U.S. Department of the Interior

U.S. Geological Survey

Scientific Investigations Report 2012–5228

Organic Contaminants, Trace and Major Elements, and 

Nutrients in Water and Sediment Sampled in Response

to the Deepwater Horizon Oil Spill
Cover: Photograph showing the U.S. Geological Survey collecting sediment samples 

at Pascagoula Beach, Pascagoula, Miss. Photo credit: Shane Stocks, U.S. Geological 

Survey Mississippi Water Science Center.
Organic Contaminants, Trace and Major 

Elements, and Nutrients in Water and 

Sediment Sampled in Response to the 

Deepwater Horizon Oil Spill

By Lisa H. Nowell, Amy S. Ludtke, David K. Mueller, and Jonathon C. Scott

Scientific Investigations Report 2012–5228

U.S. Department of the Interior

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

KEN SALAZAR, Secretary

U.S. Geological Survey

Suzette M. Kimball, Acting Director 

U.S. Geological Survey, Reston, Virginia: 2013

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Suggested citation:

Nowell, L.H., Ludtke, A.S., Mueller, D.K., and Scott, J.C., 2013, Organic contaminants, trace and major elements, 

and nutrients in water and sediment sampled in response to the Deepwater Horizon oil spill: U.S. Geological Survey 

Open‐File Report 2012–5228, 96 p, plus appendixes.
iii

Contents

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

Introduction ....................................................................................................................................................2

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

Study Area and Site Selection............................................................................................................2

Sample Collection ................................................................................................................................3

Water Samples.............................................................................................................................6

Sediment Samples.......................................................................................................................6

Chemical Analyses ..............................................................................................................................6

Water ...........................................................................................................................................9

Sediment........................................................................................................................................9

Quality-Control Samples....................................................................................................................11

Blanks .........................................................................................................................................11

Field Replicates..........................................................................................................................12

Matrix Spikes..............................................................................................................................13

Laboratory Quality-Control Procedures.................................................................................13

Water- and Sediment-Quality Benchmarks ...................................................................................13

Human-Health Benchmarks for Water...................................................................................14

Aquatic-Life Benchmarks for Water.......................................................................................14

Toxic-Unit Benchmarks for PAH-BTEX Mixtures in Water........................................14

Marine Benchmarks.........................................................................................................14

Sediment-Quality Benchmarks................................................................................................17

Equilibrium-Partitioning Sediment Benchmarks for PAH Mixtures .........................17

Equilibrium-Partitioning Sediment Benchmarks for Individual Contaminants ......19

Empirical Sediment Benchmarks...................................................................................19

National Baseline Concentrations for Trace and Major Elements and Nutrients in 

Fine Sediment ...............................................................................................................25

Interpretation of Benchmark Exceedances .........................................................................25

Data Compilation ................................................................................................................................25

Data Analyses .....................................................................................................................................26

Results and Discussion ..............................................................................................................................28

Quality-Control Analyses...................................................................................................................28

Blank Samples............................................................................................................................28

Field Replicates..........................................................................................................................31

Matrix Spikes..............................................................................................................................32

Data Censoring....................................................................................................................................34

Censoring on the Basis of Quality-Control Results ..............................................................38

Determination of Common Censoring Thresholds ...............................................................39

Organic Contaminants in Water ......................................................................................................50

Contaminant Occurrence .........................................................................................................50

Comparison of Pre-Landfall to Post-Landfall Samples........................................................56

Comparison with Benchmarks for Human Health and Aquatic Life .................................58
iv

Contents

Results and Discussion—Continued

Organic Contaminants in Sediment ................................................................................................64

Contaminant Occurrence .........................................................................................................64

Comparison of Pre-Landfall to Post-Landfall Samples........................................................65

Comparison with Benchmarks for Aquatic Life....................................................................68

Trace and Major Elements and Nutrients in Water .....................................................................69

Constituent Occurrence ...........................................................................................................69

Comparison of Pre-Landfall to Post-Landfall Samples........................................................70

Comparison with Benchmarks for Human Health and Aquatic Life..................................74

Trace and Major Elements and Nutrients in Sediment ................................................................78

Constituent Occurrence ...........................................................................................................78

Comparison of Pre-Landfall to Post-Landfall Samples........................................................79

Comparison with Sediment-Quality Benchmarks and National Baseline 

Concentrations ............................................................................................................82

Contaminant Concentrations at Sites with Macondo-1 Well Oil Fingerprint Evidence .........83

Data Issues, Data Censoring, and Quality Control .......................................................................83

Summary and Conclusions.........................................................................................................................85

Organics in Water...............................................................................................................................85

Organics in Sediment.........................................................................................................................85

Trace and Major Elements and Nutrients in Water .....................................................................86

Trace and Major Elements and Nutrients in Sediment ................................................................86

Comparison of Pre-Landfall to Post-Landfall Samples ................................................................87

Acknowledgements.....................................................................................................................................87

References Cited .........................................................................................................................................88

Glossary.........................................................................................................................................................93

Appendix 1. Methods, Reporting levels, and Laboratories Used for Chemical Analysis for

the Deepwater Horizon Oil Spill, Gulf of Mexico, 2010.............................................................95

Appendix 2. Data Distributions for Contaminants in Water and Sediment Sampled in 

Response to the Deepwater Horizon Oil Spill, 2010..................................................................95

Appendix 3. Benchmark Exceedances for Contaminants in Water and Sediment Sampled in 

Response to the Deepwater Horizon Oil Spill, 2010..................................................................96
v

Figures

1. Map showing U.S. Geological Survey sites sampled in response to the

Deepwater Horizon oil spill, Gulf of Mexico, 2010 ....................................... 3

2. Graph showing number of analytes for which percentiles were determined 

by using four different methods, shown by contaminant class, sampling medium, 

and sampling period from the 2010 Deepwater Horizon oil spill in the Gulf of 

Mexico ....................................................................................... 27

3. Graph showing the effect of censoring threshold on the percentages of

quantified values that are retained and indeterminate values for an example

contaminant from the Deepwater Horizon oil spill, Gulf of Mexico, 2010 ............ 41

4. Graphs showing examples of the data distribution of contaminant

concentrations from the Deepwater Horizon oil spill, Gulf of Mexico, 2010 ......... 51

5. Graphs showing for selected analytes, difference between organic contaminant

concentrations in samples collected during post-landfall and pre-landfall periods

by the USGS at Deepwater Horizon oil spill sampling sites along the Gulf of

Mexico coast, 2010 ........................................................................ 59

6. Graphs showing for selected analytes, difference between trace and major

element and nutrient concentrations in samples collected during post-landfall

and pre-landfall periods by the USGS at Deepwater Horizon oil spill sampling

sites along the Gulf of Mexico coast, 2010, from west to east ........................ 72

7. Graphs showing number of benchmark exceedances for trace elements in

water in paired pre-landfall and post-landfall samples from the Deepwater

Horizon oil spill, Gulf of Mexico, 2010 ................................................... 77

Tables

1. U.S. Geological Survey pre-landfall and post-landfall sampling sites in the 

Gulf of Mexico, 2010 Deepwater Horizon oil spill ....................................... 4

2. Chemical analysis of whole water samples from the Deepwater Horizon oil spill,

Gulf of Mexico, 2010: laboratory, analytical methods, and sample treatment ...... 7

3. Chemical analysis of sediment samples from the Deepwater Horizon oil spill,

Gulf of Mexico, 2010: laboratory, analytical methods, and sample treatment ...... 10

4. Number of blanks, matrix samples for laboratory spiking, and replicate sets from

the 2010 Deepwater Horizon oil spill, submitted to U.S. Geological Survey and

TestAmerica laboratories .................................................................. 11

5A. Benchmark values for organic contaminants: toxic-unit benchmarks for PAH

and BTEX compounds in water ............................................................ 15

