Atmospheric Pressure Chemical Ionization

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Gas Chromatography/ Atmospheric Pressure Chemical Ionization Tandem Mass Spectrometry for Fingerprinting the Macondo Oil Spill Vladislav V. Lobodin, Ekaterina Maksimova, and Ryan Patrick Rodgers Anal. Chem., Just Accepted Manuscript • DOI: 10.1021/acs.analchem.6b01652 • Publication Date (Web): 09 Jun 2016 Downloaded from http://pubs.acs.org on June 9, 2016

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Analytical Chemistry

Gas Chromatography/ Atmospheric Pressure Chemical Ionization Tandem Mass Spectrometry for Fingerprinting the Macondo Oil Spill Vladislav V. Lobodin*,†,‡, Ekaterina V. Maksimova,§,⊥ and Ryan P. Rodgers*,†,‡ †

‡

Future Fuels Institute, Florida State University, 1800 East Paul Dirac Drive, Tallahassee, FL 32310. National High Magnetic Field Laboratory, Florida State University, 1800 East Paul Dirac Drive,

Tallahassee, FL 32310. §

College of Marine Science, University of South Florida, St. Petersburg, FL 33701.

⊥

Center for Ocean-Atmospheric Prediction Studies, Florida State University, Tallahassee, FL 32310.

Re -submitted to Analytical Chemistry: June 5, 2016

ABSTRACT We report the first application of a new mass spectrometry technique (gas chromatography combined to atmospheric pressure chemical ionization tandem mass spectrometry, GC/APCI-MS/MS) for fingerprinting a crude oil and environmental samples resulted from the largest marine oil spill in a history (the Macondo oil spill, the Gulf of Mexico, 2010). The fingerprinting of the oil spill is based on a trace analysis of petroleum biomarkers (steranes, diasteranes, and pentacyclic triterpanes) naturally occurring in crude oil. GC/APCI enables soft ionization of petroleum compounds that form abundant molecular ions without (or little) fragmentation. Ability to operate the instrument simultaneously in several tandem mass spectrometry (MS/MS) modes (e.g., full scan, product ion scan, reaction monitoring) significantly ACS Paragon Plus Environment


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improves structural information content and sensitivity of analysis. For fingerprinting the oil spill, we constructed diagrams and conducted correlation studies that measure the similarity between environmental samples and enable to differentiate the Macondo oil spill from other sources.

Keywords: APGC, APGC-MS, GC/APCI, biomarkers, petroleum, oil spill, hopanes, steranes, Deepwater Horizon.

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■ INTRODUCTION On April 20th, 2010 a semi-submersible, mobile offshore drilling platform known as the Deepwater Horizon, operating 75 km southeast of Louisiana (28°44′17.3″N, 88°21′57.4″W) in more than 1,500 meters of water, suffered an uncontrolled release of oil / gas that resulted in an explosion. Damage to the riser pipe and wellhead led to a subsurface wellhead “blowout” that resulted in a massive off-shore oil spill. The spill has lasted for 87 days and led to a severe negative impact on Gulf of Mexico’s ecosystem and economy. It is estimated that about 800,000 m3 (~5 million barrels) of crude oil leaked from the Macondo well.1 However, final legal opinion set the total release amount as 3.19 million barrels taking collection efforts into account.2 After escaping from the well, the Macondo crude oil underwent dissolution in water column,3 evaporation from the water surface,4 emulsion (mouse) formation,5 biodegradation,4,6 and photo-oxidation.4,7 As a result, oil slicks and highly weathered tarballs found in the sea and on the beach were compositionally altered relative to the parent crude oil.8,9 Thus, source identification of the weathered oil became an important issue in tracking the fate and transport of oil spill residues,10 as well as evaluation of its impact on ecosystem.11 A combination of mass spectrometry (MS) and high performance separation methods provides a potential solution for source identification in environmental applications.12 Environmental and petroleum geochemistry studies rely mainly on GC-MS(/MS) analysis of petroleum biomarkers, in which the ionization of analytes in a mass spectrometer ion source takes place under vacuum by electron ionization (EI). From the total collection of petroleum biomarkers, select steranes and pentacyclic triterpanes (e.g., hopanes) are particularly useful for the differentiation of crude oils, and the characterization, fingerprinting, and monitoring of the degradation processes. Steranes and hopanes are natural organic compounds that are highly resistant to degradation under environmental conditions.13 They form during digenesis and catagenesis from biogenic precursors (steroids and hopanoids) that, in turn, were produced by ancient organisms (eukaryotes and prokaryotes correspondingly) millions years ago.14 ACS Paragon Plus Environment


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Unfortunately, conventional EI (70 eV) is a highly energetic ionization method that can produce extensive fragmentation of petroleum biomarker molecular ions. The fragmentation provides much needed structural information; however, it does so at the expense of molecular ion abundance, which degrades overall sensitivity. Consequently, biomarkers such as 17α(H)-22,29,30-tris-norhopane (C27-hopane) and 5α(H),14α(H),17α(H)-20R-cholestane (C27-sterane) yield a total ion count < 10% for molecular ions (Figure 1, top) under typical EI conditions. As the concentration of the biomarkers in crude oil is usually very low, various detection methods of the formed ions are used to increase the sensitivity of analysis. For example, registration of full mass spectra by recording the total ion current (TIC), selected ion monitoring (SIM), and selected reaction monitoring (SRM, also called multiple reaction monitoring (MRM)) are commonly used.15,16

EI mass spectra 17α(H)-22,29,30-tris-norhopane

5α(H),14α(H),17α(H)-20R-cholestane 7% of TIC 4% of TIC C27H48

C27H46

M+•

M+•

m/z

m/z

APCI mass spectra 17α(H)-22,29,30-tris-norhopane

44% of TIC 370 M+•

5α(H),14α(H),17α(H)-20R-cholestane

47% of TIC 372 M+•

191 95 121 149 50

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Figure 1. Top. EI mass spectra of 17α(H)-22,29,30-tris-norhopane and 5α(H),14α(H),17α(H)-20Rcholestane. Note extensive fragmentation of molecular ions under EI. Bottom. APCI mass spectra of 17α(H)22,29,30-tris-norhopane and 5α(H),14α(H),17α(H)-20R-cholestane. Note, soft ionization under APCI produces abundant molecular ions.

