A Preliminary Report to the U.S. Coast Guard, Part 2 

Petroleum Hydrocarbons in Sediment from the 

Northern Gulf of Mexico Shoreline, Texas to 

Florida

By Robert J. Rosenbauer, Pamela L. Campbell, Angela Lam, Thomas D. Lorenson, 

Frances D. Hostettler, Burt Thomas, and Florence L. Wong

Open-File Report 2011-1014

U.S. Department of the Interior

U.S. Geological Survey
U.S. Department of the Interior

KEN SALAZAR, Secretary

U.S. Geological Survey

Marcia K. McNutt, Director

U.S. Geological Survey, Reston, Virginia 2011

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Suggested citation:

Rosenbauer, R.J., Campbell, P.L., Lam, A., Lorenson, T.D., Hostettler, F.D., Thomas, B., and 

Wong, F.L., 2011, Petroleum hydrocarbons in sediment from the northern Gulf of Mexico 

shoreline, Texas to Florida: U.S. Geological Survey Open-File Report 2011-1014, 22 p.

[http://pubs.usgs.gov/of/2011/1014/].

Any use of trade, product, or firm names is for descriptive purposes only and does not imply 

endorsement by the U.S. Government.

Although this report is in the public domain, permission must be secured from the individual 

copyright owners to reproduce any copyrighted material contained within this report.

Cover: A beach just south of Tampa, Fla. before a coming storm, photograph by Tom 

Lorenson
iii

Contents

Abstract ............................................................................................................................................. 1 

Introduction ....................................................................................................................................... 1 

Methods ............................................................................................................................................ 2 

 Sampling ...................................................................................................................................... 2 

 Analytical...................................................................................................................................... 2 

 Statistical Analysis ....................................................................................................................... 3 

Results .............................................................................................................................................. 4 

 Macondo-1 Well Oil...................................................................................................................... 4 

 Sediment...................................................................................................................................... 4 

 Statistical Results......................................................................................................................... 5 

Conclusions ...................................................................................................................................... 6 

Acknowledgments............................................................................................................................. 7 

References Cited .............................................................................................................................. 7 

Appendix 1. Definition of geochemical parameters used in petroleum correlation studies..............18

Appendix 2. Geochemical parameters for sediment samples .........................................................20

Appendix 3. Geochemical parameters for sediment samples used in the statistical analysis .........22

Figures

1. Location map of the sediment samples collected for this study ....................................10 

2. Chromatograms of M-1 well oil and sediment extracts (TX-48; FL-18) ......................11 

3. Heirarchical cluster diagram of 39 sediment samples and 1 tarball from the 

northern Gulf of Mexico coast and the M-1 well oil .....................................................12 

4. Distribution of biomarkers within the four statictically derived groups of oil 

compared with the M-1 well oil ....................................................................................13 

5. A 3-D depiction of a principal components analysis of sediment, tar sample and 

M-1 well oil ...................................................................................................................14 

6. Location map of sediment samples that contain petroleum ...........................................15 

Tables

1. Gulf of Mexico preimpact Macondo-1 well oil spill sampling sites ...............................................16

2. Distribution of biomarkers within groups derived from the hierarchical cluster analysis ..............17
Petroleum Hydrocarbons in Sediment from the Northern Gulf of 

Mexico Shoreline, Texas to Florida

By Robert J. Rosenbauer, Pamela L. Campbell, Angela Lam, Thomas D. Lorenson, 

Frances D. Hostettler, Burt Thomas, and Florence L. Wong

Abstract

Petroleum hydrocarbons were extracted and analyzed from shoreline sediment 

collected from the northern Gulf of Mexico (nGOM) coastline that could potentially be 

impacted by Macondo-1 (M-1) well oil. Sediment was collected before M-1 well oil 

made significant local landfall and analyzed for baseline conditions by a suite of 

diagnostic petroleum biomarkers. Oil residue in trace quantities was detected in 45 of 

69 samples. With the aid of multivariate statistical analysis, three different oil groups, 

based on biomarker similarity, were identified that were distributed geographically 

along the nGOM from Texas to Florida. None of the sediment hydrocarbon extracts 

correlated with the M-1 well oil extract, however, the similarity of tarballs collected at 

one site (FL-18) with the M-1 well oil suggests that some oil from the Deepwater 

Horizon spill may have been transported to this site in the Florida Keys, perhaps by a 

loop current, before that site was sampled. 

Introduction

From April 20 through July 15, 2010, an estimated 4.93 million barrels (1 barrel = 

42 gallons) of crude oil spilled into the northern Gulf of Mexico (nGOM) from the 

ruptured British Petroleum (BP) Macondo-1 (M-1) well located in the Mississippi 

Canyon lease block 252 (Operational Science Advisory Team, 2010). This event, 

resulting from the explosion of the Deepwater Horizon drilling rig, exceeds the previous

largest spill in U.S. waters of as much as 750,000 barrels of crude oil from the Exxon 

Valdez in Prince William Sound in 1989 (Bence and others, 1996; Wolfe and others, 

1994). In addition, 1.84 million gallons of CorexitTM dispersants were applied to the oil 

both on and below the sea surface (British Petroleum, 2010). By April 30, estimates 

placed the total spread of the oil at 3,850 square miles (10,000 km2) (National Oceanic 

and Atmospheric Administration, 2010; fig. 1), and it reportedly first made landfall at 

Santa Rosa Island in the Gulf Islands National Seashore on June 1, 2010 (National Park 

Service, 2010). Spilled oil from this event poses a potential threat to sensitive habitat 

along the shores of the nGOM. In response, the U.S. Geological Survey (USGS) 

collected near-surface beach and coastal sediment from 70 sites along the shores of the 

nGOM from Texas to Florida before estimated local landfall of oil. These sites included 

priority areas of the nGOM, such as coastal wetlands and Department of Interior (DOI) 

wetlands, shorelines, and barrier islands at highest risk for oil contamination that could 

suffer severe environmental damage if a significant amount of oil came ashore. The 

purpose of this effort was to document conditions before oil made landfall at a given site

and to characterize petroleum hydrocarbons that reside in coastal sediment samples 

before the M-1 oil spill could have any potential impact. 
2

This report complements activities of other USGS scientists and USGS 

production and research laboratories that are analyzing aliquots of the same samples for 

volatile organic compounds and other hydrocarbons, oil and grease, trace metals, 

CorexitTM surfactants, total and dissolved organic carbon characterization, bacterial 

populations capable of degrading oils, nutrients such as nitrogen and phosphorus 

compounds related to oil releases, toxicity of pore water, and benthic macroinvertebrate 

indicators of shoreline habitat condition. Results from this effort will be compared to 

similar analyses of the postimpact samples (Rosenbauer and others, 2010) collected from 

the same sites and reported in a companion report. 

Methods

Sampling

Preimpact samples of coastal sediment were obtained from 70 sites distributed in 

Texas, Louisiana, Mississippi, Alabama, and Florida that could potentially be affected by 

the 2010 Deepwater Horizon oil spill in the Gulf of Mexico. A separate tarball sample 

was isolated from sediment at one site (FL-18). Samples were collected from May

through early July 2010 from coastal sediments at depths of 4–5 inches. The sample 

designation “preimpact” is not intended to imply a conclusion about the samples based 

upon analyses. The sampling effort extended over a time period of several weeks, so 

samples designated preimpact in one location may have been collected after oil made 

landfall in other parts of the gulf. For comparison, an aliquot of the Macondo-1 well oil 

from a previous study (Rosenbauer and others, 2010) was provided by B & B Laboratory, 

College Station, Texas. The well oil was obtained by BP from the riser insertion tube 

aboard the drillship Discoverer Enterprise on May 21, 2010, and was absent of any 

defoamer or dispersant. All samples were collected, processed, and shipped under 

standard chain-of-custody protocols according to methods listed in the USGS National 

Field Manual for the Collection of Water-Quality Data (NFM) 

(http://pubs.water.usgs.gov/twri9A/) as well as other USGS standard operation 

procedures (Wilde and others, 2010). This standardized and documented set of protocols 

encompassing the entire data-collection process ensured the integrity, consistency, and 

comparability of the data from site to site and within sites.