5B. Benchmark values for organic contaminants: supplemental aquatic-life

benchmarks for organic contaminants in water ....................................... 16

5C. Benchmark values for organic contaminants: human-health benchmarks

(recreational contact) for organic contaminants in water.............................. 17

5D. Benchmark values for organic contaminants: equilibrium-partitioning sediment

benchmark toxic units for PAH and BTEX compounds in sediment .................. 18

5E. Benchmark values for organic contaminants: supplemental aquatic-life

benchmarks for organic contaminants in sediment .................................... 20
vi

Tables

6A. Benchmark values for trace and major elements: aquatic-life benchmarks for

trace elements in water..................................................................... 22

6B. Benchmark values for trace and major elements: human-health benchmarks 

(recreational contact) for trace elements in water .................................... 22

6C. Benchmark values for trace and major elements: aquatic-life benchmarks for

trace elements in whole sediment......................................................... 23

6D. Benchmark values for trace and major elements: national baseline

concentrations for trace and major elements in the less than 63-micrometer

sediment fraction ........................................................................... 24

7. Analytes with quantified detections in field blanks collected during the

pre-landfall sampling period from the Deepwater Horizon oil spill, Gulf of 

Mexico, 2010 ................................................................................. 29

8. Analytes with quantified detections in field and trip blanks collected during 

the post-landfall sampling period and analyzed at the TestAmerica Laboratory 

in Pensacola, Florida, from the 2010 Deepwater Horizon oil spill in the Gulf of 

Mexico ....................................................................................... 30

9. Analytes with quantified detections in sediment-equipment rinsate blanks from

the Deepwater Horizon oil spill, Gulf of Mexico, 2010 ................................. 30

10. Mean relative standard deviation for water analytes with quantified detections

in at least two samples in at least four sets of replicate water samples from the

Deepwater Horizon oil spill, Gulf of Mexico, 2010 ....................................... 31

11. Mean relative standard deviation for analytes with quantified detections in at

least two samples in at least four sets of replicate sediment samples from the

Deepwater Horizon oil spill, Gulf of Mexico, 2010 ....................................... 32

12. Analytes with less than 70 percent or more than 115 percent recovery in water

matrix spikes, or with less than 50 percent or more than 115 percent recovery 

in sediment matrix spikes from the Deepwater Horizon oil spill, Gulf of Mexico, 

2010 .......................................................................................... 33

13. Constituents that were not detected in any environmental water samples

analyzed from the Deepwater Horizon oil spill, Gulf of Mexico, 2010 ............... 34

14. Constituents that were not detected in any environmental sediment samples

analyzed from the Deepwater Horizon oil spill, Gulf of Mexico, 2010 ............... 37

15. Constituents analyzed in water that were affected by censoring because of

contamination detected in laboratory, field, and trip blanks from the Deepwater

Horizon oil spill, Gulf of Mexico, 2010 ................................................... 40

16A. Optimal censoring thresholds and sample counts from the Deepwater Horizon

oil spill, Gulf of Mexico, 2010: organic contaminants in water ........................ 42

16B. Optimal censoring thresholds and sample counts from the Deepwater Horizon

oil spill, Gulf of Mexico, 2010: organic contaminants in whole sediment ............ 44
vii

Tables

16C. Optimal censoring thresholds and sample counts from the Deepwater Horizon

oil spill, Gulf of Mexico, 2010: trace and major elements and nutrients in water ... 46

16D. Optimal censoring thresholds and sample counts from the Deepwater Horizon

oil spill, Gulf of Mexico, 2010: trace and major elements and nutrients in whole

sediment .................................................................................... 48

16E. Optimal censoring thresholds and sample counts from the Deepwater Horizon

oil spill, Gulf of Mexico, 2010: trace and major elements and nutrients in the less

than 63-micrometer sediment fraction ................................................... 49

17. Summary statistics for organic contaminants in water from the Deepwater

Horizon oil spill, Gulf of Mexico, 2010 ................................................... 50

18. Statistical comparisons of contaminant concentrations in pre-landfall samples

to those in post-landfall samples from the Deepwater Horizon oil spill, Gulf of

Mexico, 2010: organic contaminants in water .......................................... 57

19. Summary of benchmark exceedances for organic contaminants in water and

sediment from the Deepwater Horizon oil spill, Gulf of Mexico, 2010 ............... 63

20. Summary statistics for organic contaminants in sediment from the Deepwater

Horizon oil spill, Gulf of Mexico, 2010 ................................................... 65

21. Statistical comparisons of contaminant concentrations in pre-landfall samples

and post-landfall samples from the Deepwater Horizon oil spill, Gulf of Mexico,

2010: organic contaminants in sediment ................................................ 66

22. Summary statistics for trace and major elements and nutrients in water from the

Deepwater Horizon oil spill, Gulf of Mexico, 2010 ....................................... 69

23. Statistical comparisons of contaminant concentrations in pre-landfall samples

to those in post-landfall samples from the Deepwater Horizon oil spill, Gulf of

Mexico, 2010: trace and major elements and nutrients in water ..................... 71

24A. Summary of benchmark and baseline exceedances for trace and major

elements from the Deepwater Horizon oil spill, Gulf of Mexico, 2010: benchmark

exceedances in water. ..................................................................... 75

24B. Summary of benchmark and baseline exceedances for trace and major

elements from the Deepwater Horizon oil spill, Gulf of Mexico, 2010: benchmark

exceedances in whole sediment and national baseline exceedances in the less

than 63-micrometer sediment fraction ................................................... 76

25. Summary statistics for trace and major elements and nutrients in whole

sediment from the Deepwater Horizon oil spill, Gulf of Mexico, 2010 ............... 78

26. Summary statistics for trace and major elements and nutrients in the less than

63-micrometer ediment fraction from the Deepwater Horizon oil spill, Gulf 

of Mexico, 2010 .............................................................................. 78

27. Statistical comparisons of contaminant concentrations in pre-landfall samples

to those in post-landfall samples from the Deepwater Horizon oil spill, Gulf of

Mexico, 2010: trace and major elements and nutrients in whole sediment and 

in the less than 63-micrometer sediment fraction ....................................... 80
viii

Conversion Factors

SI to Inch/Pound

Multiply By To obtain

Length

centimeter (cm) 0.3937 inch (in.)

millimeter (mm) 0.03937 inch (in.)

meter (m) 3.281 foot (ft) 

kilometer (km) 0.6214 mile (mi)

kilometer (km) 0.5400 mile, nautical (nmi) 

meter (m) 1.094 yard (yd) 

Area

square meter (m2) 0.0002471 acre 

square kilometer (km2) 0.3861 square mile (mi2)

Volume

cubic meter (m3) 6.290 barrel (petroleum, 1 barrel = 42 gal)

liter (L) 33.82 ounce, fluid (fl. oz)

liter (L) 2.113 pint (pt)

liter (L) 1.057 quart (qt)

liter (L) 0.2642 gallon (gal)

liter (L) 61.02 cubic inch (in3) 

Mass

gram (g) 0.03527 ounce, avoirdupois (oz)

kilogram (kg) 2.205 pound avoirdupois (lb)

Temperature in degrees Celsius (°C) may be converted to degrees Fahrenheit (°F) as follows:

°F=(1.8×°C)+32

Temperature in degrees Fahrenheit (°F) may be converted to degrees Celsius (°C) as follows:

°C=(°F-32)/1.8

Concentrations of chemical constituents in water are given either in milligrams per liter (mg/L), 

micrograms per liter (μg/L), or percent.
ix

Abbreviations and Acronyms

AET Apparent effect threshold

BTEX Benzene, toluene, ethylbenzene, xylene and related volatile (compounds)

