effect of sampling modes on the discrimination of commercial gasolines using direct analysis in real time mass spectrometry

The identification and classification of gasolines are crucial in a forensic context because direct evidences are provided on gasoline adulteration or other related offenses. However, it is attractive but challenging to develop a facile and efficient strategy to discriminate different brands of commercial gasolines. Herein we propose a means to realize this goal by combining direct analysis in real time mass spectrometry (DART-MS) and principle component analysis (PCA). In this process, different experimental parameters, including the ratio between gasoline and methanol, heating temperature of helium, sample moving speed and helium gas pressure, were found playing vital roles to determine the analysis sensitivity of DART-MS. By evaluating the performance with three characteristic peaks (C8H12N+ at m/z 122, C17H17+ at m/z 221 and C16H24N+ at m/z 230) from gasolines, abundant fingerprinting spectra of gasolines were achieved for later favorable brand classification. Furthermore, sampling mode was found crucial to the distinguishing ability of different brands of gasolines for the first time. Two frequently used sampling modes (sample card sampling and glass rod sampling) were compared to discriminate 6 brands of standard gasolines and 28 brands of the Research Octane Number (RON) 92 and 95 (namely 92# and 95#) commercial gasolines. In contrast to glass rod sampling, a full separation of different brands of gasolines was more favorable to be generated by using sample card sampling. Though limited gasoline samples were performed, results generated from in this study indicated that it was feasible and promising to identify and classify different brands of commercial gasolines using DART-MS and PCA analysis.

Analytical Study of Affecting Gasoline Quality Properties on Environment and Its Conformity with Specifications

Gasoline is an important fuel in human life, but it is also responsible for deteriorating Ambient Air Quality (AAQ) through fugitive and exhaust emissions. In this study, chemical properties (Sulfur and Lead content) of gasoline production at Al-Daura refinery were verify based on a statistical quality control tool. Gasoline samples were examined in January/2011 and compared with samples examined in January/2019. In this study, it was concluded that the average production process and process variability for Sulfur content and added Lead value are stable. In January/2011 Sulfur content conforms to Iraqi and European standard specifications, but Lead value doesn’t conform to Iraqi standards, where internationally the use of lead to enhance engine performance has been banned since the 1970s of a century ago because it’s large dangerous on the environment. In January/2019 Sulfur content conforms to Iraqi standards but doesn’t conform to European standards specifications. The addition of lead to gasoline is stopped in 2016; imported gasoline was used by blend it with produced gasoline at al Daura refinery to raise its quality. Gasoline quality properties must be improved and tighten up according to international standards to save our environment.

A unified kinetic and thermodynamic model of evaporation for forensic applications

A unified kinetic and thermodynamic model was derived to predict evaporation for forensic applications, such as fire debris analysis. In this model, a reversible first-order reaction served as the foundation, with rate constants (kinetic regime) and standard vapor pressures (thermodynamic regime) as input parameters. The rate constants and standard vapor pressures for normal (n-) alkanes were fit by linear regression to the retention index, with correlation coefficients of 0.9969 and 0.9998, respectively. These regression equations were used to calculate fraction-remaining curves as a function of the retention index. From these curves, the kinetic and thermodynamic models were able to predict the total fraction remaining of the fuel, either as a bulk quantity or as a chromatogram, as well as the fractions remaining of individual compounds.To evaluate the kinetic and thermodynamic models, gasoline samples were experimentally evaporated to nominal fractions remaining of 0.7, 0.5, 0.3, and 0.1 (30%, 50%, 70% and 90% evaporated). The experimental chromatograms were compared to predicted chromatograms, with Pearson product-moment correlation coefficients of 0.9913 – 0.9068 for the kinetic model and 0.9903 – 0.8921 for the thermodynamic model. The experimental and predicted fractions remaining for individual compounds were compared for n-alkanes and alkylbenzenes spanning a wide range of retention indices and abundances. For the n-alkanes, the mean average percent error was 2.8 – 13.9% for the kinetic model and 3.2 – 20.2% for the thermodynamic model. This approach provides a unified basis for the comparison of the models, and demonstrates the accurate performance of each model.