Analytical

All samples were extracted and processed in the USGS Pacific Coastal Marine 

Science Center (PCMSC) organic geochemistry laboratory located in Menlo Park, 

California. Samples were kept frozen in their glass jars, then thawed in the same 

containers before extraction. Sediment from one site, LA-36, was not analyzed because 

of container breakage during transit (table 1). Following homogenization of the sediment 

sample, ~ 100 g of wet sediment was weighed directly into a 300-mL stoppered flask. 

Two hundred mL of dichloromethane (DCM) and 40 g of NaSO4 were added to each 

flask, which was then placed in a sonicating water bath for 90 minutes at 30°C (after

Bekins and others, 2005; Hostettler and others, 2007). The extract was then filtered 

through a champagne funnel lined with glass wool and containing 30 g NaSO4 into turbovap vessels. An additional 100 mL of DCM was added to the previously extracted 

sediment, and the sample was again sonicated for 60 minutes at 30°C. The extracts were 
3

combined in the turbo-vap vessels, evaporated with N2

Two separate fractions were collected—saturate (hexane eluent) and aromatic 

(30-percent DCM eluent). The saturate and aromatic fractions, evaporated to 0.5 mL, 

were analyzed by gas chromatography/mass spectrometry (GC/MS). The gas 

chromatograph was first maintained at 90°C for 2.0 minutes and then programmed at a 

5°C/min ramp to 310°C. The capillary column (DB-5MS: 30 m, 0.25 mm I.D. containing 

a 0.25-μm bonded phase) was directly interfaced to the ion source of the mass 

spectrometer. A separate analysis was carried out with the GC/MS in the single-ion 

monitoring mode (SIM). Compound identifications were made either by comparison with 

known standards or with published reference spectra. Selected biomarker ratios

(appendix 1) were calculated from GC/MS/SIM chromatograms of m/z 191 

(terpanes/hopanes) and 217 (steranes) using peak heights. Other ratios are generally

calculated from the chromatograms of the aromatic fraction using appropriate extracted 

ion (EI) values, but because of the low aromatic content in preimpact sediment, this 

fraction was archived. Either summed areas or peak heights of the compounds 

indentified in the GC/MS/SIM chromatograms were used to determine parameter ratios. 

Biomarker values were used to correlate the samples and group them according to their 

probable sources (Peters and others, 2008; Lorenson and others, 2009). Laboratory ID 

numbers were cross-referenced to site locations (appendix 2). 

 to near dryness, and transferred to 

10-mL KD tubes and adjusted 5 mL with hexane. For the tarball sample, ~30 mg were 

dissolved in DCM, filtered through glass wool to remove particulates, air-dried to remove 

the DCM, then taken up in 5 mL of hexane. Both sediment and tarball extracts were then 

loaded onto liquid chromatography columns for compound class separation. Each 

column was layered with 2.5 g of 5-percent deactivated neutral alumina and 2.5 g and 5.0 

g of 62 and 923 silica gels, respectively. 

Statistical Analysis

Statistical analysis (JMPTM software) of the data included hierarchical cluster 

analysis (HCA) and principal components analysis (PCA) to establish correlations among 

the oil residues. Oil-oil and oil-source rock correlations are based on the concept of 

similarity through heritage, where migrated oil collected from the environment has 

source-related compositional parameters (biomarkers) similar to the seeps or reservoirs 

and bitumen remaining in the effective source rock from which it was derived. 

Biomarkers are complex organic compounds that occur in petroleum, rocks, and 

sediments and show little change in structure from their parent organic molecules in 

living organisms; these have been used in oil and source rock correlations (Peters and 

others, 2005). The statistical chemometric analysis includes source-related biomarkers 

(appendix 1) that are not readily affected by migration, biodegradation, or thermal 

maturation and are key indicators of genetic relationships among oil and source rock 

bitumen samples (Peters and others, 2005). 

Hierarchical clustering was carried out by both the Ward’s minimum variance 

method and the K-means iterative alternating fitting process to group oil residues with 

similar characteristics. Principal components were calculated from the parameter list and 

displayed on a three-dimensional plot to discriminate between groups and detect outliers. 

The PCA also helps reduce the dimensionality of the dataset.
4

Results

Macondo-1 Well Oil

Although the focus of this study is on preimpact baseline conditions, knowledge 

of the biomarker composition of the M-1 well oil was important because (1) some M-1 

oil had reportedly made landfall at Santa Rosa Island June 1, 2010 (National Park 

Service, 2010), within the timeframe of sample collection for this study and (2) although 

designated as preimpact samples, some may have been obtained after an unrecognized 

landfall of the M-1 well oil. We therefore compared the M-1 oil signature to 

hydrocarbons in potentially impacted shoreline sediments. A second determination of the 

biomarker composition of the M-1 well oil, made for this study, was consistent with 

previous results (Rosenbauer and others, 2010). 

Rosenbauer and others (2010) identified a suite of 19 biomarker parameter ratios

that defined a chemical signature (fingerprint) of the BP M-1 well oil. Such ratios are 

used to genetically relate oil and tar to their sources (Hostettler and others, 2004; 

Kvenvolden and others, 1995; Peters and others, 2008; Lorenson and others, 2009). Of 

these ratios, 12 were particularly diagnostic of the BP M-1 oil and could be determined in 

the preimpact sediment; these 12 ratios were used for statistical analyses in this study. 

Specifically excluded from this set of ratios were pristane and phytane, because there are

confounding natural environmental inputs and losses in the oils caused by environmental 

degradation. Patterns from chromatograms of the tricyclic terpanes and hopanes in the 

191 m/z traces and of the steranes in the 217 m/z traces obtained by the GC/MS in singleion monitoring (SIM) mode showed several key visual relations for the M-1 well oil (fig. 

2A, B). Particularly notable are the tricyclic terpanes that define the triplet, the C24-

tetracyclic terpane, and the C26

Sediment

-tricyclic terpane (S and R epimers) that were uniformly 

equal (fig. 2A). Also of note is the prominence of the 18α(H)-30-norneohopane (29D)

relative to the 17α,21β(H)-30-norhopane (αβ29 (fig. 2A). The prominence of the 

diasterane epimer pair (βαC27 diasterane, S & R) is also characteristic of this oil (fig. 

2B). 

Total extractable organic matter was typically low in the preimpact sediment, 

ranging from less than 1 to 137 mg/kg and averaging 14.9 mg/kg, excluding one sample 

containing discrete tarballs that had an extractable weight of 1,830 mg/kg (table 1). The 

extractable organic content generally correlates with the presence of petroleum but often 

included some biogenic material and in some cases a water-soluble precipitate. Some 

samples with as little as 1 mg/kg extractable organic matter contained petroleum. 