The use of tandem mass spectrometry is particular advantageous, because it can operate in all aforementioned modes (separately or simultaneously). Moreover, SRM is beneficial for targeted analysis of compounds in trace amounts and provides improved signal-to-noise ratio, higher selectivity, and lower detection limit.15 Biomarker analysis with SRM transitions is carried out by synchronized transmission of precursor ion (usually a molecular ion) and a selected product ion only. The product ion is usually one of the characteristic fragment ions produced from the parent ion in a collision cell. However, as shown in Figure 1, molecular ions of biomarkers under EI conditions account for only a minor fraction (4-7%) of the TIC. Thus, for parent ion identification, only those ions that remain unfragmented are available for subsequent MS/MS experiments (including SRM). In contrast, the combination of MS/MS with soft ionization methods that efficiently form molecular or pseudo-molecular ions without (or a low amount of) fragmentation can significantly improve signal-to-noise ratio and structural information content through subsequent, controlled fragmentation. Soft atmospheric pressure ionization methods (such as APCI, APPI, and ESI) are widely used with LC/MS instruments. Despite the first coupling of GC with atmospheric pressure ionization mass spectrometry (API-MS) was demonstrated over 40 years ago,17 it lacked prompt commercialization and thus was surpassed by LC/MS applications. Nevertheless, in 2005 McEwen and McKay reported the integration of GC with a commercial LC/MS instrument and the operation of GC/API-MS under APCI by corona discharge.18 In the recent years several mass spectrometry vendors launched commercial GC/APCI ion sources that can be connected to LC/MS instruments. Such systems enable quick switching between GC and LC modes and can be used for ACS Paragon Plus Environment


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analysis of a wider range of compounds including volatile and semi-volatile (GC-amenable), and polar, nonvolatile compounds (LC/MS). GC/APCI-MS is a relatively new configuration that gains popularity for mass spectrometry-based analysis with rising number of applications including analysis of environmental samples,19-21 pharmaceuticals22 and doping drugs,23 petroleum samples,24-26 metabolomics,27-29 and food industry,30-32 etc. In this work, we demonstrate the first utilization of GC/APCI combined with tandem mass spectrometry for a trace analysis of petroleum biomarkers from the Macondo well crude oil and fingerprinting the oil spill.

■ EXPERIMENTAL Samples. Macondo crude oil (NIST2779) and NIST2266 standard mix that includes five hopanes (17α(H)22,29,30-trisnorhopane,

17α(H),21β(H)-30-norhopane,

17α(H),21β(H)-hopane,

17α(H),21β(H)-22S-30-

homohopane, 17α(H),21β(H)-22R-30-homohopane) and five steranes (5α(H),14β(H),17β(H)-20R-cholestane, 5α(H),14α(H),17α(H)-20R-cholestane,

5α(H),14β(H),17β(H)-20R-24S-methylcholestane,

5α(H),14α(H),17α(H)-20S-24R-ethylcholestane,

5α(H),14β(H),17β(H)-20R-24R-ethylholestane)

were

purchased from NIST (Gaithersburg, MD). Natural oil seep sample (“Megaplume”) located in GC 600 lease block (Gulf of Mexico) was collected by a remote operated vehicle at the depth of 1222 m at the seep mouth (27°22'27.96”N, 90°30'41.34”W) with TFE-fluorocarbon polymer net without interferences from other hydrocarbon sources.33,34 A Blue Crude oil35 sample from Independence hub platform operated in the Gulf of Mexico (28°05'89.0”N, 87°59'27.0”W) was provided by an oil company. Figure 2 shows a map with marked locations for environmental samples (SAM 1-18) collected from May 2010 to January 2014 (see SI for sampling date and location). The environmental samples were extracted by Soxhlet extraction as described elsewhere.8,9 The extracts were evaporated under a gentle nitrogen flow to dryness and then diluted in dichloromethane (HPLC grade, J.T.Baker) to the concentration of 20 mg/mL for GC-APCI/MS-MS analysis. The crude oils were five-fold diluted in dichloromethane prior to analysis.


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Figure 2. Image of the Gulf of Mexico with marked locations of sample collection (SAM-1‒ SAM-18), Deepwater Horizon explosion, Megaplume oil seep and Independence hub (Blue Crude oil).

Sample Characterization. A gas chromatography/mass spectrometry analysis was conducted with an GC/APCI-MS instrument consisting of an Agilent 7890 GC system (Agilent Technologies, Santa Clara, CA) and a Xevo TQ-S tandem quadrupole instrument (Waters Corporation, Milford, MA) equipped with an APGC ion source. The injected volume was 1 µL in split mode (split ratio was 1:10). Helium (99.9995%) at flow rate of 1.2 mL/min was the carrier gas. The gas chromatograph inlet temperature was 300°C. The GC oven temperature was programmed from 50 °C and held for 3 min, then ramped at 20°C/min to 150 °C and 2°C/min from 150°C to 350°C, and then held at the maximum temperature for 25 min. The transfer line was kept at 380°C. A MXT-5 GC column (60 m long, 250µm ID, 0.25 µm film thickness) was purchased from ACS Paragon Plus Environment


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Restek Corporation (Bellefonte, PA). The ion source was held at 150°C. Nitrogen served as auxiliary gas

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(250 L/hr), cone gas (200 L/hr), and make-up gas (350 ml/min) and was delivered from a Dewar as a boil-off of liquid N2. Collision gas was argon (99.999%) and was supplied to a collision cell at 0.15 ml/min. Each sample was run in triplicate with a solvent blank between the samples to make sure of the absence of a carryover. Comparative EI data were recorded with 5973 GC/MS instrument (Agilent Technologies, Santa Clara, CA). The injected volume was 1 µL in split mode (split ratio was 1:10). The carrier gas was helium (99.9995%) at flow rate of 1.0 mL/min. The gas chromatograph inlet temperature was 300°C. The GC oven temperature was programmed from 50 °C and held for 0.5 min, then ramped at 1.5°C/min to 320 °C and then held at the maximum temperature for 10 min. The transfer line was kept at 300°C. A DB-5MS GC column (30 m long, 250µm ID, 0.25 µm film thickness) was purchased from Agilent Technologies (Santa Clara, CA). The ion source was held at 150°C. Analytes were ionized by APCI (corona discharge in the atmosphere of nitrogen, current of 2.5 µA) and positive ions were mass-analyzed. Mass spectrometry data were acquired with MassLynx 4.1 software (Waters Corp.) in full scan and MS/MS modes: SRM and product scan. Table 1S shows conditions for acquisition of SRM transitions. Areas under biomarkers’ peaks from the corresponding SRM chromatograms were used to calculate biomarkers ratios. 7-axis diagrams were constructed with Microsoft Excel (Microsoft Office Professional Plus 2010). The correlation coefficients were calculated and plotted with MATLAB R2014a (MathWorks, Natick, MA).

