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1. INTRODUCTION

Fuel oils are refi ned from crude petroleum by fractional distillation. Petroleum products are usually grouped into three categories viz. light distillates (LPG, naphtha and gasoline), middle distillates (kerosene and diesel), heavy distillates & residuum (heavy fuel oil, lubricating

oils, wax, asphalt, etc.). This classifi cation is based on the way crude oil is distilled and separated into fractions (called distillates and residuum). Diesel fuel is categorised under middle distillate in the process of refi ning of crude oil. Middle distillates include kerosene, aviation fuel & diesel fuel. Diesel fuel is about 18% heavier than gasoline and consists mainly

Carbon Number Distribution by Gas Chromatography for Identifi cation of Outlying Diesel Sample

M A Bawase, S D Reve, S V Shete and M R Saraf

The Automotive Research Association of India, Kothrud, Pune-411038Email: bawase.aml@araiindia.com

Abstract: Fuel oils are refi ned from crude petroleum by fractional distillation and are usually grouped into three categories including light distillates, middle distillates, heavy distillates & residuum. Middle distillates, which include fractions of kerosene and diesel, have overlapping carbon number distribution viz., C9 to C15 for kerosene & C12 to C22 for diesel. Physico-chemical properties of fuel are specifi ed, as quality of diesel fuel directly affects engine performance, exhaust emissions and safety aspects. Most of the physico-chemical properties are dependent on the composition of hydrocarbons present in the fuel.Diesel samples were analyzed through separation of various hydrocarbons by using gas chromatograph with fl ame ionization detector. Hydrocarbons were identifi ed by comparing the peaks obtained with the peaks for different standard hydrocarbons. Peak areas obtained for each hydrocarbon in the sample was considered proportional to the amount of that hydrocarbon. The results obtained for analysis of 26 number of samples show the distribution of various fractions (like <C10, C10-C12, C12-C15, C15-C20 and > C20) across the samples. Same samples were subjected to distillation characteristics test. The results obtained are in agreement when compared with the distillation characteristics vis-à-vis the carbon number distribution. Some of the samples were found to be distinctly different from the set of other samples.The results from this exercise provide information on relative composition of the light, medium and heavy fractions in each fuel sample and subsequently an outlying sample can be identifi ed.

Keywords: Diesel fuel, carbon number distribution, diesel fractions, gas chromatograph with fl ame ionization detector

AdMet 2012 Paper No. CM 003

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of hydrocarbons that ranges from C12 to C22, with various confi gurations of hydrogen atoms attached to carbon atoms. Gasoline is usually in C7 to C11 ranges, while kerosene, used for jet engine fuel, is weighted just between diesel & gasoline in C9 to C15 range. These fuels contain paraffi ns (alkanes), cycloparaffi ns, aromatics & olefi ns [1, 2]. Thus, major distillate fractions of diesel & kerosene are having overlapping carbon number distribution e.g. kerosene contains C9 to C15 carbon numbers & diesel contains C12 to C22 carbon numbers.

Diesel fuel is a complex mixture of normal, branched, cyclic alkanes, aromatic compounds with small amounts of alkenes obtained from the middle-distillate and gas-oil fraction during petroleum separation. At room temperature, diesel fuels are generally moderately volatile, slightly viscous, fl ammable, brown liquids with a kerosene-like odour. The boiling ranges are usually between 140 and 3850C. The quality and composition of diesel fuel infl uence the emissions of pollutants from diesel engines considerably.

Physico-chemical properties of fuel are specifi ed, as quality of diesel fuel directly affects engine performance, exhaust emissions and safety aspects. Most of the physico-chemical properties are dependent on the composition of hydrocarbons present in the fuel. Therefore, study of diesel fuel composition is important to understand the relationship between fuel composition and performance parameters. A major problem is the separation and identifi cation of pure compounds or classes of compounds from the complex hydrocarbon mixtures in diesel fuel.