The identification of oil in the sediment samples was based on the presence of 

specific saturated hydrocarbons in the mass spectra of the sediment extracts. These are 

petroleum-related biomarkers, including the tricyclic terpanes, pentacyclic hopanes, and 

steranes (Peters and others, 2005; Wang and Fingas, 2003; Wang and others, 2006). In 

particular, we focused on the C20 through C29 tricyclics, C30 hopane, C29 nor-hopane, 

the homologous series of C31 through C35 homohopanes, and the C27 through C29 

steranes. The polycyclic aromatic hydrocarbons (PAHs) were too low in abundance to be 

useful for any diagnostic purpose. 
5

The extracted hydrocarbon composition of sediment ranged from below detection, 

containing only biogenic material, to oil or possibly a mixture of oils. There was no clear 

evidence of oil residue at 24 of the sites (35 percent). The remaining 45 sites contained at

least some trace amount of oil residue, and many samples (16 of 26 in Florida, 5 of 10 in 

Alabama, 12 of 13 in Louisiana, 2 of 9 in Mississippi, and 10 of 11 in Texas) had distinct 

oil signatures. This oil likely represents inputs from either natural oil seepage, which can 

be prevalent in some areas of the nGOM (Sassen and others, 2001), or from other 

previous oil spills. One sample from Coco Plum Beach on the Florida Panhandle 

contained cubic-centimeter-size tarballs throughout. Coco Plum Beach is in the path of a 

loop current in the Straits of Florida where tarballs commonly occur (Van Vleet and 

others, 1984). Biodegradation ranking of the extracted oil ranged from 4 to 5, which is 

considered moderate (Peters and Moldowan, 1993) and allows for robust comparison 

with M-1 oil. 

Except at the tarball site (FL-18), all the GC/MS spectra obtained from the solvent 

extracts of the preimpact shoreline sediment were distinct from the reference BP M-1 

well oil (fig. 2). For example, the Ts/Tm ratio is lower, the αβC29/αβC30 ratio is higher 

(fig 2C), and the βα27D/αααC29 ratio is lower (fig. 2D) in sediment from site TX-48 

than in the BP M-1 well oil. Terpanes and hopanes extracted from the tarball at site FL18 were remarkably similar to the M-1 well oil (fig. 2A, E), but the sterane profiles were 

somewhat different (fig. 2B, F). Where the presence of oil residues was detected, a total 

of 17 individual biomarker parameters were calculated for each sediment sample using 

the saturate fraction (appendix 2). Biomarker parameters are listed in appendix 1, along 

with references to their use and other characteristics such as age, thermal maturity, 

depositional environment, degree of biodegradation, and general nature. 

Statistical Results

Differences in the mass spectra of the sediment extracts suggest that some oils 

have different sources. Because of the variety of geological conditions and ages under 

which oil was formed, every crude oil exhibits a unique biomarker fingerprint. Often 

these differences are subtle and a statistical approach is required to separate oils into 

distinct groups with different sources (Lorenson and others, 2009). Hence we carried out 

a multivariate statistical analysis of the biomarker ratios obtained from the sediment 

extracts, using HCA and PCA. 

Twelve biomarker parameters common to the preimpact sediment were used in 

the statistical analysis (appendix 3). Eight samples were excluded because of the absence 

of several of these 12 parameters. An additional four samples lacked a complete set of 12 

parameters, but in these cases an average of the missing parameter was used, a technique 

used in other chemometric biomarker analyses (Peters and others, 2008). Data previously 

acquired for the M-1 well oil (Rosenbauer and others (2010) were also included in the 

statistical analysis. 

Results of the HCA show three clusters of similar size (fig. 3) and three outliers. 

Each cluster defines a group of samples with a distinct combination of characteristic 

biomarkers (fig 4). Groups 1 (red) and 4 (orange) are distinguished by the lowest values 

for Ts/Tm and 29D/29H and the highest values for 35S/34S (table 2). Group 1 has the 

highest values for C29/C30 and C31S/C30 (table 2). Groups 1 and 4 were generally 

similar but differ by a factor of ~2 in average values of 26Tri/25Tri and C27DS/C29R 
6

(table 2). Groups 1 and 2 (green) differ significantly in most parameters. Groups 2 and 4 

differ especially in values for the triplet, C27DS/C29R, and C28R/C29R (table 2). 

One outlier from these three groups, TX-50, plots close to group 2 but has a lower 

value for the triplet and an unusually high value for the C28R/C29R. The other outliers 

are the tarball from site FL-18 and the M-1 well oil. Statistically, with the limited 

parameter list, the tarball and the M-1 well oil are grouped together but differ somewhat

in their sterane profiles (fig. 2F). 

The results of the PCA depicted in a 3-D plot show the three clusters of 

genetically related oil residues in preimpact sediment (fig. 5). The first, second, and third 

principal components are the x, y, and z axes, respectively. Three and six principal 

components explain 60 and 82 percent of the total variance, respectively. Regions 

encircled and labeled G1, G2, and G4 correlate with groups 1, 2, and 4 determined by 

HCA. The two closely spaced blue crosses are analyses of the sediment and tarball from 

FL-18, and the isolated blue cross is the M-1 well oil. 

The groups defined by the statistical analysis do not group geographically, but are 

found scattered along the entire nGOM coast from Texas to Florida (fig. 6). This 

widespead distribution of disparate oil types implies input from distant offshore seepage 

rather than from local seeps or spills as the probable petroleum sources. Geochemical 

analyses of surface seeps, produced oils, and gases suggest that the source rocks for 

GOM oils are Mesozoic and Tertiary (for example, Walters and Cassa, 1985). Walters 

and Cassa (1985) have shown that the ratio of tricyclic diterpanes to the sum of 

sesterterpane and triterpane tricyclics is a sensitive indicator of offshore Gulf Coast oils. 

Sofer (1988) used tricyclic terpanes, stable carbon isotopes of saturates, and aromatics to 

classify groups of Gulf Coast oils showing a wide range of thermal maturity. Genetically 

distinct oil groups correlate with differing source maturity and in many places overlap 

(Hood and others, 2002; Guzman-Vega and others, 2002).

None of the sediment extracts correlate with the M-1 well oil, but the similarity of 

the tarball collected at site FL-18 with the M-1 well oil brings up the possibility that some 

oil from the Deepwater Horizon spill entered a loop current and was transported to the 

Florida Keys before that tarball sample was collected. Sediment from site FL-18 was 

collected on May 24, 6 days after the National Oceanic and Atmospheric Administration 

(NOAA) reported that a small tendril of M-1 well oil had entered the loop current on May 

18 (Lubchenco, 2010). Additional analyses are underway to better compare tarballs 

intermixed with sediment collected at this site with the M-1 well oil and with other 

tarballs that are known to accumulate in this area (Van Vleet and others, 1984). 

Conclusions

Sediment samples were collected at 69 sites along the northern Gulf of Mexico 

(nGOM) coastline that could potentially be impacted by Macondo-1 (M-1) well oil, and 

these samples were analyzed for petroleum hydrocarbons. Oil residue in trace quantities 

was detected in 45 of 69 samples. With the aid of multivariate statistical analysis, three 

different oil groups were identified that were dispersed geographically along the nGOM 

from Texas to Florida. None of the sediment extracts correlated with the M-1 well oil, but 

the similarity of tarballs collected at site FL-18 to the M-1 well oil is consistent with the 

possibility that some oil from the Deepwater Horizon spill entered a loop current and was 

transported to the Florida Keys before the sampling for this study. Further studies of 
7

sediment both onshore and offshore are warranted to place these results into a larger 

context for the entire nGOM. Additional work is also required to determine the source of 

other oils found in this study, such as possible correlations with oils in the extensive 

database of petroleum biomarkers maintained by GeoMark Research LTD. 

Acknowledgments

The USGS initiated this preimpact sampling and analytical study, and additional 

funding was later provided by the U.S. Coast Guard for both the pre- and postimpact 

work. We thank Renee Takesue and Peter Swarzenski for thoughtful reviews of an earlier 

version of the manuscript that greatly improved this report. We thank also Peter Stauffer 

for critical editing and Mike Diggles for formatting the manuscript.

