Molecular-Level Characterization of Refinery Streams by High

Article pubs.acs.org/EF

Molecular-Level Characterization of Refinery Streams by HighResolution Mass Spectrometry Vatsala Sugumaran,* Hillol Biswas, Anil Yadav, Jayaraj Christopher, Vivekanand Kagdiyal, Mitra Banu Patel, and Biswajit Basu Research and Development Centre, Indian Oil Corporation Limited, Sector 13, Faridabad, Haryana 121007, India ABSTRACT: Compositional changes of hydrocarbon fractions affect the physical properties and performance for a specific application. Various techniques, such as liquid chromatography and nuclear magnetic resonance spectroscopy, are normally used for determination of hydrocarbon analysis in petroleum fractions. These techniques provide limited information regarding the hydrocarbon classes. Mass spectrometry offers a unique advantage over these techniques by providing detailed information on hydrocarbon classes present in samples. Commonly used methods in mass spectrometry provide 19, 22, and 33 classes of hydrocarbons in petroleum fractions. These methods are useful in understanding relative changes in composition in the samples during further processing in refineries. The major problem with these methods is validation of results, which poses a challenge to researchers. In the present study, a high-resolution mass spectrometry (HR-MS) technique has been optimized to characterize the petroleum fractions in terms of 33 hydrocarbon classes (HC33), comprising 5 classes of saturates, 13 classes of aromatics, and 15 classes of sulfur aromatics, for detailed hydrocarbon-type analysis. About 40 samples covering a wide range of petroleum streams, such as light cycle oil (LCO), clarified light oil (CLO), and vacuum gas oil (VGO), in the boiling range of 170−650 °C have been analyzed for 33 classes of hydrocarbons. To validate the results, a correlation of sulfur compounds by HC33 with the total sulfur content as determined by wavelength-dispersive X-ray fluorescence (WDXRF) has been carried out. The saturate content was determined using saturates, aromatics, resins, and asphaltenes (SARA) by thin-layer chromatography−flame ionization detection (TLC−FID) and compared to that obtained by HC33 for the samples. Results obtained from HC22 and HC33 methods were also correlated through analysis of variance for saturate, aromatic, and sulfur aromatic classes. The observed F value for the groups is less than F critical, indicating there is no significant difference between the two methods. Further, on the basis of mass spectrometry analysis, a case study on the importance of detailed hydrocarbon-type analysis (33 classes) for problem solving in VGO hydroprocessing has been reported. spray ionization (ESI),5 to generate molecular ions with fewer fragments for analysis of complex petroleum fractions using a peak analysis approach. Molecular characterization and compositional analysis of middle distillates using gas and/or liquid chromatography with field ionization mass spectrometry (FIMS) has also been discussed by many authors.6−8 A method for analysis of composition of hydrocarbons in diesel fuel has been reported by Ogawa9 using FIMS to study the influence of various MS conditions and reasons for different properties with the same H/C ratios but difference in end-point carbon number distribution. Most of the ASTM methods of characterization of petroleum streams by MS are based on electron impact (EI) mode and require prior separation of samples into saturates and aromatics using column chromatography. Earlier developed methods by Gallegos et al.10 used a single matrix for calculation of 19 classes of hydrocarbons without column fractionation. Further, the analysis has been expanded to include 22 classes by Teeter11 based on eight standard matrices with appropriate selection of matrices based on average molecular weight or simulated distillation of the sample for quantitation. Bouquet and Brument 12 had successfully developed a method based on high-resolution mass spectrom-

1. INTRODUCTION Analysis of the petroleum fraction poses a huge challenge to analytical chemists because of the presence of a large number of compounds with similar chemical compositions. In the present hydrocarbon scenario, because of the global depletion of crude oil, the available crude oils are rich in aromatic and heteroaromatic compounds containing sulfur, nitrogen, and oxygen. The abundance of these aromatic compounds with nitrogen and sulfur atoms in the crude oil not only has an adverse effect, such as catalyst poisoning, but also has a strong influence on the design and operation of secondary refinery processes. Under these circumstances, it is important to have knowledge about the distribution of hydrocarbon classes and heterocyclic aromatic classes before processing these feedstocks. Detailed characterization of feed and products of refinery is important to develop and optimize processes, understand reaction mechanisms to solve refining process problems, and evaluate the effect of compositional changes on physical properties of products. For the past 5 decades, the mass spectrometric technique has played a vital role in molecular-level characterization of complex petroleum fractions in terms of hydrocarbon classes and component analysis.1 Peak analysis and type analysis are widely used for such purposes. Mass spectrometry (MS) uses several ionizations, such as field ionization (FI),2 fast atom bombardment (FAB),3 chemical ionization (CI),4 and electro© XXXX American Chemical Society