In order to predict the phase behavior of crude oil mixtures accurately, some description of the oil composition is required. One common laboratory procedure for describing oil is simulated distillation, which uses chromatography to estimate the carbon number distribution of oil. The simulated distillation technique is based on the fundamental assumption that individual non-polar hydrocarbon components of a sample elute in the order of their boiling points from a GC column coated with non-polar (hydrocarbon-like), stationary phase.

The elution, or retention, time is dependent upon vapor pressure of the component and its affi nity for the stationary phase. The elution time of a component in GC depends on the volatility of the component in the carrier gas. Volatility, in turn, is controlled by temperature. Therefore, during a typical GC run for a crude oil, the oven temperature is gradually increased so that heavier and heavier crude oil components, which have a wide range of boiling points, are eluted.

In this paper, a simple method for identifi cation of outlying samples from the set of samples based on carbon number distribution is presented. Results obtained for analysis of 26 numbers of diesel samples through separation of various hydrocarbons by using high resolution gas chromatograph with fl ame ionization detector are discussed.

2. LITERATURE SURVEY

Various studies report evaluation of petroleum oils for carbon number distribution using different techniques. A brief account of the studies is presented below.

Simulated distillation was reported early in the 1960s by Eggertsen et al. [1] and Green et al. [2, 3] as a method of simulating the time-consuming laboratory-scale physical distillation procedure by using GC. Similarly, S.C. Thomas, J.P. Kleiman and V.O. Brandt identifi ed compositions of hydrocarbons in two commercial diesel fuels using a combination of preparative High Performance Liquid Chromatography and Gas Chromatography-Mass Spectroscopy [4]. In an another study, Grzegorz Zadora, Rafal Borusiewicz, Janina Zieba-Palus have showed that the observed differences in the analysed samples of kerosene and a diesel fuel, which were weathered at the time of burning, were systematic and signifi cant. Therefore, it was possible to distinguish them on the basis of information about the relative content of n-alkanes (C11H24–C15H32) when statistical methods (cluster analysis and likelihood ratio approach) were applied [5].

An, Gao and Chou [6] determined the contents of n-paraffi n and carbon number

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distribution in n-paraffi n wax of two diesel oils of Daqing oil fi eld by gas chromatography mass spectrometry and FID with FID temperature 3100C, column temperature increased from 800C to 2900C at 50C/min. Results showed that n-paraffi n was separated successfully from each other. In another study [7], carbon number distributions of 26 stock tank oils were determined by simulated distillation using gas chromatography and supercritical fl uid chromatography (SFC) using high-pressure CO2 as the carrier fl uid. Carbon number distributions determined by the two methods were equivalent within normal experimental scatter. Comparison of the fraction of each crude oil eluted in the GC and SFC analyses indicated that for most oils, a signifi cantly larger fraction of the oil eluted in an SFC analysis. It was observed that, the advantage of simulated distillation by SFC is that there was no hydrocarbon decomposition at high temperature. Review of analytical techniques for simulated distillations like gas chromatography and supercritical fl uid chromatography is presented by Peaden [8]. Dahan et al [9] also compared simulated distillation by GC and SFC and observed good agreement between the GC and SFC data in the range of 4500C to 7310C. Neer and Deo [10] found that capillary gas chromatography permits the analyses of samples containing higher boiling compounds at temperatures similar to those employed in packed-column chromatography. They developed a procedure that allows for a high-resolution characterization of the C5-C90 fraction of the oil by using a short (5 m) capillary column to obtain carbon number distributions of compounds from C20-C90. The results were found to be in agreement in the overlapping region of the two oils analyzed. Vendeuvre et al, [11] compared two-dimensional gas chromatography (GC X GC) with gas chromatography, liquid chromatography and mass spectroscopy for group type separation and detailed hydrocarbon analysis and simulated distillation and found the results in line. Application of high- temperature simulated distillation (HTSD) for hydrocarbon components covering boiling range 36–750°C, which covers the n-alkanes with a chain length of about C5–C120 is discussed by Villalanti et al [12].

3. METHODOLOGY

Total twenty six numbers of diesel samples received for analysis were analyzed for their carbon number distribution using high resolution gas chromatograph (HRGC) with fl ame ionization detector (FID). When a diesel sample was injected in to a gas chromatographic column, the constituents of hydrocarbons were separated in the order of increased boiling points and detected by FID detector.