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Van Vleet, E.S., Sacketta, W.M., Reinhardt, S.B., and Mangin, M.E., 1984, Distribution, 

sources and fates of floating oil residues in the Eastern Gulf of Mexico: Marine 

Pollution Bulletin, v. 15, Issue 3, p. 106-110. 

Walters, T.G., and Cassa, M.R., 1985, Regional organic geochemistry of offshore 

Louisiana: Transactions Gulf Coast Association of Geological Societies, v. 35, p. 

277-286. 

Wang, Z., and Fingas, M., 2003, Development of oil hydrocarbon fingerprinting and 

identification techniques: Marine Pollution Bulletin, v. 47, p. 423-452. 

Wang, Z., Stout, S.A., and Fingas, M., 2006, Forensic fingerprinting of biomarkers for oil 

spill identification and source identification (a review): Environmental Forensics, 

v. 7, no. 2, p. 105-146. 

Waples, D.W., and Machihara, T., 1991, Biomarkers for geologists—a practical guide to 

the application of steranes and triterpanes in petroleum geology: American 

Association of Petroleum Geologists, Methods in Exploration, no. 9, 91 p. 

Wilde, F.D., Skrobialowski, S.C., and Hart, J.S., 2010, Sampling protocol for postlandfall Deepwater Horizon oil release, Gulf of Mexico, 2010: U.S. Geological 

Survey Open-File Report 2010-1191, 155 p., accessed online at 

http://pubs.usgs.gov/of/2010/1191/. 

Wolfe, D., Michel, J., Hameedi, M.J., Payne, J.R., Galt, J.A., Watabayashi, G., Braddock, 

J., Short, J., O'Claire, C., and Rice, C., 1994, The fate of the oil spilled from the 

Exxon Valde: Environmental Science & Technology, v. 28, no. 13, p.560A-568A. 
10

Figure 1. Location map of sediment samples collected for this study. The blue shading depicts the cumulative areal coverage of the 

BP M-1 well oil spill as of April 30, 2010, derived from wind, ocean currents, aerial photography, and satellite imagery (National 

Oceanic and Atmospheric Administration, 2010). Sample designations are abbreviated for clarity in location; complete sample 

numbers are listed in the tables and are prefaced by the two-letter state abbreviation. The location of the Macondo-1 well is also 

indicated.

Florida

Texas

Alabama Georgia

Mississippi

Louisiana

BP Macondo-1

(M-1)

8

9

10

11

12

13

14

15

16

17

18

19

20

21

22 23

24

25

26

23 22

24

25

26

28

29 30

31 32 33

35 36

46 47

48

1

50

51

52

53

54

55

49

2 3

4

5 6

7

56

94°W 92°W 90°W 88°W 86°W 84°W 82°W 80°W

30°N

28°N

26°N

Explanation

BP Macondo-1 (M-1)

oil extent 30 Apr 2010

0 100 200 50

Kilometers

1

2 3 4 5 6

7

8 9 10

34

37 38

39 40 41 42

43

44

45

Mississippi Alabama

Florida

89°W 88°30'W 88°W 87°30'W

30°30'N

30°15'N

30°N

0 20 40 10

Kilometers

UTM zone 15
11

Figure 2. Chromatograms of M-1 well oil (reproduced from Rosenbauer and others, 

2010) and sediment extracts (TX-48; FL-18). Selected ion monitoring (SIM) 

chromatograms of m/z 191, Hopanes (A, C, E), and m/z 217, Steranes (B, D, F). 

Compounds identified in appendix 1. Legend : Steranes, C27 to C29 regular steranes; 

Hopanes, C29 to C35 regular hopanes; 23T, C20 through C26, tricyclic terpanes; T, 

triplet, Ts and Tm, defined in appendix 1; αβ29, αβ30, αβ31 through αβ35 (S & R 

epimers), αβ-hopanes with carbon numbers. 
12

Figure 3. Heirarchical cluster diagram of 39 sediment samples, 1 tarball, and the M-1 

well oil from the northern Gulf of Mexico coast. The clusters marked in red, orange, and 

green indicates sediments with similar distribution of petroleum biomarkers. The cluster 

of blue crosses contains the sediment and tarball from site FL-18 and the M-1 well oil. 

Method = Ward

FL-9 120 0

AL-2 131 7

AL-3 101 5

AL-4 164 5

AL-7 94 5

LA-31 114 7

MS-44 130 0

MS-43

LA-22 103 0

LA-24 162 0

LA-25 100 5

LA-26 101 5

LA-28 93 0

LA-30 120 0

LA-29 140 0

LA-32 103 0

LA-33 143 0

LA-34 100 0

LA-35 94 5

FL-7 113 0

FL-8 170 0

TX-47 152 5

TX-51 131 3

TX-53 120 5

TX-54 103 6

TX-55 103 5

TX-56 120 3

TX-48 272 7

FL-18 154 5

FL-21 160 0

FL-22 130 0

FL-23 100 0

FL-24 140 0

TX-49 131 5

TX-50 142 5

TX-52 121 5

FL-18 1545 tarball

FL-19 130 0

FL-20 150 0

Macondo- 1

Dendrogram

Hierarchical Clust ering
13

Figure 4. Graphical representation of the distribution of biomarkers within groups 

derived from the hierarchical cluster analysis (HCA). Biomarkers obtained from analyses 

of preimpact sediment. Group numbers are correlated oil residues (fig. 3). 
14

Figure 5. Three-dimensional depiction of principal components scores of the M-1 well 

oil, sediment, and tarball samples. The x, y, and z axes are the first three principal 

components PC1, PC2, and PC3, respectively. Regions encircled and labeled G1, G2, and 

G4 correlate with groups 1, 2, and 4 determined by hierarchal cluster analysis (HCA). 

The two closely spaced blue crosses are analyses of the sediment and tarball from FL-18 

and the blue cross near the x-axis is the M-1 well oil. 
15

Figure 6. Location map of sediment samples containing oil. Oils groups are derived from the statistical analysis of the petroleum 

biomarkers. Group 1, circles; group 2, squares; group 3, pentagon; group 4, crosses. Oil not detected denoted by open white squares. 

The blue shading depicts the cumulative areal coverage of the BP M-1 well oil spill as of April 30, 2010 (National Oceanic and 

Atmospheric Administration, 2010). 

Texas

Alabama Georgia

Mississippi

Louisiana

Florida

BP Macondo-1

(M-1)

94°W 92°W 90°W 88°W 86°W 84°W 82°W 80°W

30°N

28°N

26°N

Explanation

group 1

group 2

group 3

group 4

few biomarkers

no oil detected

not analyzed

BP Macondo-1 (M-1)

oil extent 30 Apr 2010

0 100 200 50

Kilometers

Mississippi Alabama

Florida

89°W 88°30'W 88°W 87°30'W

0°30'N

0°15'N

30°N

0 20 40 10

Kilometers

UTM zone 15
16

Table 1. Gulf of Mexico preimpact Macondo-1 well oil spill sampling sites. 