■ RESULTS AND DISCUSSION The ionization of petroleum compounds in GC/APCI source occurs by a charge transfer mechanism initiated by a corona discharge: in a nitrogen plasma (nitrogen molecules generate radical cations that, in turn, ionize analyte molecules to form molecular ions). Figure 1S shows schematic diagram for operation of GC/APCI and ionization mechanisms for the formation of molecular and pseudo-molecular ions. The ion source ACS Paragon Plus Environment

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conditions correspond to “dry” operation with no reagent/dopant added. Alternatively, ionization can take

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place through proton transfer reactions if a proton source (e.g., moisture or protic solvents, such as alcohols) is present in the ion source. The former mechanism results in efficient ionization of non-polar species whereas the later mechanism ionizes polar compounds. Both types of petroleum biomarkers (hopanes and steranes) are efficiently ionized in the GC/APCI ion source with formation of abundant M+• ions. Figure 1 (bottom) shows APCI mass spectra of 17α(H)-22,29,30-tris-norhopane and 5α(H),14α(H),17α(H)-20Rcholestane) that demonstrate a significant increase (up to 10 times) in the relative abundance of molecular ions in comparison to fragmentation of these compounds under EI. In turn, due to combination of GC/APCI source with triple quadrupole mass spectrometer, the formed molecular ions are available for the subsequent MS/MS experiments, e.g., collisionally activated dissociation (CAD) to provide structural information. Figure 3 shows MS/MS product scan (daughter spectra) from M+• of 17α(H)-22,29,30-tris-norhopane and 5α(H),14α(H),17α(H)-20R-cholestane. The MS/MS spectra demonstrate fragmentation patterns similar to those observed under EI (see Figure 1S). The collision conditions (collision gas- argon, collision energy of 15eV and 20 eV) were optimized to maximize the yield of characteristic ions: m/z 191 for the hopane and m/z 217 for the sterane. Figure 2S shows the summed signal for seven SRM-transitions for hopanes and steranes in NIST2266 standard mix and a five-point calibration curve for 17α(H),21β(H)-hopane demonstrating a linear signal response and stability of GC/APCI-MS/MS operation.



GC/APCI-MS/MS. Product Spectra from M+• 17α(H)-22,29,30-tris-norhopane 191

Relative Abundance, %

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357

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Figure 3. Product ion spectra (MS/MS) from M+• (produced under APCI in GC/APCI source) of 17α(H)22,29,30-tris-norhopane at collision energy of 15 eV (top) and 5α(H),14α(H),17α(H)-20R-cholestane at collision energy of 20 eV (bottom).

Figures 3S and 4S show individual SRM chromatograms for every compounds in NIST2266. Each chromatogram corresponds to a SRM transition (M+• → m/z 191 or M+• → m/z 217) that is specific for compounds in the mixture. Such individual chromatograms simplify the assignment and the integration of peaks and are especially useful for complex mixtures when co-elution of compounds is observed in TIC.


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Figure 4 shows a chromatogram for summed signal of SRM transitions for triterpanes (M+• → m/z 191)

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in the Macondo well crude oil (NIST2779) with assignment of over dozens hopanes: Ts, Tm, H29, C29Ts, DH30, M30, H30, H31S, H31R, H32S, H32R, H33S, H33R, H34S, H34R, H35S, H35R (see SI for full compounds names). The assignment of the peaks is based on retention times for standard compounds from NIST2266, elution order and signal from individual SRM transitions.

GC/APCI-MS/MS for NIST2779 (Macondo Wellhead Crude Oil) Hopanes: Summed Signals for C27-C35 (M+• → m/z 191) 100

H30 19 20 12 18 E 21 30 32 34 13 11 25 26 D 17 22 31 33 35 1 9 C 28 16 29 2 14 A 10 B 8 27 15 7 3 5 6 4 23 24

H29

RA, %

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Ts Tm

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C29Ts

C31

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84.00

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Time, min

Figure 4. GC/APCI-MS/MS chromatogram, showing the sum of SRM transitions (M+• → m/z 191) for C27– C35 hopanes from the Macondo crude oil.

The hopane signature provides a powerful tool for fingerprinting an oil spill and, for example, determination of spill sources in the Strait of Malacca was exclusively based on pentacyclic triterpanes.36 However, apart from triterpanes, the use of steranes and diasteranes can be also beneficial when hopane signatures of the oils are not distinct. Diasteranes do not have direct precursors in living organisms and are formed from sterols and steranes during diagenesis and catagenesis by rearrangements that involve migration



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of two methyl groups from positions C10 and C13 to C5 and C14. The rearrangement is promoted by acidic catalysis and high temperature, and usually is favorable in clay-reach environment.37 Figure 5 (top) shows a chromatogram for summed signal of SRM transitions for C27-C29 steranes/diasteranes (M+• → m/z 217) and a general formula of steranes. It is to be noted higher complexity of steranes/diasteranes signature in the Macondo crude oil due to the co-elution of the compounds. Nevertheless individual SRM transitions (M+• → m/z 217) facilitate visualization and assignment of the peaks. Additional SRM transitions (M+• → m/z 218, M+• → m/z 259) specific for steranes and diasteranes were added to the experiment script (see Table 1S) to increase confidence in the assignment of chromatographic peaks. Two dozen steranes and diasteranes were identified in the crude oil: C27βαS, C27βαR, C27αβS, C27αβR, C27αααS, C27αββR, C27αββS, C27αααR, C28βαS, C28βαR, C28αβS, C28αβR, C28αααS, C28αββR, C28αββS, C28αααR, C29βαS, C29βαR, C29αβS, C29αβR, C29αααS, C29αββR, C29αββS, C29αααR (see SI for full compounds names). In addition to selective SRM transitions, assignment of the peaks was also based on elution order of steranes and diasteranes,38 and retention times of steranes in NIST2266 standard. Figure 5S shows comparative analysis of Macondo crude oil (NIST 2779) by EI with conventional GC/MS. The ion chromatograms for ions at m/z 191 and 217 shows hopanes and steranes signatures although with higher background and lower S/N ratio. Whereas, hopnaes can be easily assigned from the chromatogram, the assignment and integration of chromatographic peaks for steranes presents a big challenge due to coelution of the compounds.


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GC/APCI-MS/MS for NIST2779 (Macondo Crude Oil) 28

Steranes & Diasteranes 100

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m/z 400 217

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Figure 5. GC/APCI-MS/MS chromatograms (SRMs), showing the C27–C29 sterane distribution for the Macondo crude oil. Note, the truncated labels correspond to compounds described in the text. The number of carbon atoms in diasteranes and steranes is defined in each SRM chromatogram.

Biomarkers ratios. Highly weathered oil samples are usually very different from a source crude oil in chemical composition, and the concentration of even persistent biomarkers may vary because of the partial degradation and changes in volume of hydrocarbon matrix.39-41 Thus, the direct comparison of absolute



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content of biomarkers in parent oil and spilled samples can be ambiguous for fingerprinting an oil spill.