Received: November 21, 2014 Revised: April 8, 2015

A

DOI: 10.1021/ef5017279 Energy Fuels XXXX, XXX, XXX−XXX

Article

Energy & Fuels Table 1. Detailed Hydrocarbon-Type Analysis (33 Classes) of CLO and LCO Samples hydrocarbon class (%, w/w) paraffins monocycloparaffins dicycloparaffins tricycloparaffins tetracycloparaffins saturates aromatic hydrocarbons alkylbenzenes benzocycloparaffins benzodicycloparaffins diaromatics naphthalenes acenaphthenes, biphenyls acenaphthylenes, fluorenes triaromatics phenanthrenes tetraromatics pyrenes chrysenes pentaromatics benzopyrenes aromatics benzothiophenes

dibenzothiophenes

naphthobenzothiophenes

disulfides

LCO-I

LCO-II

CLO-I

CLO-II

CnH(2n + 2) CnH(2n) CnH(2n − 2) CnH(2n − 4) CnH(2n − 6)

general formula

9.5 5.0 1.4 BDL BDL 15.9

8.6 0.1 0.1 BDL BDL 8.8

7.3 1.4 5.0 0.2 BDL 13.9

0.1 BDLa 0.3 0.2 0.2 0.8

CnH(2n − 6) CnH(2n − 8) CnH(2n − 10)

17.9 10.4 BDL

26.1 7.4 0.1

7.0 1.2 0.6

BDL BDL BDL

CnH(2n − 12) CnH(2n − 14) CnH(2n − 16)

39.0 0.4 2.6

52.0 BDL BDL

2.0 2.4 3.7

BDL 0.1 4.0

CnH(2n − 18) CnH(2n − 20)

4.6 0.2

0.1 0.2

8.1 7.0

13.4 4.2

CnH(2n − 22) CnH(2n − 24) CnH(2n − 26)

0.6 BDL 0.1

0.1 0.1 BDL

10.3 1.1 1.5

12.5 0.2 BDL

CnH(2n − 28) CnH(2n − 30)

BDL BDL 75.8 3.8 1.4 0.3 1.6 0.4 BDL BDL BDL 0.4 0.2 0.2 BDL 0.1 BDL BDL 8.4

BDL BDL 86.1 4.3 0.1 0.2 0.1 0.1 BDL BDL BDL 0.1 0.1 BDL BDL BDL BDL BDL 5.0

1.4 0.4 46.7 8.3 12.0 5.1 7.6 2.8 BDL 1.5 0.3 0.2 0.2 0.7 BDL 0.1 BDL BDL 38.8

1.5 0.5 36.4 9.7 15.0 8.3 17.5 5.0 0.1 2.9 1.8 1.3 0.4 0.8 BDL BDL BDL BDL 62.8

CnH(2n − 10)S/H(2n − 20) CnH(2n − 12)S/H(2n − 22) CnH(2n − 14)S/H(2n − 24) CnH(2n − 16)S/H(2n − 26) CnH(2n − 18)S/H(2n − 28) CnH(2n − 20)S/H(2n − 30) CnH(2n − 22)S/H(2n − 32) CnH(2n − 24)S/H(2n − 34) CnH(2n − 26)S/H(2n − 36) CnH(2n − 28)S/H(2n − 38) CnH(2n − 30)S/H(2n − 20)S CnH(2n − 32)S/H(2n − 22)S CnH(2n − 34)S CnH(2n − 36)S CnH(2n − 38)S

sulfur aromatics a

BDL = below detection limit (0.1%) for the HC33 method.

(UV) spectra of middle distillates and vacuum gas oils (VGOs) with HR-MS-based hydrocarbon-type analysis by Baldrich Ferrer and Novoa Mantilla.15 In the recent years, identification and characterization of aromatics and heteroaromatics in petroleum distillates has been reported using Fourier transform infrared spectroscopy/mass spectrometry (FTIR/MS) at very high resolution.16−18 Roussis and Fitzgerald19 have developed a HR-MS method for exhaustive determination of hydrocarbon compound types by sequential comparison of the theoretical masses of compounds using low electronvolts and chemical ionization using benzene and carbon disulfide as reagent compounds for charge exchange. This method gives information on elemental analysis, compound class analysis, z-series distributions for each compound class, and molecular weight distribution in z series. Group types, such as alkanes, naphthenes, and sulfur- and oxygen-containing species, present in oils have been analyzed by a two-dimensional gas

etry (HR-MS) to characterize 33 hydrocarbon classes in heavy petroleum cuts ranging up to 650 °C. This method throws light on the presence of 15 sulfur aromatic classes, including additional sulfide and disulfide classes, compared to only four sulfur aromatic classes (thiophenes, benzothiophenes, dibenzothiophenes, and naphthobenzothiophenes) in the method developed by Teeter. Fafet et al.13 described a new development in MS for grouptype analysis of petroleum cuts in terms of sulfur aromatics by applying correction for accurate quantification of sulfur compounds and compared the results obtained to those by gas chromatography coupled to a sulfur-specific detector, such as chemiluminescence or atomic emission. In another work from the same authors, an inlet system for introducing the sample in the source of a mass spectrometer for hydrocarbontype analysis of heavier cuts has been described.14 Chemometric analysis has been applied for correlation of ultraviolet B