DOC dissolved organic carbon

ERL Effects Range-Low

ERM Effects Range-Median

ESBTUi equilibrium-partitioning sediment benchmark toxic-unit concentration

EqP equilibrium-partitioning

GC/MS gas chromatography with mass spectrometry

GOM Gulf of Mexico

GPS Global Positioning System

ICP-OES inductively-coupled plasma–optical emission spectrometry

ICP-MS inductively-coupled plasma–mass spectrometry

Koc equilibrium partition coefficient

M-1 Macondo-1

MC252 Mississippi Canyon 252

MDL method detection limits

PAH polycyclic aromatic hydrocarbons

PEC probable effect concentration

PEL probable effect level

PPW paired Prentice-Wilcoxon

QC quality control

RSD relative standard deviation

SIM selective ion monitoring mode

SVOC semivolatile organic compounds

TEC threshold effect concentration

TEL threshold effect level

TOC total organic carbon

TU toxic unit

VOC volatile organic compounds

Organizations

API American Petroleum Institute

BLM Bureau of Land Management

BP British Petroleum

NOAA National Oceanic and Atmospheric Administration

NWQL USGS National Water Quality Laboratory

OCRL Organic Carbon Research Laboratory

SCL USGS Sediment Chemistry Laboratory

USEPA U.S. Environmental Protection Agency

USGS U.S. Geological Survey

Units of measurement

mg/kg milligram per kilogram

μg/g microgram per gram

μg/kg microgram per kilogram

μg/L microgram per liter

μm micrometer
x

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Organic Contaminants, Trace and Major Elements, and 

Nutrients in Water and Sediment Sampled in Response to 

the Deepwater Horizon Oil Spill

By Lisa H. Nowell, Amy S. Ludtke, David K. Mueller, and Jonathon C. Scott

Abstract

Beach water and sediment samples were collected along 

the Gulf of Mexico coast to assess differences in contaminant 

concentrations before and after landfall of Macondo-1 well 

oil released into the Gulf of Mexico from the sinking of 

the British Petroleum Corporation’s Deepwater Horizon 

drilling platform. Samples were collected at 70 coastal sites 

between May 7 and July 7, 2010, to document baseline, or 

“pre-landfall” conditions. A subset of 48 sites was resampled 

during October 4 to 14, 2010, after oil had made landfall on 

the Gulf of Mexico coast, called the “post-landfall” sampling 

period, to determine if actionable concentrations of oil were 

present along shorelines. 

Few organic contaminants were detected in water; 

their detection frequencies generally were low and similar 

in pre-landfall and post-landfall samples. Only one 

organic contaminant—toluene—had significantly higher 

concentrations in post-landfall than pre-landfall water 

samples. No water samples exceeded any human-health 

benchmarks, and only one post-landfall water sample 

exceeded an aquatic-life benchmark—the toxic-unit 

benchmark for polycyclic aromatic hydrocarbons (PAH) 

mixtures. In sediment, concentrations of 3 parent PAHs 

and 17 alkylated PAH groups were significantly higher 

in post-landfall samples than pre-landfall samples. One 

pre-landfall sample from Texas exceeded the sediment 

toxic-unit benchmark for PAH mixtures; this site was not 

sampled during the post-landfall period. Empirical upper 

screening-value benchmarks for PAHs in sediment were 

exceeded at 37 percent of post-landfall samples and 22 percent 

of pre-landfall samples, but there was no significant difference 

in the proportion of samples exceeding benchmarks between 

paired pre-landfall and post-landfall samples. Seven sites had 

the largest concentration differences between post-landfall 

and pre-landfall samples for 15 alkylated PAHs. Five of these 

seven sites, located in Louisiana, Mississippi, and Alabama, 

had diagnostic geochemical evidence of Macondo-1 oil in 

post-landfall sediments and tarballs. 

For trace and major elements in water, analytical 

reporting levels for several elements were high and variable. 

No human-health benchmarks were exceeded, although 

these were available for only two elements. Aquatic-life 

benchmarks for trace elements were exceeded in 47 percent 

of water samples overall. The elements responsible for the 

most exceedances in post-landfall samples were boron, copper, 

and manganese. Benchmark exceedances in water could 

be substantially underestimated because some samples had 

reporting levels higher than the applicable benchmarks (such 

as cobalt, copper, lead and zinc) and some elements (such as 

boron and vanadium) were analyzed in samples from only 

one sampling period. For trace elements in whole sediment, 

empirical upper screening-value benchmarks were exceeded 

in 57 percent of post-landfall samples and 40 percent of 

pre‐landfall samples, but there was no significant difference 

in the proportion of samples exceeding benchmarks between 

paired pre-landfall and post-landfall samples. Benchmark 

exceedance frequencies could be conservatively high because 

they are based on measurements of total trace-element 

concentrations in sediment. In the less than 63-micrometer 

sediment fraction, one or more trace or major elements were 

anthropogenically enriched relative to national baseline values 

for U.S. streams for all sediment samples except one. Sixteen 

percent of sediment samples exceeded upper screeningvalue benchmarks for, and were enriched in, one or more 

of the following elements: barium, vanadium, aluminum, 

manganese, arsenic, chromium, and cobalt. These samples 

were evenly divided between the sampling periods. 

 Aquatic-life benchmarks were frequently exceeded 

along the Gulf of Mexico coast by trace elements in both 

water and sediment and by PAHs in sediment. For the most 

part, however, significant differences between pre-landfall 

and post-landfall samples were limited to concentrations of 

PAHs in sediment. At five sites along the coast, the higher 

post-landfall concentrations of PAHs were associated with 

diagnostic geochemical evidence of Deepwater Horizon 

Macondo-1 oil. 
2 Contaminants in Water and Sediment Sampled in Response to the Deepwater Horizon Oil Spill 

Introduction 

On April 20, 2010, the British Petroleum (BP) 

Corporation’s Deepwater Horizon Mississippi Canyon 252 

(MC252) drilling platform sank following an explosion, 

and oil and gas began to be released into the northern Gulf 

of Mexico (GOM) from the ruptured Macondo-1 (M-1) 

well approximately 5,000 feet below the sea surface. About 

4.93 million barrels (205.8 million gallons) of oil were 

released into the northern GOM by the time the well was 

successfully capped on July 15, 2010 (Operational Science 

Advisory Team, 2010). To disperse the oil, 1.84 million 

gallons of chemical dispersants were applied to surface oil and 

at the well-head (Operational Science Advisory Team, 2010). 

In response to the threat of oil affecting sensitive habitat 

along the shores of the GOM, the U.S. Geological Survey 

(USGS) collected near-surface beach water and sediment at 

coastal sites from Texas to Florida, both before and after the 

oil made landfall on the GOM coast. “Pre-landfall” samples 

were collected from May 7 to July 7, 2010, and “post-landfall” 

samples were collected on August 23 and from October 4 to 

14, 2010. The post-landfall study was requested by the U.S. 

Coast Guard (Wilde and Skrobialowski, 2011) and was used 

in conjunction with data from other sources, including the 

U.S. Environmental Protection Agency, National Oceanic 

and Atmospheric Administration, the GOM coast states, and 

BP, to assess the distribution of actionable—that is, amenable 

to removal actions—oil-related chemicals that remain in the 

water column, sediments, or both, and to inform decision 

makers on further oil-removal operations (Operational Science 

Advisory Team, 2010; Unified Area Command, 2010).

The purpose of this report is to characterize the water and 

sediment chemistry in pre-landfall and post-landfall samples 

and to ascertain whether there were significant changes 

between the two sampling periods. This report complements 

activities of other USGS scientists and USGS production and 

research laboratories who are determining surfactants in water 

samples; analyzing geochemical markers for the presence 

of M-1 oil, also called MC252 oil, in sediment and tarballs; 

evaluating bacterial populations capable of degrading oils; 

assessing the toxicity of sediment pore water to the sea urchin 

(Arbacia punctulata); and assessing benthic macroinvertebrate 

indicators of shoreline habitat conditions (Donna N. Myers, 

Chief, Office of Water Quality, U.S. Geological Survey, 

Reston, Va., written commun., September 9, 2011).