[Site, USGS designated number for site locality; Lab ID, Internal PCMSC reference 

number; *, oil present but with limited biomarker dataset; ND, oil not detected; Group, 

statistically correlated oil residues]

Site Name Lat-dd Long-dd

Sample 

Date

Extracted 

Weight mg/kg

Oil 

present* Group 

FL-1 Gulf IS NS nr Navarre, FL 30.362389 -86.970167 5/11/10 7 ND

FL-2 Henderson Bch SP nr Destin, FL 30.382944 -86.442778 5/11/10 4 ND

FL-3 Grayton Bch SP nr Seaside, FL 30.324056 -86.155056 5/12/10 1 ND

FL-4 St. Andrews SP nr Panama City,FL 30.124722 -85.736028 5/12/10 7 ND

FL-5 St. Joe P SP nr Port St. Joe, FL 29.779167 -85.408528 5/13/10 8 *

FL-6 St George IS SP nr E Point, FL 29.697861 -84.767750 5/13/10 0 ND

FL-7 St. Marks NWR nr St. Marks, FL 30.074194 -84.180444 5/18/10 36 yes 4

FL-8 Piney Pt Bch at Cedar Key, FL 29.127750 -83.053361 5/18/10 1 yes 1

FL-9 Fort IS Gulf Bch nr Chassah., FL 28.907194 -82.690778 5/19/10 38 yes 1

FL-10 Fort DeSoto Pk nr St Pete, FL 27.624444 -82.738333 5/17/10 6 *

FL-11 Captiva IS Bch nr Captiva, FL 26.525639 -82.194222 5/20/10 7 *

FL-12 Tiger Tail Bch at Marco IS, FL 25.936139 -81.734583 5/21/10 17 ND

FL-13 NW Cape Sable Bch nr Flamingo,FL 25.224806 -81.169972 5/22/10 3 ND

FL-14 Dry Tortugas National Park, FL 24.627139 -82.873639 5/20/10 10 ND

FL-15 B Baggs Cape nr Key Biscayne, FL 25.667417 -80.155528 6/1/10 1 *

FL-16 Lloyd Bch at Ft Lauderdale, FL 26.081694 -80.109444 5/26/10 2 ND

FL-17 MacArthur Bch at W Palm Bch, FL 26.822583 -80.038056 5/27/10 2 ND

FL-18 Coco Plum Bch nr Marathon, FL 24.729250 -81.169972 5/24/10 1830 yes 3

FL-19 DBLM Tract1 nr Jupiter Inlet, FL 26.956111 -80.081667 6/16/10 6 yes 2

FL-20 BLM Tract2 nr Jupiter Inlet, FL 26.956111 -80.081944 6/16/10 58 yes 4

FL-21 BLM Tract1 nr Park Key, FL 24.650556 -81.557500 6/9/10 9 yes 1

FL-22 BLM Tract2 nr Sugarloaf Key, FL 24.617500 -81.543611 6/9/10 31 yes 4

FL-23 BLM Tract3 nr Sugarloaf Key, FL 24.616667 -81.539722 6/9/10 116 yes 4

FL-24 BLM Tract at Egmont Key, FL 27.601389 -82.763611 6/14/10 5 yes 2

FL-25 BLM Lathrop Bayou nr Panama City, F 30.040833 -85.432778 6/10/10 8 *

FL-26 Great White Heron NWR, FL 24.700833 -81.548611 7/7/10 28 *

AL-1 West Dauphin Island 30.227425 -88.326394 5/8/10 2 ND

AL-2 Dauphin Is. AL-2 30.248815 -88.184168 5/9/10 9 yes 4

AL-3 Dauphin Is. AL-3 30.246870 -88.077777 5/9/10 11 yes 1

AL-4 Fort Morgan AL-4 30.224926 -88.008330 5/8/10 1 yes 2

AL-5 Fort Morgan AL-5 30.230481 -87.904438 5/8/10 1 *

AL-6 Gulf Shores AL-6 30.241314 -87.730265 5/8/10 3 ND

AL-7 Orange Beach AL-7 30.269091 -87.581649 5/8/10 6 yes 2

AL-8 BLM-1 30.231593 -87.937772 5/24/10 5 ND

AL-9 BLM-2 30.228815 -87.867214 5/24/10 37 ND

AL-10 Fort Morgan BLM-3 30.228259 -87.831102 5/24/10 0 ND

LA-22 Jean Lafitte National Park, LA 29.742222 -90.141944 5/14/10 23 yes 1

LA-23 Cypremort Point, LA 29.735000 -91.853611 5/13/10 0 ND

LA-24 Lake Felicity, LA 29.346111 -90.429167 5/18/10 10 yes 1

LA-25 Rockefeller Refuge Beach, LA 29.635556 -92.767222 5/13/10 23 yes 4

LA-26 Sister Lake, LA 29.251944 -90.921667 5/17/10 12 yes 4

LA-28 Point Chevreuil, LA 29.573333 -91.537778 5/13/10 23 yes 2

LA-29 Crooked Bayou, LA 29.723333 -89.723611 5/18/10 6 yes 1

LA-30 Mississippi R. Gulf Outlet, LA 29.685556 -89.395833 5/7/10 1 yes 1

LA-31 Grand Isle Bch at State Park, LA 29.260278 -89.950278 5/10/10 7 yes 1

LA-32 Mississippi R. at Main Pass, LA 29.320556 -89.181944 5/7/10 6 yes 1

LA-33 Breton Sound, LA 29.588333 -89.611944 5/7/10 7 yes 4

LA-34 Miss. Sound at Grand Pass, LA 30.151944 -89.245833 5/7/10 6 yes 4

LA-35 Mississippi R. at South Pass, LA 28.997500 -89.148889 5/7/10 1 yes 2

LA-36 Mississippi R. at SW Pass, LA 28.937500 -89.398889 5/7/10 NA

MS-37 South Cat Island Beach, MS 30.219167 -89.079722 5/7/10 12 ND

MS-38 West Ship Island Beach, MS 30.207500 -88.972222 5/7/10 10 ND

MS-39 East Ship Island Beach, MS 30.232778 -88.892500 5/7/10 1 ND

MS-40 West Horn Island Beach, MS 30.240278 -88.735000 5/8/10 5 ND

MS-41 East Horn Island Beach, MS 30.222500 -88.592500 5/8/10 5 ND

MS-42 Petit Bois Island Beach, MS 30.202222 -88.426667 5/8/10 1 ND

MS-43 Pass Christian Beach, MS 30.316111 -89.236111 5/8/10 14 yes 1

MS-44 BIloxi Beach, MS 30.393333 -88.899444 5/8/10 1 yes 1

MS-45 Pascagoula Beach, MS 30.342778 -88.547778 5/8/10 3 ND

TX-46 East Sabine, LA 29.748889 -93.663333 5/10/10 5 ND

TX-47 Texas Point, TX 29.682500 -93.956389 5/10/10 14 yes 4

TX-48 Sabine Lake, TX 29.928333 -93.871389 5/10/10 16 yes 4

TX-49 High Island, TX 29.556667 -94.368333 5/10/10 137 yes 4

TX-50 East Bay nr Anahuac, TX 29.574722 -94.555833 5/10/10 5 yes 2

TX-51 Galveston Island, TX 29.304167 -94.769444 5/10/10 2 yes 2

TX-52 Trinity Bay nr Beach City,TX 29.735556 -94.836389 5/11/10 82 yes 2

TX-53 Bolivar Peninsula 29.388333 -94.719167 5/11/10 11 yes 4

TX-54 Galveston Bay nr Eagle Pt,TX 29.493611 -94.911111 5/11/10 50 yes 1

TX-55 West Bay, Galveston Is SPk 29.214167 -94.953889 5/11/10 24 yes 2

TX-56 San Luis Pass, TX 29.086667 -95.108611 5/11/10 4 yes 2
17

Table 2. Distribution of biomarkers within groups derived from the hierarchical cluster 

analysis. 

[Group headings are color coded with cluster diagram (fig. 3); biomarker ratios are 

defined in appendix 1; values are group averaged]

Biomarker Ratio Group 1 Group 4 Group 2 Group 3 Macondo-1

Ts/Tm 0.598 0.589 0.878 1.030 1.296

Triplet 0.988 0.704 1.259 2.380 1.922

22Tri/21Tri 0.574 0.601 0.741 0.270 0.268

24Tri/23Tri 0.625 0.835 0.728 0.385 0.720

26Tri/25Tri 0.936 0.540 1.028 1.280 0.968

28Tri/29Tri 0.778 0.756 1.193 0.890 1.065

C29/C30 0.925 0.794 0.786 0.585 0.448

29D/29H 0.274 0.263 0.362 0.365 0.523

C31S/C30 0.481 0.436 0.412 0.290 0.388

35S/34S 1.045 1.046 0.946 0.565 0.744

C27DS/C29R 1.292 0.584 1.412 2.385 2.789

C28R/C29R 0.467 0.379 1.236 0.195 0.483

 

 

 
18

Appendix 1. Biomarker parameter descriptions used in tarball, oil, and sediment 

statistical analyses 

Parameters used for the chemometric analysis described in text are indicated in red.