Article

Energy & Fuels Table 2. Hydrocarbon-Type Analysis (33 Classes) of VGO Feed Samples from Four Different Refineries hydrocarbon class (%, w/w) paraffins monocycloparaffins dicycloparaffins tricycloparaffins tetracycloparaffins saturates aromatic hydrocarbons alkylbenzenes benzocycloparaffins benzodicycloparaffins diaromatics naphthalenes acenaphthenes, biphenyls acenaphthylenes, fluorenes triaromatics phenanthrenes tetraromatics pyrenes chrysenes pentaromatics benzopyrenes aromatics benzothiophenes

dibenzothiophenes


disulfides

REF-1

REF-2

REF-3

REF-4


general formula

13.0 12.6 17.1 1.2 BDLa 43.9

6.3 12.4 12.0 0.3 BDL 31.0

14.7 22.1 20.6 0.5 BDL 57.9

6.8 15.5 14.2 0.3 BDL 36.8

CnH(2n − 6) CnH(2n − 8) CnH(2n − 10)

14.3 5.5 5.5

10.8 2.8 2.4

11.4 3.3 3.5

12.8 4.1 2.7

CnH(2n − 12) CnH(2n − 14) CnH(2n − 16)

6.8 3.5 4.8

2.4 2.2 3.9

3.2 2.0 3.8

2.6 2.1 3.1

CnH(2n − 18) CnH(2n − 20)

3.8 2.0

3.6 6.2

3.1 2.0

3.1 4.1

CnH(2n − 22) CnH(2n − 24) CnH(2n − 26)

2.3 BDL 0.2

2.5 0.7 1.3

1.7 0.1 0.3

2.7 0.7 1.3

CnH(2n − 28) CnH(2n − 30)

0.2 BDL 48.9 2.5 2.7 0.8 0.8 0.3 BDL 0.1 BDL BDL 0.1 BDL BDL BDL BDL BDL 7.3

1.6 0.8 41.2 8.1 3.8 2.4 6.9 2.9 BDL 1.2 0.8 0.7 0.4 0.6 0.1 BDL BDL BDL 27.9

0.4 0.1 34.9 2.0 2.2 0.6 1.4 0.6 BDL 0.2 BDL 0.1 BDL BDL BDL BDL BDL BDL 7.1

1.4 0.8 41.5 4.8 3.5 1.7 4.4 2.3 BDL 1.6 0.7 0.8 0.7 0.4 0.4 0.3 BDL BDL 21.6


sulfur aromatics a


chromatography system (GC × GC) coupled with time of flight/mass spectrometry (ToF/MS) by selecting specific fragment masses as reported by van Deursen et al.20 Briker et al.21 have discussed the results of hydrocarbon-type analyses of middle distillates by high-voltage, low-resolution electron impact gas chromatography−mass selective detection (HVLREI GC−MSD) and gas chromatography−field ionization mass spectrometry (GC−FIMS) techniques. The authors have further compared the sulfur aromatic types obtained by the above methods to those determined using gas chromatography−flame ionization detection/sulfur chemiluminiscent detection (GC−FID/SCD). In the present study, the HR-MS technique has been used to characterize the petroleum fractions for 33 classes, comprising 5 classes of saturates, 13 classes of aromatics, and 15 classes of sulfur aromatics. The study highlights the results of 33 classes of hydrocarbons in different petroleum fractions ranging from

diesel to VGO. The samples were also analyzed for 22 classes (HC22) as per the method developed by Teeter, and the results were compared against those obtained for 33 classes. The study brings out the importance of detailed molecular-level characterization of hydrocarbon-type analysis in terms of HC33 and HC22 classes by HR-MS in different refinery feedstock and products. Feed and product samples of heavy aromatic cuts, such as light cycle oil (LCO) and clarified light oil (CLO) samples, covering a wide range of hydrocarbon classes, have been taken for analysis to study the molecular-level changes taking place during the hydroprocessing. The study also includes validation of HC33 with the sulfur and saturate contents estimated by wavelength-dispersive X-ray fluorescence (WDXRF) and thin-layer chromatography−flame ionization detection (TLC-FID) techniques, respectively. C


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Energy & Fuels Table 3. Hydrocarbon-Type Composition (33 Classes) of Unconverted Oil and R1 Outlet Streams hydrocarbon class (%, w/w) paraffins monocycloparaffins dicycloparaffins tricycloparaffins tetracycloparaffins saturates aromatic hydrocarbons alkylbenzenes benzocycloparaffins benzodicycloparaffins diaromatics naphthalenes acenaphthenes, biphenyls acenaphthylenes, fluorenes triaromatics phenanthrenes tetraromatics pyrenes chrysenes pentaromatics benzopyrenes aromatics benzothiophenes

dibenzothiophenes


disulfides

UCO-1

UCO-2

UCO-3

UCO-4

R1-1

R1-2

R1-3

R1-4


general formula

25.3 43.7 17.6 0.4 BDL 87.0

26.1 46.5 14.6 0.8 BDL 88.0

25.4 44.6 16.9 0.4 BDL 87.3

27.9 46.8 13.1 0.9 BDL 88.7

17.2 32.7 18.1 0.1 BDL 68.1

13.8 27.7 17.4 0.3 BDL 59.2

16.4 33.2 18.9 BDLa BDL 68.5

18.0 33.6 18.7 BDL BDL 70.3

CnH(2n − 6) CnH(2n − 8) CnH(2n − 10)