Specific objectives of this report are the following:

• Summarize the occurrence of organic contaminants, 

trace and major elements, and nutrients in water 

and sediment samples at sites along the GOM 

coast sampled by the USGS before and after oil 

made landfall.

• Compare contaminant concentrations in prelandfall samples to post-landfall samples for water 

and sediment.

• Compare measured concentrations of contaminants 

to applicable existing benchmarks for protection of 

human health, aquatic life, and sediment quality.

This report presents one of multiple lines of evidence 

documenting conditions along the GOM coast before and after 

landfall of M-1 oil. 

Methods 

This study had two sample collection periods: 

pre-landfall and post-landfall. Pre-landfall samples were 

collected from May 7 to July 7, 2010, which was after the oil 

spill began, but before oil made landfall on the GOM coast. 

Post-landfall samples were collected on August 23 and from 

October 4 to 14, 2010, after oil made landfall at the sampled 

sites. Post-landfall sampling was carried out at a subset of the 

pre-landfall sampling sites, plus one oil-affected site that was 

not sampled during the pre-landfall period. 

Although the sample-collection methods were mostly 

the same during pre-landfall and post-landfall periods, the 

priorities for chemical analyses changed in some ways 

between the pre-landfall and post-landfall periods as more 

information became available from the National Oceanic 

and Atmospheric Administration (NOAA) and the U.S. 

Environmental Protection Agency (USEPA) about methods 

and priorities for oil-related chemical contaminant testing 

(Operational Science Advisory Team, 2010, appendix F). As 

a result, the choice of some chemical analysis methods and 

laboratories was revised for the post-landfall period period. 

Differences in methods between the two sampling periods are 

described in the “Chemical Analyses” section.

Study Area and Site Selection

The initial response of the USGS to the Deepwater 

Horizon oil spill required rapid mobilization to collect 

water and sediment samples before landfall of the oil in 

order to establish a baseline chemical and biological profile. 

This baseline profile could then be used to understand 

any post-landfall effects on, or changes to, GOM coastal 

environments (Wilde and Skrobialowski, 2011). The USGS 

Water Science Centers in Texas, Louisiana, Mississippi, 

Alabama, and Florida coordinated efforts to sample water 

and sediments at 70 sites from beaches, barrier islands, and 

coastal wetlands that could be adversely affected by oil from 

the spill coming ashore (fig. 1). High priority was given to 

coastal wetlands, Department of Interior lands at risk for oil 

contamination, such as National Wildlife Refuges, Bureau of 

Land Management (BLM) lands, National Seashore areas, 

and State Parks (Rosenbauer and others, 2010; Donna Myers, 

Chief, Office of Water Quality, U.S. Geological Survey, 

Reston, Va., written commun., September 9, 2011). The 
Methods 3

purpose of the sampling was to define pre-landfall conditions 

in the physical, chemical, biological, and microbiological 

quality of the nearshore environment. Pre-landfall samples 

were collected between May 7 and July 7, 2010 (fig. 1; 

table 1). Global Positioning System (GPS) coordinates were 

recorded at each site so that any subsequent samples could be 

collected in the same location. 

Post-landfall sampling was carried out following a 

request by the U.S. Coast Guard to assess whether actionable 

levels of Deepwater Horizon-related oil-spill contamination 

were present after the extensive clean-up efforts of coastal 

areas by BP (Wilde and Skrobialowski, 2011). Sampling was 

performed by the same USGS Water Science Centers that 

collected data for the pre-landfall assessment. Post-landfall 

samples were collected at 48 of the original 70 pre-landfall 

sites plus 1 oil-affected wetland site at Bay Jimmy, Louisiana, 

which was not sampled before landfall, making a total of 

71 sites (fig. 1; table 1). Post-landfall sites were selected 

from among the pre-landfall site locations on the basis of the 

extent of oil observed at the surface, as ascertained from ships, 

aircraft, satellites, and in situ sampling; knowledge of the 

nearshore physical oceanography, that is, movement of water 

and sediments; and trajectory modeling by NOAA (National 

Oceanic and Atmospheric Adminsitration, 2010; Unified Area 

Command, 2010). The purpose of the post-landfall sampling 

was to document residual, or actionable, oil. 

Sample Collection 

One water sample and one composite sediment sample 

were collected at each pre-landfall and post-landfall site by 

personnel from the USGS Water Science Centers from the 

GOM coastal states. All pre-landfall samples were collected 

between May 7 and July 7, 2010. All post-landfall samples 

were collected between October 4 and 14, 2010, except the 

Bay Jimmy site, which was sampled on August 23, 2010 

(table 1). Post-landfall sampling took place after the arrival 

of M-1 oil at the sampled sites. USGS field teams collected 

pre-landfall and post-landfall samples and site data by 

following protocols and procedures described in Wilde and 

Skrobialowski (2011) and in the USGS National Field Manual 

for the Collection of Water-Quality Data (variously dated). 

Post-landfall samples at each site were collected at, or close to, 

the pre-landfall sampling location (Wilde and Skrobialowski, 

2011). All samples of water and sediment were collected 

near the land/water interface, as described in the following 

sections. Samples were intended to be representative of 

ambient conditions at the time of sample collection (Wilde and 

Skrobialowski, 2011). Water samples were collected first and 

packed in coolers, and then sediment samples were collected. 

The collected samples were held on ice at 4 degrees Celsius 

(°C) after collection and during transport under chain-ofcustody to the respective laboratories for chemical analysis.

Gulf of Mexico

A t l a n t i c O c e a n

GEORGIA

ALABAMA

MISSISSIPPI

LOUISIANA

TEXAS

FLORIDA

ARKANSAS

95° 90° 85° 80°

30°

25°

EXPLANATION

Mississippi Canyon 252 well head location

Sites where post-landfall M-1 oil fingerprint detected

Post-landfall sampling sites

Pre-landfall sampling sites

0

0 100 200 300 MILES

100 200 300 KILOMETERS

FL-18

LA-6

LA-34

LA-36 LA-35

LA-33 LA-32

LA-31

LA-30 LA-29 LA-22

MS-44 MS-45

MS-43

MS-42

MS-41

MS-40

MS-39

MS-38

MS-37 AL-10

AL-9

AL-8

AL-7

AL-6

AL-5 AL-4

AL-3

AL-2

AL-1

TX-56

TX-55

TX-54

TX-52

TX-51

TX-49TX-48

TX-47

LA-46

LA-28

LA-26

LA-25

LA-24

LA-23

FL-12

TX-50

TX-53

FL-9

FL-8

FL-7

FL-6

FL-5

FL-4 FL-3 FL-2

FL-1

FL-26

FL-25

FL-24

FL-23

FL-22

FL-21

FL-20 FL-19

FL-17

FL-16

FL-15

FL-14

FL-13

FL-11

FL-10

Pacific Ocean

UNITED

STATES

MEXICO

CANADA

Map

Area Atlantic Ocean

Gulf of

Mexico

Figure 1. U.S. Geological Survey sites sampled in response to the Deepwater Horizon oil spill, Gulf of Mexico, 2010. Modified from 