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However, as a general rule, most steranes and hopanes in spill samples and source oils do not show considerable changes in diagnostic ratios for stereoisomers and biomarkers of similar structure, or belonging to the same homologous series.13 In addition, the biomarkers ratios do not necessary require quantitative analysis and can be calculated from semi-quantitative data (e.g., peak heights or areas).42 Table 2S demonstrates results for quantitative measurement of biomarkers in the Macondo crude oil (NIST2779) with GC/APCI-MS/MS that are in a good agreement with reference values provided by NIST43 (note, the reference values continue to be revised and corrected). Nevertheless quantitation of each and every biomarker compound in every environmental sample would be a very laborious and expensive. Thus, in turn, it results in marked limitations for high throughput, routine analytical applications. The use of ratios minimizes concentration effects of individual compounds caused by environmental changes and sample preparation, and levels out fluctuations in everyday instrument operation. Therefore, comparison of diagnostic ratios directly reflects differences of the target biomarker distribution among samples.37 The petroleum biomarkers identified in the Macondo crude oil were also found in all environment samples and other crude oils analyzed. In the current work we utilized seven diagnostic ratios (Ts/Tm, H29/H30,

H32S/H32R,

H33S/H33R,

H30/(H31+H32+H33+H34+H35),

C27αββ/C29αββ

steranes,

C27βα/C29βα

diasteranes) commonly used for identification, correlation, and differentiation of spilled oils.13 In principle, the number of ratios can be extended if fine differences between very similar samples need to be tracked. The Ts/Tm ratio is used in petroleum geochemistry to provide insight on maturity and source of a crude oil. Because 18α(H)-22,29,30-trisnorhopane (Ts) is thermodynamically more stable (by 4.4 kcal/mol) than 17α(H)-22,29,30-trisnorhopane (Tm), the increase in Ts/Tm ratio is diagnostic for higher oil thermal maturity.44 H29/H30 ratio is used as a general triterpane fingerprint that depends on source rock depositional environment and organic matter input. High H29/H30 ratio (>1) is typical for anoxic carbonate source rocks. The ratio measured using m/z 191 is more sensitive to C30-hopane because its molecular ion fragments to ACS Paragon Plus Environment

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yield two structurally complimentary fragment ions at m/z 191, whereas C29-hopane produce m/z 191 by only

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one pathway. Because 17α(H),21β(H)-30-norhopane (H29) is more stable than 17α(H),21β(H)-hopane (H30) at high level of thermal maturity, the ratio can be used as a maturity factor within a group of related oils.37 H32S/H32R and H33S/H33R ratios also indicate thermal maturation. During diagenesis and catagenesis biological 22R configuration in hopanoids converts to 22S in hopanes until equilibrium ratio (22S/22R) of ~1.5 is reached with thermal maturation.45 H30/(H31+H32+H33+H34+H35) ratio is not widely used in petroleum geochemistry but it was successfully applied in environmental studies for oil spill source identification to establish Middle Eastern crude origin of tarballs found in Malaysian coastal zone.36 C27αββ/C29αββ-sterane ratio describes an ecosystem contributing the precursor sterols into organic matter of the source rock. Higher relative content of C27-sternaes can be an evidence for marine plankton organic matter whereas a prevalence of C29-steranes corresponds to a preferential input from higher plants.46 C27βα/C29βα-diasterane ratio also shows a biological system responsible for organic matter deposition (algae or higher plants) and is used when steranes are degraded and diasteranes remain intact, and is usually observed for heavily biodegraded oils or some highly mature oils / condensates that show low sterane, but higher diasterane content.37 Table 3S summarizes the biomarkers ratios for all samples studied in this work calculated based on a chromatographic peak area. Reproducibility of the analytical procedure was confirmed by the triplicate analysis of all samples and relative standard deviation was within 10%. To simplify data visualization we constructed seven-axis diagrams that allows us to track difference between samples (Figure 6).



1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 267 51 52 268 53 54 269 55 56 57 58 59 60

NIST2779 βαC27/βαC29 Diasteranes

SAM-1

Ts/Tm 2 1.5

H29/H30

βαC27/βαC29 Diasteranes

1 0.5

0

H33S/H33R

SAM-3 2 1.5

H29/H30

H33S/H33R

SAM-5

Ts/Tm H29/H30

C27βα/C29βα Diasteranes

Ts/Tm

2

1.5

1

1 0.5

0

H32S/H32R

H33S/H33R

H30/ΣH31‒H35

H33S/H33R

1.5

H32S/H32R

C27αββ/C29αββ Steranes H30/ΣH31‒H35

SAM-7

H33S/H33R

SAM-8 Ts/Tm

Ts/Tm

2

H29/H30


2 1.5

H29/H30


2 1.5

1

1

1

0.5

0.5

0.5

0

0

H32S/H32R


H33S/H33R

SAM-9

H32S/H32R

H30/ΣH31‒H35

H33S/H33R

1.5

H32S/H32R

C27αββ/C29αββ Steranes

SAM-11 Ts/Tm

H29/H30

H33S/H33R

H30/ΣH31‒H35

SAM-10 C27βα/C29βα Diasteranes

Ts/Tm

2 1.5

H29/H30


2 1.5

1

1

1

0.5

0.5

0.5

0

H30/ΣH31‒H35

H33S/H33R

SAM-12

H32S/H32R


SAM-13 2


H33S/H33R

SAM-14 Ts/Tm 2

H29/H30

H32S/H32R


H33S/H33R

Ts/Tm 1.5

1.5

Ts/Tm H29/H30


2 1.5

1

1

1

0.5

0.5

0.5

0

0

H32S/H32R


H33S/H33R

SAM-15

H30/ΣH31‒H35

H32S/H32R


H33S/H33R

SAM-16 H29/H30


H33S/H33R

SAM-17 Ts/Tm

2

Ts/Tm

2 1.5

H29/H30


2 1.5

1

1

1

0.5

0.5

0.5

H32S/H32R

H30/ΣH31‒H35

H33S/H33R

SAM-18

H32S/H32R


1.5

H32S/H32R


H33S/H33R

Ts/Tm H29/H30


H33S/H33R

Blue crude

Megaplume Ts/Tm 2

Ts/Tm

2 1.5

H29/H30


2 1.5

1

1

1

0.5

0.5

0.5

H30/ΣH31‒H35

H32S/H32R

H33S/H33R


H29/H30

0

0

0


H29/H30

0

0

0


H29/H30

0

H32S/H32R


Ts/Tm 1.5

H29/H30

0

0

H32S/H32R


H29/H30

0


Ts/Tm 2

H29/H30

0

H32S/H32R


Ts/Tm


H33S/H33R

0.5

SAM-6


H32S/H32R

1

H30/ΣH31‒H35



H30/ΣH31‒H35

2 1.5

0


0

H32S/H32R

H30/ΣH31‒H35


H29/H30

1

0.5



2 1.5

0.5


SAM-4

Ts/Tm C27βα/C29βα Diasteranes

H29/H30


0

H32S/H32R

H30/ΣH31‒H35

Ts/Tm

1.5

1


SAM-2

Ts/Tm 2

0.5

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H32S/H32R

H33S/H33R


H32S/H32R

H33S/H33R

Figure 6. Spider diagrams for the Macondo crude oil, eighteen tarball samples (SAM-1–18), Megaplume oil seep and Blue Crude constructed from seven diagnostic biomarker ratios (Ts/Tm, H29/H30, H32S/H32R,


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H30(H31+H32+H33+H34+H35), H33S/H33R, C27αββ/C29αββ steranes, and C27βα/C29βα diasteranes). The diagrams

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for SAM-1–18 demonstrate the great similarity to the reference Macondo crude oil.