6.9 1.2 0.7

5.8 1.0 0.1

6.3 1.4 0.5

5.7 0.7 0.1

13.4 5.3 2.2

18.8 7.0 2.7

14.4 4.6 3.1

13.7 3.8 2.6

CnH(2n − 12) CnH(2n − 14) CnH(2n − 16)

0.6 0.3 0.4

0.4 0.9 0.2

0.9 0.2 0.4

0.8 0.3 0.5

1.5 1.4 1.1

1.8 1.6 2.1

0.2 2.2 1.3

1.1 1.0 1.2

CnH(2n − 18) CnH(2n − 20)

0.2 0.3

0.2 0.6

0.2 0.2

0.1 0.4

1.1 0.8

0.6 0.8

0.7 1.4

0.8 1.4

CnH(2n − 22) CnH(2n − 24) CnH(2n − 26)

0.5 BDL BDL

0.5 BDL BDL

0.6 0.1 BDL

0.1 0.2 0.1

0.5 0.1 0.1

1.3 0.2 0.2

0.2 0.3 0.1

BDL 0.4 0.3

CnH(2n − 28) CnH(2n − 30)

BDL BDL 11.1 0.3 0.5 0.2 0.6 0.1 BDL BDL 0.1 0.1 0.1 BDL BDL BDL BDL BDL 2.0

0.2 BDL 9.9 0.5 0.6 0.1 0.2 0.3 BDL 0.1 BDL 0.1 BDL 0.1 BDL BDL BDL BDL 2.0

BDL 0.1 10.9 0.3 0.5 0.4 0.3 0.1 BDL BDL BDL 0.1 0.1 BDL BDL BDL BDL BDL 1.8

BDL BDL 9.0 0.5 0.5 0.3 0.2 BDL BDL BDL BDL 0.1 0.3 BDL BDL BDL BDL BDL 1.9

0.1 0.1 27.7 0.7 0.9 0.4 0.3 0.2 BDL BDL BDL 0.1 0.1 BDL BDL BDL BDL BDL 2.7

0.1 0.1 37.3 0.8 1.4 0.5 0.3 0.3 BDL 0.1 BDL BDL BDL BDL BDL BDL BDL BDL 3.4

0.1 0.1 28.7 0.8 0.4 0.3 0.5 0.1 BDL 0.1 0.1 BDL 0.3 BDL BDL BDL BDL BDL 2.6

0.2 0.1 26.6 0.8 0.4 0.3 0.5 0.3 BDL BDL 0.2 0.3 0.1 0.1 BDL BDL BDL BDL 3.0


sulfur aromatics a

BDL = below detection limit (0.1%) for the HC33 method. of hydrogen gas was kept at 160 mL/min, and that of air was kept at 2000 mL/min. The chromrods used were silica-coated SIII type, with a pore diameter of 60 Å and a particle size of 5 μm. Sample solutions at the level of approximately 2% (w/v) were prepared by dissolution in dichloromethane. The IP 469 method of SARA analysis has been adopted for the chromrod development,22 which includes a three-stage developmental process. The first stage of development was carried out in hexane (10 cm); the second stage of development was carried out in toluene (5−6 cm); and the third stage of development was carried out in a 95:5 ratio of chloroform/methanol (2.5 cm). Each set of rods was dried for 3 min and then pyrolyzed over FID at a constant scan speed of 0.30 cm/s. The chromatogram was then analyzed for SARA classes. 2.3. WDXRF. Sulfur in the samples was analyzed by WDXRF (4 kW) from M/s Petroaxis, PANalytical, Netherlands, as per the ASTM D2622 method.23 Calibration of the equipment was carried out using sulfur oil standards (Conostan, Champlain, NY) in the concentration range of parts per million to percent level. The net intensity of sulfur versus the concentration of the standards was used for calibration, and

2. EXPERIMENTAL SECTION 2.1. HC33 and HC22 Analysis by HR-MS. Samples were analyzed on Autospec Ultima HR-MS using the All Glass Heated Inlet System (AGHIS). The instrument was tuned for dynamic resolution of more than 10 000 to carry out HC33 analysis and more than 6000 for HC22 analysis. Calibration of the mass spectrometer in the mass range of 50−500 Da was carried out using perfluorokerosene (PFK) as a reference compound for calibration of masses. Ionization of the sample was carried out at 70 eV electron impact. The scanning of the magnet was set at a speed of 75 s/decade. The temperature of the AGHIS bulb was set at 400 °C. A total of 3 μL of the sample was introduced through the AGHIS. The source temperature was maintained at 250 °C. Processing of the raw data was carried out by a PCMASPEC suite of software for 33 and 22 classes of hydrocarbons. Each sample was analyzed in triplicate and data-averaged. 2.2. Saturates, Aromatics, Resins, and Asphaltenes (SARA) Analysis. The hydrocarbon-type analysis in terms of SARA was accomplished using a Iatroscan MK-6 instrument, equipped with FID and interfaced with a computerized data acquisition system. The flow D