Emission Characteristics of Agricultural and Industrial Cellulosic Wastes Blended with Gasoline

Agricultural and industrial wastes like sawdust and corncobs are definitely pollutants as they are disposed in dump sites and burnt in open air in most developing countries, like Nigeria. Proper utilization of these wastes could help reduce the environmental pollution arising from wastes disposal and combustion of fuels. Emissions generated from running an internal combustion (IC) engine with blends of gasoline and bio-ethanol produced from these wastes, as well as those of pure gasoline were compared in this work. A gas emission analyzer was placed at the exhaust of the IC engine and the readings were taken for each blend and for each round of testing period. The read out emissions were then compared with each other. The range of emissions for carbon monoxide (CO) were 1.45-2.75; 2.10-2.90; 2.00-2.62 and 3.0 % vol., for corncobs bio-ethanol/gasoline, softwood sawdust bio-ethanol/gasoline, hardwood sawdust bio-ethanol/gasoline and pure gasoline samples respectively while the emission ranges for hydrocarbon (HC) were 260-435; 328-360; 313-350 and 480 ppm for the same samples respectively. In the case of carbon dioxide (CO2), the samples gave 2.6-4.0; 2.2-3.9; 3.2-4.2 and 3.0 % vol. emissions. Thus all stakeholders considering the adoption of fuel blends in the country’s quest for increased energy mix can be properly guided on the pollutants associated with the investigated waste materials. This may help in the choice of appropriate waste to energy.

Discrimination of Methanol from Ethanol in Gasoline Using a Membrane-type Surface Stress Sensor Coated with Copper(I) Complex

Abstract We successfully fabricated a novel sensing platform, a Membrane-type Surface stress Sensor (MSS) coated with copper(I) complex bearing phen and BINAP ligands, [Cu(phen)((±)-BINAP)]PF6 (1, phen = 1,10-phenanthroline, BINAP = 2,2′-bis(diphenylphosphino)-1,1′-binaphthyl), for specific molecular sensing. Based on the transduction of mechanical stresses derived from sorption-induced deformation of Cu(I) complex, the detection performance of various volatile organic compounds (VOCs) has been investigated. The fabricated sensor devices showed selective responses to methanol over a wide range of VOCs. In addition, distinct MSS signals upon exposure to methanol were observed for mixing samples of methanol in n-hexane and gasoline with clear discrimination of ethanol mixtures. In fact, gasoline vapor with 1% methanol exhibited much higher MSS responses than 20% ethanol containing gasoline samples. Methanol contamination in gasoline and related petroleum samples is a world-wide common problem in the automobile and fuel sectors where detection of methanol contaminants with portable devices by easy procedures is required. The current research results will contribute to fulfilling these social demands.

Investigation on spectral standardization among multi-channel of an on-line near-infrared spectrometer

To tackle the issue that the multivariate calibration model cannot be shared among channels due to the inter-channel spectral differences in the on-line multi-channel spectrometer, taking the determination of octane number (RON) and aromatic hydrocarbon content (AC) of multiple reformulated gasoline by on-line Fourier transform near-infrared (FT-NIR) spectrometer combined with partial least squares (PLS) as an example, a novel approach for spectral standardization by piecewise cosine spectra (cosSSM) is proposed in this paper. A total of 42 reformulated gasoline samples were collected and their RON and AC were determined using standard methods with their NIR absorption spectra being measured using the three channels of an on-line NIR spectrometer, respectively. To prove the effectiveness of cosSSM, the spectra of each channel were standardized using cosSSM, and the PLS models of RON and AC were established using the cosine spectra in one channel, then the predictions of the cosine spectra in the other channels were made. The results suggested that cosSSM effectively eliminated the adverse effect of inter-channel spectral variation on the applicability of the channel-specific PLS model, and the performance was comparable to that of the well-established piecewise direct standardization (PDS) method. Besides, cosSSM is relatively simple and easy-to-implement in practical application.

Assessment of Adulteration of Gasoline (MSP) and Diesel (AGO), in Selected Fuel Stations in Kisii County

The major transport fuels in Kenya are gasoline and diesel. A complaint on adulteration of these fuels at the point of sale or during transportation is a common occurrence in the country. The present studies on analysis of petroleum adulteration does not give a scope of what is happening at the newly and upcoming petrol stations outside the capital of city. Purposeful sampling was carried out on investigating gasoline and diesel adulteration sold at selected fuel stations in in a case study of Kisii County, and whether these products are within the standards set by Kenya bureau of Standards (KEBs). Samples of gasoline and diesel were collected from selected five fuel stations and two laboratory testing methods of ASTM D86 (Distillation) and ASTM D1298 (Density determination) were conducted at Vivo Energy Company laboratory in Nairobi. Currently, the number of fuel stations selling Gasoline and diesel is enormous in Kisii region. They involve four major oil companies namely, Shell, Total, Kenol/Kobil, Oil Libya, and now KNOCK which dominate the market as well as locally owned ones. Therefore, the sampling method that was employed to select randomly five specific filling stations comprising of one major and four Minor companies representing the population with parameters of interest, for analysis in this study.