Each axis on the diagram corresponds to a specific biomarker ratio. Although some tarball samples indicate little deviation in the biomarkers ratios from NIST2779, their general profile well resembles that for Macondo crude oil. The changes in the ratios can be caused by sample degradation39,47 and/or other potential input of biogenic and petrogenic hydrocarbons. For example, the Ts/Tm ratio for many environmental samples is systematically slightly higher than that for the Macondo crude oil that is consistent with preferential degradation of thermodynamically less stable Tm in the environment.48,49 Overall, high similarity with NIST 2779 is observed for all samples found from one month to almost four years after the accident that demonstrates persistence and stability of the biomarker ratios over a prolonged period of time. Although the spider diagrams provide a very convenient, illustrative tool for graphical data visualization / comparison, the ultimate, visual judgement of similarity / dissimilarity is undoubtedly subjective. The use of a quantitative, statistical parameter to evaluate similarity / dissimilarity provides a rational basis for the determination. To establish a quantitative measure of samples similarity, we calculated a correlation coefficient, a statistical parameter that is used to “fingerprint” the oil spill. As recommended by Nordtest42, for correlation studies we utilized linear regression using least square method. This approach for evaluation of a match between the samples is less subjective than standard methods (e.g., ASTM D3328, D5739), that rely on visual comparison of chromatograms. The average values and standard deviations for the biomarker ratios (Table 3S) from triplicate analysis were used to establish a correlation between the samples. The expanded uncertainty (U) calculated as U = k·u, where u is a standard deviation and k is a coverage factor, equal to 2.484. k is determined from the Student’s t-distribution corresponding to the associated degrees of freedom and a 95 % confidence level for each sample. The correlation coefficients are calculated for every sample relatively to Macondo crude oil (NIST 2779), for which it is 1. Figure 7 shows the correlation for all samples and values presented on bars ACS Paragon Plus Environment


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(except the small negative correlation value for the Blue Crude oil) are statistically significant at the 95%

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confidence level. The closer the correlation coefficient to 1, the more identical is the sample to Macondo crude oil.

Figure 7. Correlation coefficients for quantitative comparison of 20 samples with Macondo crude oil (NIST 2779). The correlation of NIST 2779 with itself is equal to 1, as shown by the green bar.

Environmental samples (SAM-1‒SAM-18) show high similarity to the Macondo crude oil with the correlation coefficient values ranging from 0.947 to 0.996. It is worth noting that two samples (SAM-10 and SAM-11) collected within three months after the accident show some of the highest correlation values (0.996 and 0.994, correspondingly), which is consistent with lower level of degradation for samples with a shorter environmental exposure time. In fact, such a small deviation in correlation coefficient from 1 can be due to fluctuation in sample preparation and instrument operation. However, SAM-8, collected eleven months after the oil spill, shows the lowest correlation coefficient (0.947) even among tarballs with longer exposure period (SAM-12‒SAM-18). This sample was found on a barrier island in the Mississippi river delta, where extensive biodegradation50,51 and biogenic52,53 input from the environment is very possible. Furthermore, the area serves as a busy sea traffic route and faces water discharge from the river with all accompanying pollution54 that makes a contribution of petrogenic hydrocarbons from other sources probable as well. It is


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interesting to mention that another sample (SAM-17) also found in the river delta shows the second lowest

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correlation (0.965) among the environmental samples. However, apart from pollution caused by human activity, crude oil can enter the marine environment through natural seepages from the sea floor. Natural oil seeps are a global phenomenon contributing up to 2 million tonnes of petroleum a year worldwide which exceeds all anthropogenic sources combined.55,56 There are numerous seepage zones in the Gulf of Mexico, and oil slicks for some of them can be seen on water surface from Space.50 The exact volume of petroleum coming from those seeps is still under debate with estimated values from 80,000 to 200,000 tonnes/year.55 Nevertheless, petroleum compounds related to longpersistent natural oil seeps also need to be taken into account in oil spill studies.10 To demonstrate the fidelity of applied analytical approach for differentiation of the Macondo oil spill from other potential sources, we investigated the Megaplume oil seep and a Blue Crude oil35 – samples that originate from different gas/petroleum reservoirs in the Gulf of Mexico. As a contrast, Megaplume (0.655) shows substantially lower and Blue Crude (-0.393) a non-significant correlations with NIST 2779 making them very distinct from the Macondo oil and spill samples. It is to be noted that we are fully aware that evaluation of potential contribution of petroleum pollution from other sources requires comprehensive analysis of a representative set of samples and consideration of ecological, geographical, metocean, and climatic factors (e.g., source locations, their volume, mass transport due to ocean currents and waves,57 etc.). Apart from hopanes and steranes used in this work it also may be required to extend the number of molecular markers and ratios to achieve reliable differentiation between closely related sources. Some of the compounds (e.g., PAHs, PASHs, etc.) can give an additional tool for fingerprinting the oil spill and identification of a pollution source10 as well as provide an insight for degree of biotic and abiotic (weathering) degradation.39,58 Such studies with GC/API-MS for the Macondo oil spill are underway.

■ ASSOCIATED CONTENT ACS Paragon Plus Environment


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Supporting Information. Schematic diagram for GC/APCI ion source and ionization mechanisms (Figure 1S). SRM chromatograms for hopanes (M+• → m/z 191) and steranes (M+• → m/z 217) from NIST2266 standard mixture (Figures 2S, 3S, and 4S). GC/MS (EI) for NIST2779 (Figure 5S). MS/MS conditions for acquisition of SRM transitions (Table 1S). Results for quantitative measurement of biomarkers in NIST2779 with GC/APCI-MS/MS (Table 2S). Biomarker ratios for all samples (Table 3S). These materials are available free of charge via the Internet at http://pubs.acs.org.

■ AUTHOR INFORMATION Corresponding Authors * Vladislav V. Lobodin and Ryan P. Rodgers. Phone: +1 850 644 1319 (VVL),

+1 850 644 2398 (RPR)

Fax: +1 850 644 1366 (RPR and VVL) E-mails: [email protected] (VVL), [email protected] (RPR)

■ ACKNOWLEDGEMENTS This work was supported by NSF DMR-11-57490, the Florida State University Future Fuels Institute, BP/The Gulf of Mexico Research Initiative to the Deep-C Consortium, Waters Corporation, the State of Florida, and NSF OCE-1421180 (E. Maksimova). We thank Dr. Christopher M. Reddy and Mr. Robert K. Nelson (Woods Hole Oceanographic Institution, MA), and Drs. Markus Huettel and Ian MacDonald (Department of Earth, Ocean and Atmospheric Science, Florida State University, FL) for supplying environmental samples.