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Energy & Fuels Table 4. Hydrocarbon-Type Analysis (33 Classes) of FCC Feed and Products hydrocarbon class (%, w/w) paraffins monocycloparaffins dicycloparaffins tricycloparaffins tetracycloparaffins saturates aromatic hydrocarbons alkylbenzenes benzocycloparaffins benzodicycloparaffins diaromatics naphthalenes acenaphthenes, biphenyls acenaphthylenes, fluorenes triaromatics phenanthrenes tetraromatics pyrenes chrysenes pentaromatics benzopyrenes aromatics benzothiophenes

dibenzothiophenes


disulfides

HSVGO feed

(270−340 °C) product

(340 °C+) product


6.6 11.2 11.5 BDL BDL 29.3

0.3 0.1 BDL BDL BDL 0.4

0.1 BDLa 0.3 0.2 0.2 0.8

CnH(2n − 6) CnH(2n − 8) CnH(2n − 10)

12.6 3.5 2.7

2.7 1.6 2.2

BDL BDL BDL

CnH(2n − 12) CnH(2n − 14) CnH(2n − 16)

2.3 2.2 3.3

60.1 BDL 1.1

BDL BDL 4.0

CnH(2n − 18) CnH(2n − 20)

3.5 5.7

4.6 BDL

13.4 4.2

CnH(2n − 22) CnH(2n − 24) CnH(2n − 26)

2.3 0.9 1.5

BDL BDL BDL

12.5 0.2 BDL

CnH(2n − 28) CnH(2n − 30)

1.4 1.0 42.9 8.3 3.8 2.2 6.0 2.7 BDL 1.6 1.0 0.8 0.5 0.6 0.1 0.1 BDL BDL 27.7

BDL BDL 72.3 21.2 0.1 0.2 5.6 BDL BDL 0.1 BDL BDL BDL BDL BDL BDL BDL BDL 27.2

1.5 0.5 36.3 9.7 15.0 8.3 17.5 5.0 BDL 2.9 1.8 1.3 0.5 0.8 BDL BDL BDL BDL 62.8

general formula


sulfur aromatics a


the amount of sulfur in samples was determined using the calibration curve.

aromatic content. Similarly, the distribution of hydrocarbon classes in two CLO samples by HC33 analysis shows variations in aromatic compound classes, as depicted in Table 1. These detailed hydrocarbon-type investigative analyses are very useful for refiners in the process optimization as well as in identifying the source of feedstock in certain cases. 3.1.2. Detailed Compositional Analysis of VGO Samples. HC33 analysis provides the detailed variation in the composition of 33 classes of hydrocarbons in VGO samples obtained from four different refineries, REF-1, REF-2, REF-3, and REF-4, presented in Table 2. Table 3 provides results of HC33 analysis of four different VGO intermediates, reactor 1 outlet (R1-1−R1-4), and four different unconverted oils (UCO-1−UCO-4) from different hydroprocessing plants generated during hydroprocessing. Another fluidized catalytic cracking (FCC) feedstock is high-sulfur vacuum gas oil (HSVGO), which also contains 10−20% of short residue. A

3. RESULTS AND DISCUSSION 3.1. Hydrocarbon-Type Analysis. 3.1.1. Analysis of CLO and LCO by HC33. Aromatic-rich diesel range samples (120− 375 °C), such as LCO, and higher cuts (320−540 °C), such as CLO, from two different sources were analyzed for 33 classes of hydrocarbon types. Each sample was analyzed in triplicate, and average values of three experiments were reported. Data below 0.1% have been considered as below detection limit (BDL) because of the low signal-to-noise ratio (less than 3:1) of fragment ions. Table 1 shows the detailed distribution of hydrocarbon classes obtained for the four samples. Table 1 clearly reveals the compositional variation observed in two LCO samples from different sources. LCO-I is richer in sulfur aromatics than LCO-II. The two samples also differ in terms of E


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Figure 1. Percent sulfur aromatics by HC33 versus percent sulfur by XRF.