Wilde and Skrobialowski (2011) by Gregory Wetherbee and David Strong
4 Contaminants in Water and Sediment Sampled in Response to the Deepwater Horizon Oil Spill Table 1. U.S. Geological Survey pre-landfall and post-landfall sampling sites in the Gulf of Mexico, 2010 Deepwater Horizon oil spill.—Continued [Sample dates are expressed as MM/DD/YY. Abbreviations: Ala, Alabama; BLM, Bureau of Land Management; dd, decimal degrees; Fla., Florida; La., Louisiana; M-1, Macondo-1 well; Miss., Mississippi; NWISweb, online National Water Information System (http://nwis.waterdata.usgs.gov/usa/nwis/qwdata); NWR, National Wildlife Refuge; St., Saint; Tex., Texas; USGS, U.S. Geological Survey; WSC, Water Science Center; –, no post-landfall sample was collected] Map number Station identifier Site name Latitude (dd) Longitude (dd) USGS WSC Dates that site was sampled M-1 oil in post-landfall1 Post-landfall Pre-landfall2 Sediment Tarball FL-1 302144086581200 Gulf Island National Seashore near Navarre, Fla. 30.36239 –86.9702 Fla. 10/04/10 05/11/10 Mix No FL-2 302258086263400 Henderson Beach State Park near Destin, Fla. 30.38294 –86.4428 Fla. 10/05/10 05/11/10 No Yes FL-3 301926086091800 Grayton Beach State Park near Seaside, Fla. 30.32406 –86.1551 Fla. 10/05/10 05/12/10 Yes – FL-4 300729085440900 St. Andrews State Park near Panama City, Fla. 30.12472 –85.736 Fla. 10/11/10 05/12/10 No – FL-5 294645085243000 St. Joseph Peninsula State Park near Port St. Joe, Fla. 29.77917 –85.4085 Fla. 10/13/10 05/13/10 No – FL-6 294152084460300 St. George Island State Park near E Point, Fla. 29.69786 –84.7678 Fla. 10/06/10 05/13/10 No – FL-7 300427084105000 St. Marks NWR near St. Marks, Fla. 30.07419 –84.1804 Fla. 10/07/10 05/18/10 No – FL-8 290740083031200 Piney Point Beach at Cedar Key, Fla. 29.12775 –83.0534 Fla. – 05/18/10 – – FL-9 285425082412600 Fort Island Gulf Beach near Chassahowitzka, Fla. 28.90719 –82.6908 Fla. – 05/19/10 – – FL-10 273728082441800 Fort DeSoto Park near St. Petersburg, Fla. 27.62444 –82.7383 Fla. – 05/17/10 – – FL-11 263132082114000 Captiva Island Beach near Captiva, Fla. 26.52564 –82.1942 Fla. – 05/20/10 – – FL-12 255609081440700 Tiger Tail Beach at Marco Island, Fla. 25.93614 –81.7346 Fla. – 05/21/10 – – FL-13 251329081101100 Northwest Cape Sable Beach near Flamingo, Fla. 25.22481 –81.17 Fla. – 05/22/10 – – FL-14 243737082522500 Dry Tortugas National Park, Fla. 24.62714 –82.8736 Fla. – 05/20/10 – – FL-15 254002080092000 Bill Baggs Cape near Key Biscayne, Fla. 25.66742 –80.1555 Fla. – 06/01/10 – – FL-16 260454080063400 Lloyd Beach at Fort Lauderdale, Fla. 26.08169 –80.1094 Fla. – 05/26/10 – – FL-17 264921080021700 MacArthur Beach at West Palm Beach, Fla. 26.82258 –80.0381 Fla. – 05/27/10 – – FL-182 244345081000600 Coco Plum Beach near Marathon, Fla. 24.72925 –81.17 Fla. – 05/24/10 – – FL-19 265722080045400 BLM Tract1 near Jupiter Inlet, Fla. 26.95611 –80.0817 Fla. – 06/16/10 – – FL-20 265722080045500 BLM Tract2 near Jupiter Inlet, Fla. 26.95611 –80.0819 Fla. – 06/16/10 – – FL-21 243902081332700 BLM Tract1 near Park Key, Fla. 24.65056 –81.5575 Fla. – 06/09/10 – – FL-22 243703081323700 BLM Tract2 near Sugarloaf Key, Fla. 24.6175 –81.5436 Fla. – 06/09/10 – – FL-23 243700081322300 BLM Tract3 near Sugarloaf Key, Fla. 24.61667 –81.5397 Fla. – 06/09/10 – – FL-24 273605082454900 BLM Tract at Egmont Key, Fla. 27.60139 –82.7636 Fla. – 06/14/10 – – FL-25 300223085260800 BLM Lathrop Bayou near Panama City, Fla. 30.03894 –85.4355 Fla. 10/12/10 06/10/10 No – FL-26 244325081351500 Marvin Key at Great White Heron NWR, Fla. 24.70981 –81.6446 Fla. – 07/07/10 – – AL-1 301338088193500 West Dauphin Island, Ala. 30.22743 –88.3264 Ala. 10/13/10 05/08/10 Mix Yes AL-2 301455088110300 Dauphin Island, AL-2 30.24881 –88.1842 Ala. 10/07/10 05/09/10 No –

AL-3 301448088044000 Dauphin Island, AL-3 30.24687 –88.0778 Ala. 10/06/10 05/09/10 No –AL-4 301329088003000 Fort Morgan, AL-4 30.22493 –88.0083 Ala. 10/12/10 05/08/10 Yes Yes

AL-5 301349087541600 Fort Morgan, AL-5 30.23048 –87.9044 Ala. 10/13/10 05/08/10 Yes Yes

AL-6 301428087434900 Gulf Shores, Ala. 30.24131 –87.7303 Ala. 10/14/10 05/08/10 Mix Yes

AL-7 301608087345400 Orange Beach, Ala. 30.26909 –87.5816 Ala. 10/14/10 05/08/10 Mix Yes

AL-8 301353087561600 BLM-1, Ala. 30.23159 –87.9378 Ala. 10/13/10 05/24/10 Yes Yes

AL-9 301343087520200 BLM-2, Ala. 30.22881 –87.8672 Ala. 10/14/10 05/24/10 Yes Yes

AL-10 301341087495200 Fort Morgan BLM-3, Ala. 30.22826 –87.8311 Ala. 10/14/10 05/24/10 Mix Yes

LA-6 292708089521400 Bay Jimmy at Northeast Barataria Bay, La. 29.45222 –89.8706 La. 08/23/10 – Yes –

LA-22 294432090083100 Jean Lafitte National Park, La. 29.74222 –90.1419 La. 10/13/10 05/14/10 No –

Table 1. U.S. Geological Survey pre-landfall and post-landfall sampling sites in the Gulf of Mexico, 2010 Deepwater Horizon oil spill.
Methods 

5

Table 1. U.S. Geological Survey pre-landfall and post-landfall sampling sites in the Gulf of Mexico, 2010 Deepwater Horizon oil spill.—Continued[Sample dates are expressed as MM/DD/YY. Abbreviations: Ala, Alabama; BLM, Bureau of Land Management; dd, decimal degrees; Fla., Florida; La., Louisiana; M-1, Macondo-1 well; Miss., Mississippi; NWISweb, online National Water Information System (http://nwis.waterdata.usgs.gov/usa/nwis/qwdata); NWR, National Wildlife Refuge; St., Saint; Tex., Texas; USGS, U.S. Geological Survey; WSC, Water 

Science Center; –, no post-landfall sample was collected]

Map 

number Station identifier Site name Latitude (dd) Longitude (dd) USGS WSC Dates that site was sampled M-1 oil in post-landfall1 Post-landfall Pre-landfall2 Sediment Tarball

LA-23 294406091511300 Cypremort Point, La. 29.735 –91.8536 La. 10/05/10 05/13/10 No –

LA-24 292046090254500 Lake Felicity, La. 29.34611 –90.4292 La. 10/12/10 05/18/10 No –

LA-25 293808092460200 Rockefeller Refuge Beach, La. 29.63556 –92.7672 La. 10/07/10 05/13/10 No –

LA-26 291507090551800 Sister Lake, La. 29.25194 –90.9217 La. 10/08/10 05/17/10 No –

LA-28 293424091321600 Point Chevreuil, La. 29.57333 –91.5378 La. 10/05/10 05/13/10 No –

LA-29 294324089432500 Crooked Bayou, La. 29.72333 –89.7236 La. 10/13/10 05/18/10 No –