Reversed-phase dispersive liquid–liquid microextraction for elemental analysis of gasoline by inductively coupled plasma optical emission spectrometry

A green and fast sample preparation method based on reversed-phase dispersive liquid–liquid microextraction was developed for the separation and preconcentration of several elements in gasoline samples before ICP-OES determination.

AVALIAÇÃO ANALÍTICA DE ANALISADOR DE COMBUSTÍVEL COMERCIAL NO CONTROLE DE QUALIDADE DE ETANOL E GASOLINA COMUM

ANALYTICAL EVALUATION OF COMMERCIAL FUEL ANALYZER IN GASOLINE AND ETHANOL FUEL QUALITY CONTROL. Brazilian news media is full of examples about fuels out of the compliances and needs to control fuel quality. This work proposed an analytical validation of a commercial near infrared photometer (Xerloq, Tech Chrom Analytical Instruments, Brazil) able to identify percentage of ethanol in fuels comparing with NBR standards. Four procedures were selected: analysis of ethanol percentage in gasoline type C samples comparing with standard method ABNT 13992; analysis of ethanol percentage in fuel ethanol samples comparing with standard method ABNT 5992; linearity correlation and selectivity of standard solution analysis. Comparisons between the photometer and standards measurements were to determine the accuracy and precision of the device which presented a little variation from the norm (ER < 1.3%, sR < 0.4%). With regard to the test for linearity, Ethanol:water mixtures was analyzed with R-squared larger than 0.999 with RMSEV less than 1%. On selectivity tests, Gasoline:Ethanol:water and Methanol:Ethanol:water mixtures were measured with bias error not exceeding 5% for regulated samples. In conclusion, this fuel analyzer can be used to analyze ethanol content in Brazilian fuels with similar results comparing with classical standard volumetric and glass densimeter analysis and may indicate adulteration gasoline and ethanol samples by anomalous data.

Development of a Methodology Based on Extraction Induced by Emulsion Breaking for Copper Determination in Gasohol by Graphite Furnace Atomic Absorption Spectrometry

The development of a method based on extraction induced by emulsion breaking (EIEB) aiming copper determination in gasohol using graphite furnace atomic absorption spectrometry (GF AAS) is reported. Emulsification of the gasohol samples was carried out using nitric acid solution, (1,1,3,3-tetramethylbutyl)phenyl-polyethylene glycol surfactant (Triton X-114), and ultrasound energy. The variables related to the extraction efficiency were optimized by multivariate approaches (two-level factorial fractional design and Doehlert design). The best results were obtained when the emulsion was formed with 5.0 mL of the sample, 0.200 mL of 2.4 mol L-1 HNO3, 0.100 mL of 10% Triton X-114 and 10 min of sonication. A fast and efficient emulsion breaking was performed at 90 oC. A volume of 6.65 mL of the copper-rich hydroalcoholic phase was extracted, separated from the organic phase and analyzed. Under these conditions, the following analytical characteristics were obtained: 0.61 and 2.0 µg L-1 for limits of detection and quantification, respectively; precision (percentage of relative standard deviation, 10 µg L-1) of 2.8%; and analytical sensitivity of 0.011 L µg -1. Accuracy was assessed by spike tests, and values in the range of 95-110% were achieved. The method was applied in the determination of copper in Brazilian gasoline samples (gasohol with 27% ethanol).

Combustion, criteria pollutant and soot property assessment of mixing-controlled high-load engine operation with gasoline and diesel

Gasoline compression ignition (GCI) is an emerging technology that can achieve high fuel efficiency and low criteria emissions in diesel engine platforms using gasoline and gasoline-like fuels. While low- and mid-range loads are enabled with low temperature combustion (LTC) approaches, high-loads are more efficient with high temperature combustion (HTC) requiring mixing-controlled combustion (MCC). Lower soot emissions are achieved with gasoline even in high-load MCC than with diesel, but detailed soot properties from gasoline and diesel have been rarely discussed. In order to better understand how high-load operations affect soot properties, gasoline and diesel were tested in a six-cylinder heavy duty engine at 14 bar brake mean effective pressure (BMEP) at similar combustion phasing. Effects of pilot mass ratio and EGR on heat release rates, cylinder temperatures, ignition delay (ID) and combustion duration (CD) were examined, relating with emissions variations with applications of the two fuels. Soot mass and particle number emissions were slightly lower with gasoline than with diesel, resulting in a more favorable NOx-soot trade-off with gasoline like other reports. Contrary to other findings in the literature, gasoline and diesel soot samples presented similar particle distribution shapes, carbon crystalline structures and primary particle sizes, regardless of fuel type and EGR rate. Consequently, the current result proposes that soot particles have undergone similar soot formation and oxidation processes despite reactivity difference and oxygen availability under the examined high-load MCC with similar combustion phases.