Saturate fraction: 

Triterpanes (hopanes), m/z 191 SIM chromatograms

1. Ts/Tm, 18α-22,29,30-trisnorneohopane/17α-22,29,30-trisnorhopane. This ratio is 

used as both a source and maturity parameter (Seifert and Moldowan, 1978). 

: 

2. Triplet, [C26-tricyclic terpane (S?) + C26-tricyclic terpane (R?)/C24-tetracyclic 

terpane]. This source parameter was used to distinguish coastal tar residues in 

Prince William Sound (Kvenvolden and others, 1995). Abundant C24

tetracyclic is cited (Peters and others, 2005) as indicating carbonate and 

evaporite source facies, therefore lower values of this ratio (since C24

3. 20Tri/23Tri, C

is the 

denominator) indicate this characteristic.

20 tricyclic terpane/C23

4. 22Tri/21Tri, C

tricyclic terpane. Source parameter.

22 tricyclic terpane/C21

5. 24Tri/23Tri, C

tricyclic terpane. Source parameter, used by 

Peters and others (2005) to help distinguish lithofacies. 

24 tricyclic terpane/C23

6. 26Tri/25Tri, C

tricyclic terpane. Source parameter, used by 

Peters and others (2005) to help distinguish lithofacies. 

26 tricyclic terpanes/C25

7. 28Tri/29Tri. C

tricyclic terpanes. peak areas. Source 

parameter; high values (>1) indicate a lacustrine depositional environment, 

whereas lower values indicate a marine source.

28 tricyclic terpanes/C29

8. C

tricyclic terpanes, peak areas. Source 

parameter.

29/C30

9. 29D/29H, 18α(H)-30-norneohopane/17α,21β(H)-30-norhopane. Source parameter. 

, 17α,21β(H)-30-norhopane/17α,21β(H)-hopane. This ratio is a source 

parameter adapted from Palacas and others (1984). 

10. C31S/C30

11. 35S/34S, 17α,21β(H)-29-pentakishomohopane (22S)/17α,21β(H)-29-

tetrakishomohopane (22S). Higher C

, 17α,21β(H)-homohopane (22S)/ 17α,21β(H)-hopane. Source parameter.

35 than C34

12 OI, Oleanane Index, 18α+β(H)-oleanane/17α,21β(H)-hopane. This commonly used 

source parameter indicates a contribution from Cretaceous and younger plant 

material (Peters and Moldowan, 1993). In the California coastal tars, 

oleanane is generally present, but in low amounts. 

 22S homohopanes is an 

indication of carbonate/evaporite facies or anoxic depositional environment. 

13 GI, Gammacerane Index, gammacerane/17α,21β(H)-hopane. This ratio is used as a 

source parameter; abundant gammacerane is a carbonate/evaporite facies 

indicator and a marker for highly reducing, hypersaline depositional 

environments (Peters and Moldowan, 1993). 

Steranes, m/z 217 SIM chromatograms

14. C

: 

28/C29

15. C27d S/R, βα27diasterane S/βα27diasterane R, source parameter

, 24-methyl-5α,14α,17α(H)-cholestane (20R)/ 24-ethyl-5α,14α,17α(H)-

cholestane (20R). This source parameter has been modified from discussions 

in Grantham and Wakefield (1988) and Waples and Machihara (1991). 

16. C27ds/C29s, βα27diasterane S/24-ethyl-5α,14α,17α(H)-cholestane (20S)
19

17. PAH-RI, Polycyclic Aromatic Hydrocarbon-Refractory Index. This index is a source 

parameter, the ratio of the second, usually major, peak containing the C

Aromatic fraction

26R 

and C27S members in the highly refractory C26 to C28 triaromatic sterane suite 

(TAS, m/z 231) to that of the first, usually dominant, peak in the monomethyl 

chrysenes (m/z 242) (Hostettler and others, 1999). In this very large data set it 

can be seen that this previously descriptive-only parameter does reflect a 

specific facies characteristic. PAH-RI goes from low values in shale, mid 

values in marl, and high values in carbonate (increasingly anoxic facies) 

environments. Since PAH-RI compares TAS to a typical petrogenic C1

18. ∑C2D/∑C2P, dimethyl dibenzothiophenes (m/z 212)/dimethyl phenanthrenes (m/z 

206). Source parameter indicating relative levels of sulfur-containing PAH to 

regular PAH (Kaplan and others, 1997; Bence and others, 1996). 

PAH, 

high values indicate higher levels of TAS. TAS are known to be a stable 

product of diagenesis of steranes in a reducing or anoxic environment. 

Therefore, PAH-RI is another indicator of the anoxic nature of the source 

environment. 

19. ∑C3D/∑C3P, trimethyl dibenzothiophenes (m/z 226)/trimethyl phenanthrenes (m/z 

220). Source parameter as #32. 
20

Appendix 2. All biomarker parameters for oil, sediment and tarball samples

[Parameter definitions are in appendix 1; ND, not detected] 

Sample Lab # Ts/Tm triplet 20Tri/23Tri 22Tri/21Tri 24Tri/23Tri 26Tri/25Tri 28Tri/29Tri C29/C30 29D/29H C31S/C30 35S/34S BI OI GI C27DS/C27DR C27DS/C29S C28R/C29R

FL-1 1330 10-224 0.50 1.70 ND 1.00 0.93 1.52 ND 0.92 0.36 0.49 ND ND ND ND ND ND ND

FL-2 1730 10-225 ND ND ND ND ND ND ND 0.69 ND ND ND ND ND ND ND ND ND

FL-3 1130 10-226 ND ND ND ND ND ND ND 0.69 ND ND ND ND ND ND ND ND ND

FL-4 1530 10-199 0.90 ND ND ND 0.82 ND ND 0.94 0.59 0.78 ND ND ND ND ND ND ND

FL-5 900 10-227 1.67 1.37 ND 1.22 0.89 1.02 ND 1.00 ND ND ND ND ND ND 1.57 ND ND

FL-6 1200 10-174 ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND

FL-7 1130 10-200 0.61 0.56 0.18 0.47 0.77 0.52 0.56 0.92 0.23 0.62 1.10 0.03 0.03 0.10 1.40 0.22 0.31

FL-8 1700 10-201 0.52 0.84 0.19 0.60 0.62 0.96 1.02 1.01 0.17 0.68 1.13 0.02 0.02 0.12 1.53 0.62 0.56

FL-9 1200 10-164 0.37 1.67 ND 0.30 0.78 1.00 1.05 0.69 0.35 0.40 1.01 0.05 0.07 0.04 1.44 2.30 0.54

FL-10 1600 10-202 0.86 ND ND 1.00 1.11 ND ND 0.72 0.57 0.47 ND ND ND ND ND ND ND

FL-11 1630 10-215 0.92 2.25 ND ND 0.75 1.43 ND 1.00 ND 0.75 ND ND ND ND ND ND ND

FL-12 1500 10-209 ND ND ND ND 0.78 ND ND ND ND ND ND ND ND ND ND ND ND

FL-13 1305 10-210 ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND

FL-14 945 10-211 ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND

FL-15 1300 10-212 1.17 2.25 ND 0.58 0.72 1.70 ND 0.85 0.59 0.47 ND ND ND ND ND ND ND

FL-16 1500 10-213 ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND

FL-17 1530 10-216 ND ND ND ND ND ND ND 0.69 ND ND ND ND ND ND ND ND ND

FL-18 1545 10-217 1.07 2.44 0.16 0.27 0.39 1.23 0.91 0.59 0.38 0.29 0.57 0.11 0.67 0.12 1.50 3.36 0.18

FL-18 tarball 10-236 0.99 2.32 0.17 0.27 0.38 1.33 0.87 0.58 0.35 0.29 0.56 0.05 0.58 0.11 1.65 1.41 0.21