short residue is the residue (boiling range above 550 °C) obtained from the vacuum distillation unit. It is upgraded by mixing with low boiling streams and hydroprocessed to produce value-added products. Table 4 provides detailed information about compositional variation in hydrocarbontype analysis (33 classes) of such FCC feedstock and its products. From the table, it was evident that S aromatic compounds became enriched in a higher distillate cut and a different S aromatic class distribution is observed by HC-33 analysis. This type of information is useful for a refiner to study process parameters and optimize the catalyst and other process conditions. 3.2. Comparison of Total S Aromatic Estimation by HC33 and Total Sulfur Content by XRF. To validate the results of HC33 class of analysis, 15 samples from different sources comprising VGO, raffinate, extracts, LCO, and CLO were analyzed by the WDXRF technique20 for total sulfur content and compared to sulfur aromatics determined by HC33 for 33 hydrocarbon classes by HR-MS. Figure 1 shows the correlation graph between the two data, and it shows a good correlation with a correlation coefficient R2 = 0.97. Further, the relationship indicates that sulfur classes as determined by HC33 are more than 8 times higher than those determined as per the WDXRF method, which justifies the thumb rule that sulfur compounds estimated by MS are about 10 times higher than the sulfur content estimated by XRF proposed by Bouquet and Brummet.12 3.3. Comparison of HC33 to SARA by TLC−FID. For further validation of the results of HC33 analysis, SARA analysis has been carried out for 17 samples in the boiling range of 300−600 °C according to the IP 469/01 test method.19 The saturate content obtained from TLC−FID was compared to the saturate content obtained by HC33 and HC22 analyses. The results are shown in Table 5. A correlation study has also been carried between the saturate content by SARA with HC33 and

Table 5. Comparison of the Saturate Content by SARA, HC33, and HC22 Analyses of VGO Range Samples number

saturates by SARA

saturates by MS (33 classes)

saturates by MS (22 classes)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17

39.6 64.6 12.3 40.0 75.1 32.0 33.5 21.0 32.3 97.3 97.5 96.5 96.3 78.5 67.4 75.0 82.7

38.1 61.9 10.5 28.3 65.6 31.0 20.0 30.0 31.2 87.0 88.0 87.3 88.7 68.1 59.2 68.5 70.3

36.2 62.5 9.6 30.0 73.2 33.1 34.0 18.6 30.5 82.6 82.2 83.0 84.6 64.0 58.4 72.6 59.8

HC22 analyses, and it shows good correlation among techniques, as shown Figure 2. The correlation coefficients of R2 = 0.97 and 0.96 were obtained for HC33 and HC22, respectively. 3.4. Comparison of HC33 and HC22. A total of 38 samples comprising VGO, CLO, and LCO samples were subjected to both HC33 and HC22 analyses. The three major classes of hydrocarbons, vis-à-vis saturates, aromatics, and sulfur aromatics, determined by HC22 and HC33 were then compared and represented in Figures 3, 4, and 5, respectively. For saturates and sulfur aromatics, a high degree of correlation (R2 = 0.96 and 0.91, respectively) was established, while for F


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between the two methods. Hence, detailed hydrocarbon-type analysis by both HC33 and HC22 methods is acceptable. 3.5. VGO Analysis by the HC33 Method: A Case Study. In refineries, because of the scarcity of regularly used feedstock, at times, blends of new and regular feedstocks in different compositions are processed. In one such case, the feedstock comprising 25−35% new VGO with regularly used feed was introduced to the unit. It was found that, after the introduction of blended feed, the severity of the process was increased to obtain the desired conversion level. Therefore, to understand the above observation, a study was conducted in the pilot plant stimulating the refinery conditions to investigate the reasons for the increasing severity of the process. Five feedstocks with different hydrocarbon compositions, namely, A, B, C, D, and E, were taken up for this study (Table 6). Pilot-plant experiments were carried out on the above feed samples under refinery process conditions. The feed samples were analyzed for 33 hydrocarbon classes by a HR-MS technique (Table 7). It was observed that, whenever feedstock E was processed, the severity of the process conditions (temperature and pressure) was increased to maintain the same conversion level. From Table 7, it is evident that the paraffin content in feed B is higher than those in feed A and feed C. The aromatic and sulfur aromatic contents in both feed A and feed C are around 41 and 28%, respectively. Figure 6 shows the comparison of saturates and mono-, di-, tri-, tetra-, and penta-ring aromatics in feed A, feed B, and feed C. From Table 7 and Figure 6, it is observed that although monoaromatic contents in the three feeds do not have significant variation, feed B differs from feed A and feed C in terms of contents of higher ring aromatics (dito penta-rings). The sulfur aromatic classes in feed B are comparatively present in lower amounts than those in feed A and feed C.

Figure 2. Comparison of saturates by TLC−FID SARA to HC33 and HC22.

aromatics, the value of R2 has been found to be 0.81. The comparison brings out the essential similarity between the two methods, despite the difference in experimental conditions and number of hydrocarbon classes determined. Further, one-way analysis of variation (ANOVA) was performed on sets of results obtained from HC22 and HC33 methods for saturate, aromatic, and sulfur aromatic classes. It was found that the observed F value between two methods for saturates was 0.007, the observed F value between two methods for aromatics was 0.248, and the observed F value between two methods for S aromatics was 0.394. The observed F values between two methods for the groups is less than the F critical value of 3.97. Therefore, there is no significant difference

Figure 3. Correlation graph of the saturate content by HC33 and HC22. G


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Figure 4. Correlation graph of the aromatic content by HC33 and HC22.

Figure 5. Correlation graph of S aromatics by HC33 and HC22.