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Table of Contents Graphic

GC/APCI-MS

Corona Pin

Ionization Chamber

Ts/Tm 2 Ion Source Housing


1.6

H29/H30

1.2 0.8 0.4

Heated Transfer Line

0 αββC27/αββC29 Steranes

Mass Spec (Atmospheric Pressure)

H32S/H32R

Capillary GC Column H30/H31+H32+H33+H34+H35

H33S/H33R

NIST2779 (Macondo crude oil) SAM-10 (Pensacola Beach) Megaplume oil seep (GC600) Blue crude (Independence Hub)



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Figure legends Figure 1. Top. EI mass spectra of 17α(H)-22,29,30-tris-norhopane and 5α(H),14α(H),17α(H)-20Rcholestane. Note extensive fragmentation of molecular ions under EI. Bottom. APCI mass spectra of 17α(H)22,29,30-tris-norhopane and 5α(H),14α(H),17α(H)-20R-cholestane. Note, soft ionization under APCI produces abundant molecular ions. Figure 2. Image of the Gulf of Mexico with marked locations of sample collection (SAM-1‒ SAM-18), Deepwater Horizon explosion, Megaplume oil seep and Independence hub (Blue Crude oil). Figure 3. Product ion spectra (MS/MS) from M+• (produced under APCI in GC/APCI source) of 17α(H)22,29,30-tris-norhopane at collision energy of 15 eV (top) and 5α(H),14α(H),17α(H)-20R-cholestane at collision energy of 20 eV (bottom). Figure 4. GC/APCI-MS/MS chromatogram, showing the sum of SRM transitions (M+• → m/z 191) for C27– C35 hopanes from the Macondo crude oil. Figure 5. GC/APCI-MS/MS chromatograms (SRMs), showing the C27–C29 sterane distribution for the Macondo crude oil. Note, the truncated labels correspond to compounds described in the text. The number of carbon atoms in diasteranes and steranes is defined in each SRM chromatogram. Figure 6. Spider diagrams for the Macondo crude oil, eighteen tarball samples (SAM-1–18), Megaplume oil seep and Blue Crude constructed from seven diagnostic biomarker ratios (Ts/Tm, H29/H30, H32S/H32R, H30(H31+H32+H33+H34+H35), H33S/H33R, C27αββ/C29αββ steranes, and C27βα/C29βα diasteranes). The diagrams for SAM-1–18 demonstrate the great similarity to the reference Macondo crude oil. Figure 7. Correlation coefficients for quantitative comparison of 20 samples with Macondo crude oil (NIST 2779). The correlation of NIST 2779 with itself is equal to 1, as shown by the green bar.


Page 25 of 35

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


Supporting Information. Figure legends and Tables

Figure 1S. Top. Schematic diagram for GC/APCI ion source. Bottom. Ionization mechanisms for the formation of molecular ion (by charge transfer) and pseudo-molecular ion (protonation). By courtesy of Waters Corporation.

Figure 2S. Summed signal for seven SRM-transitions (M+• → m/z 191 and M+• → m/z 191) for hopanes and steranes in NIST2266 standard mix. Inset. Calibration curve for 17α(H),21β(H)-hopane containing five points at the range of 1.2-540 picograms with least squares regression (R2) of 0.999. Each point is an average of seven analysis runs.

Figure 3S. SRM chromatograms (M+• → m/z 191 ) for hopanes in NIST2266 standard mix: 17α(H)22,29,30-trisnorhopane,

17α(H),21β(H)-30-norhopane,

17α(H),21β(H)-hopane,

17α(H),21β(H)-22S-30-

homohopane, 17α(H),21β(H)-22R-30-homohopane).

Figure 4S. SRM chromatograms (M+• → m/z 217) for steranes in NIST2266 standard mix: 5α(H),14β(H),17β(H)-20R-cholestane, 24S-methylcholestane,

5α(H),14α(H),17α(H)-20R-cholestane,

5α(H),14α(H),17α(H)-20S-24R-ethylcholestane,

5α(H),14β(H),17β(H)-20R-

5α(H),14β(H),17β(H)-20R-24R-

ethylholestane. Figure 5S. GC/MS (EI) of Macondo crude oil (NIST2779). Ion chromatograms at m/z 191 (top) and m/z 217 (bottom).



1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 26 of 35

Table 1S. MS/MS conditions for acquisition of SRM transitions. Compound class

SRM transition

Dwell time, ms

Collision energy, eV

C27-Hopanes C27-Steranes C27-Steranes C27-Steranes C28-Hopanes C28-Steranes C28-Steranes C28-Steranes C29-Hopanes C29-Steranes C29-Steranes C29-Steranes C30-Hopanes C30-Steranes C31-Hopanes C32-Hopanes C33-Hopanes C34-Hopanes C35-Hopanes

370.30 → 191.10 372.30 → 217.10 372.30 → 218.10 372.30 → 259.20 384.30 → 191.10 386.30 → 217.10 386.30 → 218.10 386.30 → 259.20 398.30 → 191.10 400.30 → 217.10 400.30 → 218.10 400.30 → 259.10 412.30 → 191.10 414.30 → 217.10 426.30 → 191.10 440.40 → 191.10 454.40 → 191.10 468.40 → 191.10 482.40 → 191.10

50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50

15 20 20 20 15 20 20 20 15 20 20 20 20 20 20 20 20 20 20

26 ACS Paragon Plus Environment

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1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


Table 2S. Results for quantitative measurement (in mg/kg) of biomarkers in NIST2779 with GC/APCI-MS/ MS. aThe results are expressed as average values from triplicate analysis ± the expanded uncertainty. The expanded uncertainty (U) calculated as U = k·u, where u is a standard deviation and k is a coverage factor, equal to 2.484, determined from the Student’s t-distribution corresponding to the associated degrees of freedom for triplicate analysis and a 95% confidence level for each compound.

b

Reference values from

certificate ± the expanded uncertainty as provided by NIST.43 Note, that the reference values continue to be revised and corrected. NIST2779

NIST2779

Compound

a

18α(H)-22,29,30-Trisnorneohopane 17α (H)-22,29,30-Trisnorhopane 17α(H),21β(H)-30-Norhopane 17α(H),21β(H)-Hopane 17α(H),21β(H)-22R-Homohopane 17α(H),21β(H)-22S-Homohopane 5α(H),14α(H),17α(H)-Cholestane 20S 5α(H),14α(H),17α(H)-Cholestane 20R 5α(H),14α(H),17α(H)-24-Ethylcholestane 20S 5α(H),14α(H),17α(H)-24-Ethylcholestane 20R 5α(H),14β(H),17β(H)-Cholestane 20R 5α(H),14β(H),17β(H)-Cholestane 20S 5α(H),14β(H),17β(H)-24-Methylcholestane 20R 5α(H),14β(H),17β(H)-24-Methylcholestane 20S 5α(H),14β(H),17β(H)-24-Ethylcholestane 20R 5α(H),14β(H),17β(H)-24-Ethylcholestane 20S