The experiments were performed using Perkin Elmer Auto System XL High Resolution Gas Chromatograph (Fig.1) with PONA-Capillary Column, 100m, 0.25mm ID, 0.5�m coating thickness.

Fig.1. High Resolution Gas Chromatograph (HRGC) with Flame Ionization Detector (FID)

The chromatographic analysis was conducted according to the following program- Initial temperature of 400C maintained for 5min, increase at the rate of 40C per min to 2800C and maintained for 22 min at 2800C. Helium was used as a carrier gas at a pressure 48psi during the analysis injector temperature of 2300C and detector (FID) temperature of 3000C were maintained.

For the identifi cation of peaks of carbon number, the instrument was calibrated using representative individual carbon number standards (C7-heptane, C9-nonane, C10-decane, C11-undecane, C18-octadecane, C20-ecosane).

Carbon number distribution of various fractions in the diesel samples was assumed as given below:

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• Naphtha Fraction: < C10

• Gasoline Fraction: C11 - C12

• Kerosene Fraction: C13 - C15

• Diesel Fraction: C16 - C20

• Heavy Oil Fractions: >C20 Peak areas of each of the above carbon

number fraction were evaluated. Peak area obtained for each hydrocarbon fraction in the sample was considered proportional to the amount of that hydrocarbon in the fuel and accordingly % distribution of each carbon fraction in a fuel was determined.

The diesel samples were also analyzed for distillation characteristics (ASTM D86) using automatic distillation unit (Fig.2) for evaluation of initial boiling point, temperature for various recovery volumes and fi nal boiling point.

Since the distillation characteristics depend on the hydrocarbon fractions present in the fuel, this data can be utilized for assessment vis-à-vis the carbon number distribution data.

Fig.2. Automatic Distillation Unit

4. RESULTS AND DISCUSSION

Gas chromatograph obtained for calibration standards, a few representative samples are presented in Fig.3 and Fig.4.

Chromatogram at Fig. 3 (a) presents calibration results obtained for individual carbon number standards viz. C7-heptane, C9-nonane, C10-decane, C11-undecane, C18-octadecane, C20-ecosane. Fig. 3 (b) to (d) represent the chromatograms of samples.

Fig.3. Gas Chromatoraphs of (a) Calibration Standards, (b)- (e) Samples

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It can be observed that the carbon number distribution patterns of the chromatograms are very similar to each other. Fig. 3 (e) represents overlay of a few representative samples. As can be seen from the overlay chromatogram, the samples are following a similar pattern with respect to the peaks obtained for individual carbon numbers.

Similarly, Fig.4 (f) to (i) represent the chromatograms of some of the samples. It can be observed that the carbon number distribution patterns of the chromatograms are distinctly different from each other. Therefore, these samples can be considered as out-lying samples and may be subjected to further detailed investigations.

Based on the gas chromatograms for the samples, % distribution of each carbon fraction in a fuel was determined through the peak area obtained for each hydrocarbon fraction in the samples and is presented in Table 1. Also, the distillation characteristics i.e. temperature in degree Celsius for various recovery volumes of diesel samples in terms of their initial boiling point, temperature for 50% recovery and 90% recovery are reported.

Fig.4. Gas Chromatoraphs (f)- (i) of out-lying samples

Table1 Percent Distribution of Carbon Fractions and Distillation Characteristics of

Diesel Samples

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From Table 1, it can be observed that sample S1 to S21 have a similar carbon number distribution pattern and distillation characteristics were also found to be in agreement with the carbon number distribution across the sample. While in case of samples S22 to S26, it is observed that the carbon number distribution is quite different from the rest of the samples, especially lower carbon number groups. Distillation characteristics also support the data. For example, in case of sample number S22 to S24, lower carbon number (high volatile) fractions were found to be on lower side and the distillation characteristics show higher initial boiling point (IBP). On the other hand, in case of samples S25 and S26, the lower carbon fraction was higher and IBP was lower.