LA-30 294108089234500 Mississippi River Gulf Outlet, La. 29.68556 –89.3958 La. 10/13/10 05/07/10 No –

LA-31 291537089570100 Grand Isle Beach at State Park, La. 29.26028 –89.9503 La. 10/14/10 05/10/10 Yes3 Yes3

LA-32 291914089105500 Mississippi River at Main Pass, La. 29.32056 –89.1819 La. 10/07/10 05/07/10 No –

LA-33 293518089364300 Breton Sound, La. 29.58833 –89.6119 La. 10/13/10 05/07/10 No –

LA-34 300907089144500 Mississippi Sound at Grand Pass, La. 30.15194 –89.2458 La. 10/11/10 05/07/10 No –

LA-35 285951089085600 Mississippi River at South Pass, La. 28.9975 –89.1489 La. 10/07/10 05/07/10 No –

LA-36 285615089235600 Mississippi River at Southwest Pass, La. 28.9375 –89.3989 La. 10/14/10 05/07/10 Yes –

LA-46 294456093394801 East Sabine, La. 29.74889 –93.6633 La. 10/06/10 05/10/10 No –

MS-37 301309089044700 South Cat Island Beach, Miss. 30.21917 –89.0797 Miss. 10/14/10 05/07/10 Yes Yes

MS-38 301227088582000 West Ship Island Beach, Miss. 30.2075 –88.9722 Miss. 10/14/10 05/07/10 No –

MS-39 301358088533300 East Ship Island Beach, Miss. 30.23278 –88.8925 Miss. 10/11/10 05/07/10 No Yes

MS-40 301425088440600 West Horn Island Beach, Miss. 30.24028 –88.735 Miss. 10/12/10 05/08/10 Yes Yes

MS-41 301321088353300 East Horn Island Beach, Miss. 30.2225 –88.5925 Miss. 10/12/10 05/08/10 No Yes

MS-42 301208088253600 Petit Bois Island Beach, Miss. 30.20222 –88.4267 Miss. 10/13/10 05/08/10 Yes Yes

MS-43 301858089141000 Pass Christian Beach, Miss. 30.31611 –89.2361 Miss. 10/08/10 05/08/10 No Yes

MS-44 302336088535800 Biloxi Beach, Miss. 30.39333 –88.8994 Miss. 10/07/10 05/08/10 No No

MS-45 302034088325200 Pascagoula Beach, Miss. 30.34278 –88.5478 Miss. 10/14/10 05/08/10 No No

TX-47 294057093572301 Texas Point, Tex. 29.6825 –93.9564 Tex. 10/06/10 05/10/10 No –

TX-48 295542093521701 Sabine Lake, Tex. 29.92833 –93.8714 Tex. – 05/10/10 – –

TX-49 293324094220601 High Island, Tex. 29.55667 –94.3683 Tex. 10/07/10 05/10/10 No –

TX-50 293429094332101 East Bay near Anahuac, Tex. 29.57472 –94.5558 Tex. – 05/10/10 – –

TX-51 291815094461001 Galveston Island, Tex. 29.30417 –94.7694 Tex. 10/13/10 05/10/10 No3 –

TX-52 294408094501101 Trinity Bay near Beach City, Tex. 29.73556 –94.8364 Tex. – 05/11/10 – –

TX-53 292318094430901 Bolivar Peninsula, Tex. 29.38833 –94.7192 Tex. 10/07/10 05/11/10 No –

TX-54 292937094544001 Galveston Bay near Eagle Point, Tex. 29.49361 –94.9111 Tex. – 05/11/10 – –

TX-55 291251094571401 West Bay, Galveston Island State Park, Tex. 29.21417 –94.9539 Tex. 10/14/10 05/11/10 No3 –

TX-56 290512095063101 San Luis Pass, Tex. 29.08667 –95.1086 Tex. 10/05/10 05/11/10 No –
6 Contaminants in Water and Sediment Sampled in Response to the Deepwater Horizon Oil Spill 

Water Samples

Water samples were collected to represent surf and 

suspended-sediment conditions at the time of sampling (Wilde 

and Skrobialowski, 2011). Samples were collected in wadable 

water about 60 to 90 centimeters (cm) deep by using the 

direct dip method. Samples were collected from depths of 

15 to 30 cm below the surface, and at least 15 cm from the sea 

bottom to avoid collection of re-suspended bottom material. In 

general, sample containers were submerged to an appropriate 

depth, uncapped to fill the container to the appropriate volume, 

and recapped underwater. For analysis of trace and major 

elements and nutrients, water was collected in field-rinsed 

bottles, then poured into smaller sample bottles containing 

the appropriate chemical preservative (table 2). Bottles used 

for organic-contaminant samples were not field rinsed prior to 

sample collection to avoid over-representing oil in the water 

sample (Wilde and Skrobialowski, 2011). Quality-control 

(QC) samples collected for water included field (ambient) 

blanks, trip blanks, matrix spikes, and field replicates; 

these are described later in the report. Water samples were 

preserved, if appropriate, then stored on ice in coolers and 

shipped chilled at less than 4°C to the appropriate laboratory. 

Table 2 lists the laboratory, method code, sample containers, 

and preservatives for each class of analytes determined in 

water samples. 

Sediment Samples

Wet-sediment core samples were collected from a 

2-square meter or larger area at the land/water interface, or 

swash zone, on beaches and from bottom materials of streams 

that dissect wetland or marsh areas (Wilde and Skrobialowski, 

2011). For post-landfall samples, samples were collected 

from an area and at a depth horizon to which oil could have 

penetrated (Wilde and Skrobialowski, 2011). Beach sediment 

samples were collected to a depth of 25 cm from the swash 

zone by using a Teflon scoop or core tube and were stored in 

a Teflon-lined bucket. Where possible, post-landfall sediment 

was collected at a comparable stage of tide as the pre-landfall 

sample collection at the same site. Marsh sediment samples 

were collected from a depth of 10 to 15 cm in submerged 

sediment by using a Teflon scoop and were stored in a 

Teflon‐lined bucket. A single bulk-sediment sample was 

subdivided into subsamples for different analyses, including 

various chemical contaminants, percent moisture, pore-water 

toxicity, microorganisms, and oil-fingerprinting characteristics. 

The sub-samples for chemical analyses were chilled to less 

than 4°C and shipped to the appropriate laboratory (table 3). 

Chemical Analyses 

Water and sediment samples were analyzed for a variety 

of contaminants known to be associated with oil. Crude oil 

contains a complex mixture of many types of hydrocarbons, 

which range in size from 1 to 50 carbon atoms per molecule 

and in structure from simple, linear alkanes to branched or 

cyclic molecules (Georgia Coastal Research Council, 2010). 

These include polycyclic aromatic hydrocarbons (PAH), 

which are important because of their potential adverse effects 

on humans and aquatic life (U.S. Environmental Protection 

Agency, 2010, 2011a, and 2011b). Crude oil typically 

contains 1 to 2 percent PAHs, with the majority being 

alkylated PAHs (Operational Science Advisory Team, 2010). 

The M-1 well oil is a light, sweet oil with about 84 percent 

carbon, 4 percent hydrogen, and often less than 1 percent 

sulfur by weight (Georgia Coastal Research Council, 2010) 

and has an American Petroleum Institute (API) gravity of 

38.8 degrees (Rosenbauer and others, 2010). “Light” indicates 

that the material has a low density due to the relatively 

high abundance of smaller, saturated alkane hydrocarbons. 