(measured) 12.7±2.2 10.2±2.7 23.1±4.7 45.8±6.3 19.8±2.7 23.9±4.1 24.3±0.4 23.0±2.4 15.7±2.4 16.1±1.5 24.2±2.0 23.3±5.6 21.4±3.1 17.6±1.1 20.1±2.9 20.3±2.7

(certificate)b 6.9±1.1 7.29±0.79 17.0±4.6 42.1±9.9 13.8 ±3.6 17.3±4.3 N/A N/A 16.9±5.0 N/A 23.7±2.7 22.3±7.5 N/A N/A 21.3±8.2 23.1±6.4



1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 28 of 35

Table 3S. Biomarker ratios (Ts/Tm, H29/H30, H32S/H32R, H30/Σ(H31-H35), H33S/H33R, C27αββ/C29αββ steranes, and C27βα/C29βα diasteranes) for the Macondo crude oil (NIST2779), eighteen environmental samples (SAM-1–18), Megaplume oil seep and Blue Crude oil. The results are expressed as average values from triplicate analysis ± the standard deviation. Ts/Tm

H29/H30

H32S/H32R

H33S/H33R

H30/Σ(H31-H35)

C27αββ/C29αββ

C27βα/C29βα

steranes

diasteranes

NIST2779

1.42±0.05

0.52±0.04

1.48±0.03

1.46±0.06

0.65±0.03

0.68±0.06

0.94±0.02

SAM-1

1.49±0.02

0.56±0.03

1.36±0.01

1.42±0.07

0.65±0.06

0.68±0.02

0.95±0.03

SAM-2

1.43±0.05

0.58±0.02

1.41±0.13

1.35±0.05

0.62±0.05

0.66±0.04

0.89±0.04

SAM-3

1.49±0.10

0.55±0.01

1.36±0.03

1.34±0.10

0.66±0.02

0.72±0.03

0.91±0.04

SAM-4

1.47±0.03

0.59±0.02

1.39±0.03

1.40±0.12

0.61±0.01

0.73±0.03

0.93±0.02

SAM-5

1.49±0.08

0.57±0.01

1.31±0.07

1.37±0.05

0.62±0.03

0.69±0.02

0.90±0.02

SAM-6

1.56±0.03

0.50±0.05

1.32±0.03

1.33±0.03

0.68±0.01

0.71±0.01

0.97±0.02

SAM-7

1.53±0.09

0.53±0.06

1.35±0.09

1.30±0.01

0.60±0.01

0.67±0.05

0.94±0.05

SAM-8

1.30±0.09

0.62±0.06

1.40±0.09

1.32±0.10

0.46±0.06

0.42±0.02

0.56±0.03

SAM-9

1.43±0.11

0.49±0.03

1.39±0.11

1.49±0.11

0.67±0.05

0.74±0.06

0.96±0.02

SAM-10

1.46±0.07

0.53±0.05

1.42±0.07

1.46±0.08

0.66±0.06

0.64±0.07

0.90±0.08

SAM-11

1.42±0.10

0.52±0.05

1.41±0.08

1.32±0.12

0.60±0.02

0.66±0.07

0.91±0.09

SAM-12

1.48±0.08

0.56±0.06

1.50±0.12

1.39±0.11

0.54±0.05

0.58±0.06

0.89±0.08

SAM-13

1.50±0.07

0.51±0.05

1.46±0.08

1.36±0.09

0.60±0.07

0.62±0.06

0.96±0.06

SAM-14

1.49±0.09

0.49±0.05

1.45±0.13

1.52±0.14

0.63±0.06

0.64±0.05

1.00±0.07

SAM-15

1.33±0.05

0.59±0.05

1.57±0.15

1.52±0.15

0.55±0.05

0.58±0.06

0.92±0.09

SAM-16

1.49±0.10

0.54±0.06

1.46±0.14

1.40±0.12

0.60±0.06

0.54±0.05

0.92±0.07

SAM-17

1.37±0.05

0.54±0.03

1.41±0.09

1.49±0.07

0.46±0.04

0.40±0.03

0.60±0.04

SAM-18

1.47±0.12

0.59±0.06

1.52±0.09

1.45±0.14

0.55±0.05

0.59±0.06

0.81±0.80

Megaplume

1.00±0.05

1.01±0.05

1.48±0.05

1.44±0.08

0.52±0.04

0.84±0.07

0.82±0.08

Blue Crude

0.15±0.04

0.74±0.05

0.54±0.05

0.94±0.05

2.00±0.10

0.11±0.03

0.84±0.06

Sample


Page 29 of 35

17α(H)-22,29,30-tris-norhopane 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 50

Analyticalspectra Chemistry EI mass

5α(H),14α(H),17α(H)-20R-cholestane 7% of TIC

4% of TIC C27H48

C27H46

M+•

M+•

m/z

m/z

APCI mass spectra 17α(H)-22,29,30-tris-norhopane

44% of TIC 370 M+•

5α(H),14α(H),17α(H)-20R-cholestane

47% of TIC 372 M+•

191 95 121 149 100

150

355 ACS Paragon Plus Environment 200

m/z

250

300

350

400

50

100

357

217 149 175 203 150

200

m/z

250

300

350

400


89°W

31°N

88°W

87°W

86°W

SAM-1 SAM-5 SAM-16

90°W

SAM-3

91°W

SAM-14

92°W

SAM-11 SAM-13

93°W

SAM-15

85°W

84°W

83°W 31°N

Tallahassee

SAM-10

New Orleans SAM-12

SAM-17

SAM-2

SAM-8

SAM-7 SAM-6

30°N SAM-18

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42

Page 30 of 35

30°N

SAM-9 29°N

29°N

Deepwater Horizon explosion

SAM-4

28°N

28°N

Independence Hub

Megaplume oil seep

27°N

26°N

27°N

-100

-50

0

100

26°N

200

Kilometers

25°N

25°N 93°W

92°W

91°W

90°W

89°W 88°W 87°W ACS Paragon Plus Environment

86°W

85°W

84°W

83°W

Page 31 of 35


GC/APCI-MS/MS. Product Spectra from M+•

1 Figure 3 17α(H)-22,29,30-tris-norhopane 2 3

191



4 5 100 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 0 50 29 30 31 32 33 34 100 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 0 50 58