Distribution of various fractions (like <C10, C11-C12, C13-C15, C16-C20 and > C20) across the diesel samples can be observed from Fig.5.

the light, medium and heavy fractions in each fuel sample.

• Relative composition of various carbon fractions can be evaluated and subsequently an outlying sample can be identifi ed for further detailed investigations.

• Analysis of 26 number of samples was carried out for distribution of various fractions based on carbon numbers (like <C10, C11-C12, C13-C15, C16-C20 and > C20). Results show variation across the samples and some of the samples were found to be distinctly different from the set of other samples.

• The results obtained are in agreement when compared with the distillation characteristics vis-à-vis the carbon number distribution.

6. REFERENCES

1. F.T. Eggertsen, S. Groennings and J.J. Holst, “Analytical Distillation by Gas Chromatography”, Anal. Chem., 1960, 32, 904–909.

2. L. E. Green and J. C. Worman, “Simulated Distillation of High Boiling Petroleum Fractions”, Anal. Chem., 1965, 37, 1620–1621.

3. L.E. Green, L.J. Schumauch and J.C. Worman, “Simulated Distillation by Gas Chromatography”, Anal. Chem., 1964, 36, 1512–1516.

4. S.G. Thomas, J.P. Kleiman and V.O. Brandt, “Analysis of commercial Diesel Fuels by Preparative High Performance Liquid Chromatography and Gas Chromatography-Mass Spectrometry”.

5. Grzegorz Zadoa, Rafal Borusiewicz and Janina Zieba-Palus, “Differentiation between weathered kerosene and diesel fuel using automatic thermal desorption- GC-MS analysis and the likelihood ratio approach”, J. Sep. Sci., 2005, 28, 1467-1475.

6. Hong An, Shugang Gao and Jingyu

Fig.5. Distribution of Carbon Fractions in Diesel Samples

It can be observed that there is signifi cant variation in a group based on carbon numbers especially for the lower carbon number groups like below C10 and between C10 and C12 in case of some samples and these samples can be considered as out-lying samples from a set of samples tested.

5. SUMMARY

• Gas chromatograph with fl ame ionization detector can be used for preliminary analysis of diesel samples to provide information on relative composition of

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Chou, Determination of n-paraffi n in DaQing diesel oil by gas chromatography mass spectrometry, Remote Sensing, Environment and Transportation Engineering (RSETE), 2011 International Conference.

7. Stadler, M.P., Deo, M.D., Orr Jr., F.M. and Stanford U, Crude Oil Characterization Using Gas Chromatography and Supercritical Fluid Chromatography, SPE International Symposium on Oilfi eld Chemistry, 1993, 2-5 March.

8. Peaden, P. A., “Simulated distillation of petroleum and its products by gas and supercritical fl uid chromatography: A review”, Journal of High Resolution Chromatography, 1994, Volume 17, Issue 4, pages 203–211.

9. Laure Dahan., Didier Thiebaut, Fabrice Bertoncini, Didier, Espinat and Alain Quignard, “Simulated distillation of heavy fraction by capillary supercritical fl uid chromatography. Evaluation and comparison with GC”, Am. Chem. Soc., Div. Fuel Chem., 2004, 49 (1), 18.

10. Lawrence A. Neer and Milind D. Deo, “Simulated Distillation of Oils With a Wide Carbon Number Distribution”, Journal of Chromatographic Science, 1995, Volume 33, 133-138.

11. Colombe Vendeuvre, Rosario Ruiz-Guerrero, Fabrice Bertoncini, Laurent Duval, Didier Thiebaut, Marie-Claire Hennion, “Characterisation of middle-distillates by comprehensive two-dimensional gas chromatography (GC XGC): A powerful alternative for performing various standard analysis of middle-distillates”, Journal of Chromatography A, 2005, 1086, 21-28.

12. Dan C. Villalanti, Joseph C. Raia, and Jim B. Maynard, High-temperature Simulated Distillation Applications in Petroleum Characterization, in Encyclopedia of Analytical Chemistry; R.A. Meyers (Ed.), 6726–6741.