“Sweet” indicates there is little sulfur contamination (Georgia 

Coastal Research Council, 2010). The U.S. Environmental 

Protection Agency (2011a) identified nickel and vanadium as 

relevant to the Deepwater Horizon oil spill, and the general 

category of Louisiana sweet crude oil was reported to be 

low in trace elements, having 0.1 to 0.8 percent sulfur by 

weight, 0 to 4 milligrams per kilogram (mg/kg) vanadium, 

and 0 to 6 mg/kg nickel (Nadkarni, 1991). In two surveys 

of the general category of light crude oils, or those having 

an API gravity of 33 degrees or more, reported by the 

American Petroleum Institute (2011), maximum trace-element 

concentrations were less than 1 mg/kg for arsenic, barium, 

cadmium, chromium, cobalt, copper, mercury, molybdenum, 

lead, antimony, selenium, and thallium. Concentrations 

were higher for iron, nickel, tin, vanadium, and zinc, which 

had mean values in the 2 to 4 mg/kg range and maximum 

concentrations of 16 mg/kg for iron, 7 mg/kg for nickel, 

10 mg/kg for tin, 20 mg/kg for vanadium, and 8 mg/kg for 

zinc. Concentrations of most trace elements are similar 

in different crude types, but nickel and vanadium tend to 

increase as crude oils become heavier (American Petroleum 

Institute, 2011).

In general, after oil is released into the environment, it is 

subject to various weathering processes, including dissolution, 

evaporation, emulsification, photo-oxidation, sedimentation, 

and biodegradation. The lower molecular-weight components 

tend to be lost through dissolution and evaporation, and 

photo-oxidation forms more water-soluble products, such as 
Methods 

7

Table 2. Chemical analysis of whole water samples from the Deepwater Horizon oil spill, Gulf of Mexico, 2010: laboratory, analytical methods, and sample treatment.

—Continued

[Abbreviations: BTEX, benzene, toluene, ethylbenzene, xylenes and related compounds; CVAA, cold vapor atomic absorption; FA, filter-acidify; g, gram; GC, gas chromatography; H2SO4, sulfuric acid; HCl, 

hydrochloric acid; HNO3, nitric acid; ICP, inductively coupled plasma; L, liter; LAB, laboratory; mL, milliliter; MS, mass spectrometry; Na, sodium; NH4, ammonium; NWQL, USGS National Water Quality 

Laboratory; OCRL, Organic Carbon Research Laboratory; OES, optical emission spectrometry; oz, ounce; PAH, polycyclic aromatic hydrocarbon; poly, polypropylene plastic container; RA, raw acidified; SIM, selective ion monitoring; SVOC, semivolatile organic compound; TAL-CO, TestAmerica Laboratory, Arvada, Colorado; TAL-FL, TestAmerica Laboratory, Pensacola, Florida; TAL-VT, TestAmerica Laboratory, Burlington, Vermont; TKN, total Kjeldahl nitrogen; TP, total phosphorus; TPH-DRO, total petroleum hydrocarbons–diesel range organics; TPH-GRO, total petroleum hydrocarbons–gasoline range organics; USEPA, U.S. Environmental Protection Agency; USGS, U.S. Geological Survey; VOA, volatile organic analyses; VOC, volatile organic compounds; 1x, one of (or 2x means two of, etc.) the type of container that follows; oC, degrees Celsius; <, less than; μm, micrometer]

Sample collected Analytes Lab Method (code or schedule) Container, preservation, and handling Citations

Pre-landfall PAH and other SVOC USGS NWQL GC/MS O-1316-87, 

O-3117-83, O-3118-83

1x 1-L baked, amber glass. Chill to 4°C 

without freezing

Fishman (1993); Wershaw and others 

(1987)

Pre- and postlandfall PAH and other SVOC TAL-FL Continuous liquid/liquid extraction; GC/MS 

(8270D)

2x 1-L baked, amber glass. Leave 

headspace. Chill to 4°C without freezing. Ship overnight

USEPA (1986), Method SW-846-8270d

Pre- and postlandfall Oil and grease TAL-FL n-Hexane extraction, gravimetry 

(1664A-HEM) 

1x 1-L wide-mouth glass. Leave 

headspace. Preserve to pH 2 with HCl. Chill to 4°C without freezing. Ship overnight

USEPA (1999) Method 1664, revision A

Pre-landfall VOC with BTEX USGS NWQL Purge and trap GC/MS 

O-5506-06 (2021)

3x 40-mL VOA septum vials. No 

bubbles. Chill to 4°C without freezing

Connor and others (1998); Wershaw and 

others (1987)

Post-landfall VOC with BTEX TAL-CO Purge and trap, GC/MS 

(8260B)

2x 40-mL VOA septum vials. No 

bubbles. Chill to 4°C without freezing

USEPA (1986), Method SW-846-8260b

Pre- and postlandfall VOC with BTEX TAL-FL Purge and trap, GC/MS (8260B) 2x 40-mL VOA septum vials. No bubbles. Chill to 4°C without freezing USEPA (1986), Method SW-846-8260b

Pre-landfall TPH-GRO with BTEX TAL-CO Purge and trap GC 

(8015B) 

3x 40-mL VOA septum vials. No 

bubbles. Chill to 4°C

USEPA (1986), Method SW-846-8015b

Pre- and postlandfall TPH-GRO TAL-FL Purge and trap GC (8015B) 2x 40-mL VOA septum vials. No bubbles. Chill to 4°C USEPA (1986), Method SW-846-8015b

Post-landfall TPH-DRO TAL-FL Flame ionization GC 

(8015C)

1x 1-L fired, amber glass. Leave 

headspace. Chill to 4°C without freezing

USEPA (1986), Method SW-846-8015c

Table 2. Chemical analysis of whole water samples from the Deepwater Horizon oil spill, Gulf of Mexico, 2010: laboratory, analytical methods, and sample treatment.
8 Contaminants in Water and Sediment Sampled in Response to the Deepwater Horizon Oil Spill Table 2. Chemical analysis of whole water samples from the Deepwater Horizon oil spill, Gulf of Mexico, 2010: laboratory, analytical methods, and sample treatment. —Continued

[Abbreviations: BTEX, benzene, toluene, ethylbenzene, xylenes and related compounds; CVAA, cold vapor atomic absorption; FA, filter-acidify; g, gram; GC, gas chromatography; H2SO4, sulfuric acid; HCl, 

hydrochloric acid; HNO3, nitric acid; ICP, inductively coupled plasma; L, liter; LAB, laboratory; mL, milliliter; MS, mass spectrometry; Na, sodium; NH4, ammonium; NWQL, USGS National Water Quality 

Laboratory; OCRL, Organic Carbon Research Laboratory; OES, optical emission spectrometry; oz, ounce; PAH, polycyclic aromatic hydrocarbon; poly, polypropylene plastic container; RA, raw acidified; SIM, selective ion monitoring; SVOC, semivolatile organic compound; TAL-CO, TestAmerica Laboratory, Arvada, Colorado; TAL-FL, TestAmerica Laboratory, Pensacola, Florida; TAL-VT, TestAmerica Laboratory, Burlington, Vermont; TKN, total Kjeldahl nitrogen; TP, total phosphorus; TPH-DRO, total petroleum hydrocarbons–diesel range organics; TPH-GRO, total petroleum hydrocarbons–gasoline range organics; USEPA, U.S. Environmental Protection Agency; USGS, U.S. Geological Survey; VOA, volatile organic analyses; VOC, volatile organic compounds; 1x, one of (or 2x means two of, etc.) the type of container that follows; oC, degrees Celsius; <, less than; μm, micrometer]

Sample collected Analytes Lab Method (code or schedule) Container, preservation, and handling Citations

Pre-landfall Trace elements, major ions USGS NWQL ICP-OES & ICP-MS 

(I-4471-97, I-4020-05, & I-4472-97) Method 2130

1x 125-mL poly, acid-rinsed (FA) Garbarino and Stuzeski (1998); Garbarino 

(1999); Garbarino and others (2006)

Post-landfall Trace elements, major ions TAL-FL ICP (6010B) Use pre-cleaned, blanked RA bottle to 

collect dip sample and fill acidified 1x 250-mL poly bottle. Leave headspace. Preserve to pH<2 with HNO3. Chill to 

4°C without freezing. Ship overnight

USEPA (1986), Method SW-846-6010b

Post-landfall Mercury TAL-FL CVAA (EPA 7470A) Use pre-cleaned 250-mL glass bottle, 

acidify collected sample with 2 mL of 6 normal hydrochloric acid.