95 149 109

m/z 191

135 121

M+• 163

69

81

177

100

150

355 370 200

m/z

250

300

350

5α(H),14α(H),17α(H)-20R-cholestane 217

357

m/z 217 121 81

95 107

135

M+•

149 175 161 262 189 203 ACS Paragon Plus Environment

73 100

150

200

m/z

250

372 300

350

Analytical Chemistry GC/APCI-MS/MS for NIST2779 (Macondo Crude Oil) Page 32 of 35

Hopanes: Summed Signals for C27-C35 (M+• → m/z 191) H30 32 31

34 33

Ts Tm

70.00

H31S

Figure 4

H31R H32S

35

H29

RA, %

1 2 3 4 5 6 7100 19 20 8 9 12 18 E 21 30 13 11 10 25 26 D 17 22 11 1 C 9 28 12 16 29 2 14 13 10 B 8 27 15 A 14 7 3 5 15 6 4 16 23 24 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 0 50.00 60.00 41 42

H32R H 33S H33R H 34S H34R H35S H35R

C29Ts

C31

80.00

DH30 C32 M30 C33 C 34

82.00

86.00

88.00

90.00

92.00

94.00

Time

C35


80.00

84.00

90.00 Time, min

100.00

110.00

120.00

Chemistry GC/APCI-MS/MS for Analytical NIST2779 (Macondo Crude Oil)

Page 33 of 35

1 Figure 5 2

29

28

Steranes & Diasteranes

22

21

24 25

3 20 18 4 23 Sum of C27-C29 Steranes/Diasteranes 12 100 5 17 11 6 13 19 16 1 7 9 8 2 14 15 10 8 9 10 3 7 5 11 6 4 12 13 14 15 16 0 55.00 60.00 65.00 70.00 75.00 17 50.00 βαS 18 100 19 αββR 20 27 βαR αββS 21 27 22 αααS 23 αααR 24 m/z 372  217 αβR 25 αβS 26 27 28 29 0 55.00 60.00 65.00 70.00 75.00 30 50.00 βαS 31 100 αββR 32 28 αββS 33 28 βαR 34 αααS 35 αααR 36 αβS 37 m/z 386  217 αβR 38 39 40 41 42 43 0 50.00 55.00 60.00 65.00 70.00 75.00 44 βαS 45 100 29 αββ 46 29 47 R+S βαR 48 49 αααS 50 51 αβR m/z 400  217 αααR αβS 52 53 54 55 ACS Paragon Plus Environment 56 0 50.00 55.00 60.00 65.00 70.00 75.00 57 Time, min 58

26

27

RA, %

C D

A

-Diasteranes

80.00

C -Steranes

RA,%

C

B

-Diasteranes

C -Steranes

RA,%

C

80.00

-Diasteranes

C -Steranes

RA, %

C

80.00

80.00

Figure 6


Page 34 of 35

1 NIST2779 T /T SAM-1 Ts/Tm s m 2 2 2 3 βαC27/βαC29 βαC27/βαC29 1.5 1.5 4 Diasteranes H29/H30 Diasteranes H29/H30 5 1 1 6 0.5 0.5 7 0 0 8 H /H H32S/H32R 9 32S 32R C27αββ/C29αββ C27αββ/C29αββ 10 Steranes Steranes 11 12 H33S/H33R 13 H30/ΣH31‒H35 H33S/H33R H30/ΣH31‒H35 14 15 16 SAM-3 17 SAM-4 T /T Ts/Tm s m 18 2 2 C βα/C βα C βα/C βα 29 27 29 19 27 1.5 1.5 Diasteranes H29/H30 H29/H30 20 Diasteranes 1 1 21 22 0.5 0.5 23 0 0 24 H /H H32S/H32R C27αββ/C29αββ 32S 32R 25αββ/C αββ C27 29 Steranes 26 Steranes 27 28 H30/ΣH31‒H35 H33S/H33R H30/ΣH31‒H35 H33S/H33R 29 30 31 32 SAM-7 SAM-6 33 34 Ts/Tm Ts/Tm 35 C βα/C βα 2 2 C27βα/C29βα 27 29 36 Diasteranes 1.5 Diasteranes 1.5 H29/H30 H29/H30 37 1 1 38 0.5 0.5 39 0 40 0 41 C αββ/C αββ H /H H32S/H32R 27 29 32S 32R C27 42αββ/C29αββ Steranes Steranes 43 44 45 H30/ΣH31‒H35 H33S/H33R H30/ΣH31‒H35 H33S/H33R 46 47 48 49 SAM-9 SAM-10 50 Ts/Tm Ts/Tm 51 2 2 52 C27βα/C29βα C27βα/C29βα 53 Diasteranes 1.5 1.5 Diasteranes H29/H30 H29/H30 54 1 1 55 0.5 0.5 56 0 0 57 58 H32S/H32R C αββ/C αββ H32S/H32R C27αββ/C29αββ 27 29 59 Steranes Steranes 60 H30/ΣH31‒H35

H33S/H33R

SAM-12

H30/ΣH31‒H35

H33S/H33R

SAM-13 Ts/Tm

2 1.5

H29/H30


0.5 0


H32S/H32R

H30/ΣH31‒H35

H33S/H33R


Ts/Tm

2

1.5

0.5 0


H32S/H32R

H30/ΣH31‒H35

H33S/H33R

SAM-8 Ts/Tm C27βα/C29βα Diasteranes

2 1.5

0.5 0


H32S/H32R

H33S/H33R

H30/ΣH31‒H35


Ts/Tm 2 1.5

0.5 0

H32S/H32R


H33S/H33R

2 1.5

H29/H30


Ts/Tm 2 1.5

0.5

0

0

0

H32S/H32R


H33S/H33R

SAM-16 Ts/Tm

2

H29/H30


H32S/H32R


H33S/H33R

2 1.5

H29/H30


Ts/Tm 2 1.5

1

1

1

0.5

0.5

0.5


H33S/H33R

SAM-18

H32S/H32R


H33S/H33R

Ts/Tm

2 1.5

H29/H30


H32S/H32R


H33S/H33R

Blue crude

Megaplume Ts/Tm

2 1.5

H29/H30


Ts/Tm 2 1.5

1

1

1

0.5

0.5

0.5

0

0

0


H32S/H32R

H33S/H33R


H29/H30

0

0

0

H32S/H32R

H29/H30

SAM-17

Ts/Tm 1.5

H29/H30

1

0.5

SAM-15

H29/H30

1

0.5

H33S/H33R

H29/H30

1

1

H32S/H32R

H29/H30

1

1

H30/ΣH31‒H35


1.5

1




Ts/Tm 2

SAM-14

Ts/Tm C27βα/C29βα Diasteranes

SAM-2

H32S/H32R

H33S/H33R



H29/H30

H32S/H32R

H33S/H33R

Page 35 of 35

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42


Figure 7


Atmospheric Pressure Chemical Ionization

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