FL-19 1300 10-237 0.83 1.13 0.27 0.70 0.74 1.03 1.12 0.85 0.29 0.48 1.11 0.07 0.09 0.09 1.67 1.33 0.40

FL-20 1500 10-238 0.57 0.66 0.25 0.47 0.72 0.71 0.72 0.43 0.23 0.29 1.33 0.02 0.02 0.04 1.27 0.27 0.18

FL-21 1600 10-218 0.83 0.55 0.17 0.63 0.56 1.02 0.53 1.09 0.33 0.47 1.11 0.05 0.08 0.17 1.59 1.47 0.29

FL-22 1300 10-219 0.15 0.57 0.94 0.55 0.77 0.24 ND 0.69 0.19 0.25 0.82 0.13 0.18 0.06 1.67 0.65 ND

FL-23 1000 10-220 0.75 0.37 0.29 0.58 0.99 0.24 0.70 0.93 0.30 0.48 0.87 0.17 0.34 0.15 1.63 0.25 0.33

FL-24 1400 10-221 0.73 1.50 0.81 0.88 0.69 1.23 ND 0.81 0.55 0.57 1.00 ND 0.22 0.22 1.29 ND 0.63

FL-25 1100 10-222 0.76 1.85 ND 0.50 0.67 1.40 ND 0.80 0.35 0.56 1.05 ND ND ND 1.00 ND ND

FL-26 1100 10-223 0.62 1.80 ND 0.56 0.65 1.72 ND 0.86 0.50 0.37 ND ND ND ND ND ND ND

AL-1 1115 10-175 ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND

AL-2 1317 10-165 0.63 1.16 ND ND 0.75 0.85 0.78 0.87 0.23 0.59 1.17 0.04 0.02 0.06 1.40 0.38 0.36

AL-3 1015 10-166 0.56 1.36 ND 1.06 0.61 0.99 1.09 0.91 0.23 0.63 1.25 0.05 0.05 0.06 1.67 0.34 0.42

AL-4 1645 10-167 1.08 1.27 ND 0.59 0.67 1.03 1.31 0.80 0.34 0.47 0.96 0.06 0.15 0.08 1.42 1.27 0.58

AL-5 1500 10-168 1.27 1.75 ND ND 0.77 1.24 ND 0.87 0.69 0.67 ND ND ND ND 1.17 0.86 1.00

AL-6 1245 10-176 ND ND ND ND 0.86 ND ND 0.83 ND ND ND ND ND ND ND ND ND

AL-7 945 10-169 1.11 1.12 ND 0.56 0.73 1.44 1.76 0.72 0.36 0.38 1.00 0.05 0.16 0.05 1.38 0.93 0.53

AL-8 1300 10-184 ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND

AL-9 1500 10-185 ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND

AL-10 1630 10-186 ND ND ND ND ND ND ND 0.86 ND ND ND ND ND ND ND ND ND
21

Appendix 2. (continued) 

Sample Lab # Ts/Tm triplet 20Tri/23Tri 22Tri/21Tri 24Tri/23Tri 26Tri/25Tri 28Tri/29Tri C29/C30 29D/29H C31S/C30 35S/34S BI OI GI C27DS/C27DR C27DS/C29S C28R/C29R