The hydrocarbon class distributions of feed D and feed E are also given in Table 7. Figure 7 shows the comparison of the distribution of saturate and mono-, di-, tri-, tetra-, and pentaring aromatic classes in feed D and feed E. The saturate contents in feed D and feed E differ only by 1% (w/w), whereas the aromatic content in feed D is 36.8% and the aromatic content in feed E is 40%. In-depth analysis of data shows that the concentration of di- to penta-ring aromatic compounds is

higher in feed E than that in feed D and especially significant in tri-ring aromatic classes. Figure 8 shows the comparison of distribution of sulfur aromatic classes in feed D, feed E, and feed B feeds. From the graph, it is observed that feed D and feed E sulfur aromatics have not changed significantly but the sulfur aromatics are higher than those in feed B. The increase in severity of the process conditions for VGO-E may be due to the presence of the higher content of aromatic and sulfur aromatic H


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4. CONCLUSION A method for detailed hydrocarbon-type analysis at a mass resolution of 10 000 has been optimized and demonstrated for heavy petroleum cuts comprising VGO, lube stock feed, LCO, CLO, and other refinery feedstocks using the AGHIS at the Research and Development Centre, Indian Oil Corporation Limited. Detailed hydrocarbon-type analyses of refinery streams provide useful information to refiners for the optimization of processes and products. About 40 samples covering a wide range of petroleum streams in the boiling range of 170−650 °C have been analyzed for 33 classes of hydrocarbons. Compositional variation of feed and products has been explained on the basis of MS analysis. Detailed hydrocarbon-type analysis (33 classes) has been very useful in assigning various sulfurcontaining aromatic classes present in highly aromatic-rich petroleum streams, such as LCO, CLO, and VGO. Because 33

Table 6. Five Feedstocks with Different Hydrocarbon Compositions number

name

1 2

feed A feed B

3 4 5

feed C feed D feed E

description neat VGO from refinery A combined VGO from refinery A comprising different streams neat VGO from refinery B feed D and feed B (75%) + feed C (25%) feed B (65%) + feed C (35%)

compounds. A higher aromatic content requires higher hydrogen gas for saturation of aromatic rings. Further, a lower H/C ratio of higher aromatic rings lead to coke formation in the reactor.24 To avoid coke formation, it would have been therefore necessary to increase the temperature and pressure of the reactors to obtain the desired conversion.

Table 7. HC33 Analysis of Feed A, Feed B, Feed C, Feed D, and Feed E hydrocarbon class (%, w/w) paraffins monocycloparaffins dicycloparaffins tricycloparaffins tetracycloparaffins saturates aromatic hydrocarbons alkylbenzenes benzocycloparaffins benzodicycloparaffins diaromatics naphthalenes acenaphthenes, biphenyls acenaphthylenes, fluorenes triaromatics phenanthrenes tetraromatics pyrenes chrysenes pentaromatics benzopyrenes aromatics benzothiophenes

dibenzothiophenes


disulfides

VG0-A

VGO-B

VGO-C

VGO-D

VGO-E


general formula

6.3 12.4 12.0 0.3 BDL 31.0

11.2 15.6 13.1 0.3 BDL 40.2

7.8 12.0 11.4 BDLa BDL 31.2

10.1 14.2 12.2 0.3 BDL 36.8

9.4 13.2 12.0 0.3 BDL 35.3

CnH(2n − 6) CnH(2n − 8) CnH(2n − 10)

10.8 2.8 2.4

11.0 3.1 2.0

10.9 3.2 2.2

11.0 3.1 2.1

11.0 3.2 2.2

CnH(2n − 12) CnH(2n − 14) CnH(2n − 16)

2.4 2.2 3.9

2.6 1.4 3.1

3.1 2.3 3.8

2.8 2.1 3.3

2.7 2.2 3.6

CnH(2n − 18) CnH(2n − 20)

3.6 6.2

3.6 4.0

3.4 5.1

3.5 4.2

3.5 4.8

CnH(2n − 22) CnH(2n − 24) CnH(2n − 26)

2.5 0.7 1.3

3.1 0.1 0.4

2.7 0.8 1.1

2.9 0.3 0.7

2.8 0.5 0.9

CnH(2n − 28) CnH(2n − 30)

1.6 0.8 41.2 8.1 3.8 2.4 6.9 2.9 BDL 1.2 0.8 0.7 0.4 0.6 0.1 BDL BDL BDL 27.9

0.6 0.2 35.2 7.5 4.8 2.5 6.1 1.7 BDL 0.9 0.3 0.2 0.2 0.3 BDL BDL BDL BDL 24.5

1.3 0.7 40.6 8.2 4.2 2.7 6.6 2.7 BDL 1.2 0.8 0.4 0.4 0.6 0.2 0.1 BDL BDL 28.1

0.8 0.4 36.8 7.8 4.5 2.6 6.3 2.1 BDL 1.0 0.5 0.3 0.3 0.4 0.1 BDL BDL BDL 25.9

0.9 0.5 40.0 8.0 4.4 2.5 6.4 2.3 BDL 1.1 0.5 0.3 0.3 0.4 0.1 BDL BDL BDL 24.5


sulfur aromatics a

BDL = below detection limit (0.1%) for the HC33 method. I


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Energy & Fuels

Figure 6. Comparison of saturate, mono-, di-, tri-, tetra-, and penta-ring aromatic, benzothiophene, dibenzothiophene, naphthobenzothiphene, and disulfide classes in feed A, feed B, and feed C.

Figure 7. Comparison of saturates and mono-, di-, tri-, tetra- and penta-ring aromatics in feed D and feed E.

J


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Energy & Fuels

Figure 8. Distribution of sulfur aromatic classes in feed D and feed E. (10) Gallegos, E. J.; Green, J. W.; Linderman, L. P.; LeTourneau, R. L.; Teeter, R. M. Anal. Chem. 1967, 39, 1833−1838. (11) Teeter, R. M. Mass Spectrom. Rev. 1985, 4, 123−143. (12) Bouquet, M.; Brument, J. Fuel Sci. Technology Int. 1990, 8 (9), 961−986. (13) Fafet, A.; Bonnard, J.; Prigent, F. Oil Gas Sci. Technol. 1999, 54 (4), 439−452. (14) Fafet, A.; Bonnard, J.; Prigent, F. Oil Gas Sci. Technol. 1999, 54 (4), 453−462. (15) Baldrich Ferrer, C.-A.; Novoa Mantilla, L.-Á . CT&F, Cienc., Tecnol. Futuro 2007, 3 (3), 173−190. (16) Guan, S.; Marshall, A. G.; Scheppele, S. E. Anal. Chem. 1996, 68, 46−71. (17) Rodgers, R. P.; White, F. M.; Hendrickson, C. L.; Marshall, A. G.; Andersen, K. V. Anal. Chem. 1998, 70, 4743−4750. (18) Pakarinen, J. M. H.; Teravainen, M. J.; Pirskanen, A.; Wickstrom, K.; Vainiotalo, P. Energy Fuels 2007, 21, 3369−3374. (19) Roussis, S. G.; Fitzgerald, W. P. Energy Fuels 2001, 15 (2), 477− 486. (20) van Deursen, M.; Beens, J.; Reijenga, J.; Lipman, P.; Cramers, C.; Biomberg, J. J. High Resolut. Chromatogr. 2000, 23 (7/8), 507−510. (21) Briker, Y.; Ring, Z.; Lacchelli, A.; McLean, N.; Rahimi, P. M.; Fairbridge, C.; Coggiola, M. A.; Young, S. E. Energy Fuels 2001, 15 (1), 23−37. (22) Institute of Petroleum (IP). IP 469/01, Determination of Saturated, Aromatics and Polar Compounds in Petroleum Products by Thin Layer Chromatography and Flame Ionization Detector; IP: London, U.K., 2001. (23) ASTM International. ASTM D2622-10, Standard Test Method for Sulfur in Petroleum Products by Wavelength Dispersive X-ray Fluorescence Spectrometry; ASTM International: West Conshohocken, PA, 2010. (24) Shuyi, Z.; Wenan, D.; Hui, L.; Dong, L.; Guohe, Q. Energy Fuels 2008, 22 (6), 3583−3586.

class analysis throws light on various sulfur aromatic classes, this information is useful for the refiner in catalyst selection, process optimization, and studying the effect of various process parameters. The HC33 method has been validated for sulfur and saturate contents by XRF and TLC−FID, respectively. The composition of various hydrocarbon classes by the HC33 method has been compared to the HC22 MS method. Findings show that the HC33 method of analysis can also be routinely used in detailed characterization of petroleum streams, which is essentially required for process optimization in refineries.

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AUTHOR INFORMATION

Corresponding Author

*E-mail: [email protected]. Notes

The authors declare no competing financial interest.

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REFERENCES

(1) Analytical Advances for Hydrocarbon Research; Hsu, C. S., Ed.; Kluwer Academics/Plenum Publishers: New York, 2003. (2) Briker, Y.; Rahimi, P.; Iacchelli, A.; Ring, Z.; Fairbridge, C.; Malhotra, R. Prepr. Symp.Am. Chem. Soc., Div. Fuel Chem. 1999, 44 (1), 172−17. (3) Grisby, R. D.; Scheppele, S. E.; Grindstaff, Q. G.; Sturm, G. P., Jr. Anal. Chem. 1982, 54, 1108−1113. (4) Roussis, S. G. Rapid Commun. Mass Spectrom. 1999, 13, 1031− 1051. (5) Rodgers, R. P.; Marshall, A. G. Anal. Chem. 2005, 21A−27A. (6) Liang, Z.; Hsu, C. S. Energy Fuels 1998, 12, 637−643. (7) Ha, H. Z.; Ring, Z.; Liu, S. Pet. Sci. Technol. 2008, 26 (1), 7−28. (8) Hsu, C. S.; Blum, S. C.; Liang, Z.; Grosshans, P. B.; Robbins, W. K. U.S. Patent 5,644,129 A, July 1, 1997. (9) Ogawa, T. Fuel 2005, 84, 2015−2025. K


Molecular-Level Characterization of Refinery Streams by High

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