LA-22 1030 10-187 0.74 0.63 0.26 0.48 0.55 0.37 0.44 0.76 0.26 0.40 0.88 0.01 0.02 0.01 1.75 0.73 0.30

LA-23 1230 10-188 ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND

LA-24 1620 10-189 0.33 1.35 ND 0.15 0.69 1.36 0.44 1.12 0.29 0.50 1.29 0.07 ND 0.08 1.65 1.52 0.65

LA-25 1005 10-190 0.41 0.24 0.05 0.57 0.99 0.31 0.40 1.08 0.15 0.44 1.02 0.02 0.05 0.04 1.43 0.72 0.17

LA-26 1015 10-191 0.45 0.82 1.42 0.48 0.97 0.72 0.65 0.70 0.20 0.57 0.91 0.03 0.07 0.11 1.58 0.55 0.36

LA-28 930 10-192 0.97 1.39 0.10 0.53 0.78 0.99 1.23 0.73 0.34 0.36 0.87 0.05 0.17 0.03 1.57 1.37 0.30

LA-29 1400 10-194 0.29 2.07 ND ND 0.70 1.19 0.54 0.99 0.23 0.46 0.89 ND 0.14 0.50 1.64 1.15 1.23

LA-30 1200 10-193 0.51 0.64 ND 0.64 0.58 0.87 0.42 0.92 0.28 0.45 1.07 0.08 0.04 0.13 1.55 2.40 0.36

LA-31 1147 10-170 0.35 0.83 0.40 0.44 0.74 1.03 0.41 0.88 0.34 0.37 0.71 ND 0.11 ND 1.62 1.40 0.32

LA-32 1030 10-195 0.81 0.95 0.14 0.55 0.64 0.74 0.96 0.82 0.28 0.40 0.92 0.02 0.07 0.06 1.65 1.94 0.32

LA-33 1430 10-196 0.73 1.16 0.20 0.62 0.87 0.44 0.86 0.63 0.39 0.33 0.82 0.03 0.04 0.05 1.70 1.57 0.59

LA-34 1000 10-197 0.34 1.47 0.53 0.57 0.76 0.36 1.38 0.79 0.31 0.38 1.00 ND 0.16 0.13 1.17 0.88 0.94

LA-35 945 10-198 1.03 1.68 0.26 0.69 0.80 1.12 1.55 0.70 0.47 0.39 0.71 0.09 0.16 0.14 1.37 2.17 0.75

MS-37 1530 10-177 ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND

MS-38 1700 10-178 ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND

MS-39 1845 10-171 ND ND ND ND 0.80 ND ND 0.93 ND ND ND ND ND ND ND ND ND

MS-40 1400 10-179 ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND

MS-41 4641 10-172 ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND

MS-42 1215 10-180 ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND

MS-43 10-181 0.87 0.54 0.10 0.91 0.52 1.07 1.09 1.05 0.24 0.58 1.03 0.04 0.03 0.09 1.47 0.92 0.37

MS-44 1300 10-173 0.79 0.93 ND 0.57 0.55 0.97 1.24 0.94 0.29 0.54 1.29 0.05 0.05 0.04 1.55 0.97 0.41

MS-45 1630 10-182 0.85 ND ND ND 0.70 ND ND 1.05 0.67 ND ND ND ND ND ND ND ND

TX-46 1317 10-183 ND ND ND ND ND ND ND 0.93 0.79 ND ND ND ND ND ND ND ND

TX-47 1525 10-203 0.89 0.93 ND 0.77 1.09 0.61 1.05 0.74 0.37 0.33 1.03 0.05 0.19 0.08 1.63 0.81 0.36

TX-48 2727 10-214 0.65 0.59 0.33 0.49 0.77 0.77 0.83 0.88 0.21 0.47 1.15 0.05 0.07 0.06 1.44 1.02 0.26

TX-49 1315 10-228 0.68 0.47 0.04 0.77 0.70 0.74 0.60 0.64 0.30 0.32 1.13 0.13 0.10 0.06 1.38 0.33 0.29

TX-50 1425 10-229 0.85 0.70 0.31 0.64 0.74 0.71 0.92 0.72 0.35 0.31 0.89 0.03 0.11 0.06 1.69 1.32 5.57

TX-51 1313 10-204 0.67 0.98 ND 1.08 0.71 0.83 1.05 0.89 0.28 0.36 0.92 0.09 0.17 0.15 1.58 1.76 0.48

TX-52 1215 10-230 0.67 0.33 0.17 0.77 0.70 0.54 0.40 0.96 0.27 0.67 1.33 0.02 0.01 0.07 1.22 0.07 0.18

TX-53 1205 10-205 0.71 0.53 0.30 0.67 0.84 0.51 0.78 0.86 0.30 0.36 0.96 0.06 0.24 0.11 1.56 0.45 0.34

TX-54 1036 10-206 0.80 0.48 0.27 0.49 0.58 0.60 0.89 0.84 0.27 0.37 1.00 0.11 0.09 0.08 1.68 1.03 0.30

TX-55 1035 10-207 0.81 1.13 ND 0.86 0.65 0.99 0.85 0.80 0.30 0.39 0.90 0.09 0.08 0.07 1.47 1.47 2.47

TX-56 1203 10-208 0.70 1.69 ND 0.88 0.77 0.91 1.26 0.84 0.34 0.41 1.10 0.12 0.29 0.18 2.00 1.38 0.65
22

Appendix 3. Biomarker parameters for oil, sediment and tarball samples used in the statistical analysis. 

[Parameter definitions are in appendix 1; values in red are column averaged (see text); ND, not detected] 

Sample Lab # Ts/Tm triplet 22Tri/21Tri 24Tri/23Tri 26Tri/25Tri 28Tri/29Tri C29/C30 29D/29H C31S/C30 35S/34S C27DS/C29S C28R/C29R

FL-7 1130 10-200 0.61 0.56 0.47 0.77 0.52 0.56 0.92 0.23 0.62 1.10 0.22 0.31

FL-8 1700 10-201 0.52 0.84 0.60 0.62 0.96 1.02 1.01 0.17 0.68 1.13 0.62 0.56

FL-9 1200 10-164 0.37 1.67 0.30 0.78 1.00 1.05 0.69 0.35 0.40 1.01 2.30 0.54

FL-18 1545 10-217 1.07 2.44 0.27 0.39 1.23 0.91 0.59 0.38 0.29 0.57 3.36 0.18

FL-18 tarball 10-236 0.99 2.32 0.27 0.38 1.33 0.87 0.58 0.35 0.29 0.56 1.41 0.21

FL-19 1300 10-237 0.83 1.13 0.70 0.74 1.03 1.12 0.85 0.29 0.48 1.11 1.33 0.40

FL-20 1500 10-238 0.57 0.66 0.47 0.72 0.71 0.72 0.43 0.23 0.29 1.33 0.27 0.18

FL-21 1600 10-218 0.83 0.55 0.63 0.56 1.02 0.53 1.09 0.33 0.47 1.11 1.47 0.29

FL-22 1300 10-219 0.15 0.57 0.55 0.77 0.24 0.88 0.69 0.19 0.25 0.82 0.65 0.63

FL-23 1000 10-220 0.75 0.37 0.58 0.99 0.24 0.70 0.93 0.30 0.48 0.87 0.25 0.33

FL-24 1400 10-221 0.73 1.50 0.88 0.69 1.23 0.88 0.81 0.55 0.57 1.00 1.12 0.63

AL-2 1317 10-165 0.63 1.16 0.64 0.75 0.85 0.78 0.87 0.23 0.59 1.17 0.38 0.36

AL-3 1015 10-166 0.56 1.36 1.06 0.61 0.99 1.09 0.91 0.23 0.63 1.25 0.34 0.42

AL-4 1645 10-167 1.08 1.27 0.59 0.67 1.03 1.31 0.80 0.34 0.47 0.96 1.27 0.58

AL-7 945 10-169 1.11 1.12 0.56 0.73 1.44 1.76 0.72 0.36 0.38 1.00 0.93 0.53

LA-22 1030 10-187 0.74 0.63 0.48 0.55 0.37 0.44 0.76 0.26 0.40 0.88 0.73 0.30

LA-24 1620 10-189 0.33 1.35 0.15 0.69 1.36 0.44 1.12 0.29 0.50 1.29 1.52 0.65

LA-25 1005 10-190 0.41 0.24 0.57 0.99 0.31 0.40 1.08 0.15 0.44 1.02 0.72 0.17

LA-26 1015 10-191 0.45 0.82 0.48 0.97 0.72 0.65 0.70 0.20 0.57 0.91 0.55 0.36

LA-28 930 10-192 0.97 1.39 0.53 0.78 0.99 1.23 0.73 0.34 0.36 0.87 1.37 0.30

LA-29 1400 10-194 0.29 2.07 0.64 0.70 1.19 0.54 0.99 0.23 0.46 0.89 1.15 1.23

LA-30 1200 10-193 0.51 0.64 0.64 0.58 0.87 0.42 0.92 0.28 0.45 1.07 2.40 0.36

LA-31 1147 10-170 0.35 0.83 0.44 0.74 1.03 0.41 0.88 0.34 0.37 0.71 1.40 0.32

LA-32 1030 10-195 0.81 0.95 0.55 0.64 0.74 0.96 0.82 0.28 0.40 0.92 1.94 0.32

LA-33 1430 10-196 0.73 1.16 0.62 0.87 0.44 0.86 0.63 0.39 0.33 0.82 1.57 0.59

LA-34 1000 10-197 0.34 1.47 0.57 0.76 0.36 1.38 0.79 0.31 0.38 1.00 0.88 0.94

LA-35 945 10-198 1.03 1.68 0.69 0.80 1.12 1.55 0.70 0.47 0.39 0.71 2.17 0.75

MS-43 10-181 0.87 0.54 0.91 0.52 1.07 1.09 1.05 0.24 0.58 1.03 0.92 0.37

MS-44 1300 10-173 0.79 0.93 0.57 0.55 0.97 1.24 0.94 0.29 0.54 1.29 0.97 0.41

TX-47 1525 10-203 0.89 0.93 0.77 1.09 0.61 1.05 0.74 0.37 0.33 1.03 0.81 0.36

TX-48 2727 10-214 0.65 0.59 0.49 0.77 0.77 0.83 0.88 0.21 0.47 1.15 1.02 0.26

TX-49 1315 10-228 0.68 0.47 0.77 0.70 0.74 0.60 0.64 0.30 0.32 1.13 0.33 0.29

TX-50 1425 10-229 0.85 0.70 0.64 0.74 0.71 0.92 0.72 0.35 0.31 0.89 1.32 5.57

TX-51 1313 10-204 0.67 0.98 1.08 0.71 0.83 1.05 0.89 0.28 0.36 0.92 1.76 0.48

TX-52 1215 10-230 0.67 0.33 0.77 0.70 0.54 0.40 0.96 0.27 0.67 1.33 0.07 0.18

TX-53 1205 10-205 0.71 0.53 0.67 0.84 0.51 0.78 0.86 0.30 0.36 0.96 0.45 0.34

TX-54 1036 10-206 0.80 0.48 0.49 0.58 0.60 0.89 0.84 0.27 0.37 1.00 1.03 0.30

TX-55 1035 10-207 0.81 1.13 0.86 0.65 0.99 0.85 0.80 0.30 0.39 0.90 1.47 2.47

TX-56 1203 10-208 0.70 1.69 0.88 0.77 0.91 1.26 0.84 0.34 0.41 1.10 1.38 0.65