USEPA (1986), Method SW-846-7470a

Pre-landfall Nutrients USGS NWQL Method IDs: I-4650-03, 

I-4522-85, I-4515-91, I-4610-01.

1x 125-mL poly. Add H2SO4. Chill 

to 4°C

Fishman and Friedman (1989); Patton 

and Kryskalla (2003); Patton and Truitt (1992, 2000) 

Post-landfall Nutrients TAL-FL Colorimetry (350.1, 

365.1, 365.4)

Use pre-cleaned, blanked RA bottle to 

collect dip sample and fill acidified 1x 250-mL brown poly bottle. Leave headspace. Preserve to pH<2 with H2SO4. Chill to 4°C without freezing. 

Ship overnight

USEPA (2012)

Pre- and postlandfall Dissolved organic carbon USGS OCRL Absorbance and fluorescence 

spectroscopy

1x 125-mL fired glass. Filter at laboratory. 

Chill to 4°C without freezing

Wilde and Skrobialowski (2011), 

appendix C-1
Methods 9

phenols, carboxylic acids, and ketones (Operational Science 

Advisory Team, 2011). Intermediate molecular-weight 

components can float and disperse in water, form emulsions, 

or sorb to sediment; the viscous, heavy components can form 

solid aggregates, or tarballs, that float or sink in water or sorb 

to sediment (American Petroleum Institute, 2003). Meanwhile, 

oil molecules are subject to microbial degradation at rates 

depending on the complexity of the oil molecules; degree 

of dispersion; environmental factors, such as temperature, 

oxygen, and nutrient concentrations; and the species and 

abundance of microbial organisms (Operational Science 

Advisory Team, 2011). The result is “weathered” crude oil that 

has a different composition from the oil originally released. A 

sample of weathered M-1 oil collected on April 27, 2010, was 

determined to contain aliphatic and cyclic hydrocarbons of, 

or greater than, C14—that is, with 14 or more carbon atoms. 

Benzene, toluene, ethylbenzene, xylene and related volatile 

(BTEX) compounds were not detected (State of Florida Oil 

Spill Academic Task Force, 2010). One goal of the nearshore 

sampling and chemical analysis was to characterize the 

weathering and shoreline degradation of the oil (Unified Area 

Command, 2010).

In the present study, contaminant classes determined 

in water and whole sediment included various organic 

compounds, trace and major elements, nutrients, and organic 

carbon. Trace and major elements, nutrients, and carbon also 

were analyzed in the fine sediment fraction, which is also 

called the silt-clay fraction, defined as less than 63-micrometer 

(μm) in size. As noted previously, there were changes in target 

analytes and analytical methods between the pre-landfall 

and post-landfall sampling periods. In September 2010, the 

Operational Science Advisory Team (2010, appendix F) 

recommended that future sample analyses in water and 

sediment include 43 PAH analytes, other organic compounds 

required for comparison to USEPA benchmarks for PAH 

mixtures, and metals. In the case of PAHs, this represented an 

expanded analyte list, and a change in the analytical method 

was made. For PAHs in sediment, pre-landfall samples were 

subsequently reanalyzed by using the updated analytical 

method. The analytical methods and laboratories that carried 

out the analyses are listed by analyte type in table 2 for 

water samples, and in table 3 for sediment samples, and are 

described briefly in the following sections. More detail is 

provided in the publications cited in tables 2 and 3. Analytical 

reporting levels are summarized in appendix 1. 

Water

Organic contaminants analyzed in water included volatile 

organic compounds (VOC), PAHs and other semivolatile 

organic compounds (SVOC), dissolved organic carbon 

(DOC), gasoline-range organics having 6 to 10 carbon 

atoms, diesel-range organics having 10 to 28 carbon atoms, 

and oil and grease (table 2). Most organic contaminants 

were determined by using gas chromatography with mass 

spectrometry (GC/MS). Most analyses were carried out at 

either the USGS National Water Quality Laboratory (NWQL) 

in Denver, Colorado, or the TestAmerica Laboratory in 

Pensacola, Florida (table 2), except for DOC, which was 

determined at the USGS Organic Carbon Research Laboratory 

(OCRL) in Boulder, Colorado. 

Trace and major elements and nutrients were determined 

in water by various methods, including cold vapor atomic 

absorption spectrometry for mercury, and inductively 

coupled plasma-optical emission spectrometry (ICP-OES) or 

inductively coupled plasma-mass spectrometry (ICP-MS) for 

other trace elements (table 2). Analyses of water samples were 

carried out at either the USGS NWQL or the TestAmerica 

Laboratory in Florida (table 2). If water samples had high 

specific conductance (for example, greater than 2,000 

microsiemens per centimeter) or high dissolved total solids, 

they were diluted prior to analysis by ICP-OES or ICP-MS 

methods for operational purposes and to approximate the 

matrices of the standards used to calibrate the instruments. 

High-salinity samples can cause an accumulation of solids 

in the sample-introduction system on ICP-OES and ICP-MS 

instruments, thereby compromising sensitivity (and therefore 

detection capability), accuracy, and precision (Tedmund M. 

Struzeski, Chemist, U.S. Geological Survey, Denver, Colo., 

written comm., Nov. 8, 2011). 

References for the analytical methods that were used are 

cited in table 2, and individual analytes and their reporting 

levels in water are listed in appendix tables 1-1 and 1-3. 

Sediment

Contaminants determined in whole, unsieved sediments 

included PAHs, alkylated PAH groups, other SVOCs, oil 

and grease, trace and major elements, nutrients, and carbon 

(table 3). Oil and grease in sediment was analyzed by the 

TestAmerica Laboratory in Arvada, Colorado, for pre-landfall 

samples and the TestAmerica Laboratory in Florida for 

post-landfall samples (table 3). PAHs in sediment were 

analyzed by GC/MS at the USGS NWQL for pre-landfall 

samples and the TestAmerica Laboratory in Florida for 

post-landfall samples. In addition, both pre-landfall and 

post-landfall samples were analyzed for PAHs and alkylated 

PAH groups at the TestAmerica Laboratory in Burlington, 

Vermont, by using GC/MS in the selective ion monitoring 

mode (SIM). Because the GC/MS SIM mode resulted in 

lower method detection limits (MDL), analytical results 

from the GC/MS SIM method were given precedence over 

results obtained by using GC/MS when both were available. 

Pre-landfall sediment samples were frozen for approximately 

8 months prior to reanalysis in February 2011 by GC/MS SIM. 
10 Contaminants in Water and Sediment Sampled in Response to the Deepwater Horizon Oil Spill Table 3. Chemical analysis of sediment samples from the Deepwater Horizon oil spill, Gulf of Mexico, 2010: laboratory, analytical methods, and sample treatment.

[Abbreviations: AAS, atomic absorption spectrometry; Ag, silver; Cd, cadmium; CVAA, cold vapor atomic absorption; g, gram; GC, gas chromatography; HEM, hexane extractable material; Hg, mercury; ICP, inductively coupled plasma; L, liter; LAB, laboratory; MS, mass spectrometry; NWQL, USGS National Water Quality Laboratory; OES, optical emission spectrometry; oz., ounce; PAH, polycyclic aromatic hydrocarbon; Pb, lead; SCL, Sediment Chemistry Laboratory, Atlanta, Georgia; SIM, selective ion monitoring; SVOC, semivolatile organic compound; TAL-CO, TestAmerica Laboratory, Denver, CO; TAL-FL, TestAmerica Laboratory, Pensacola, Florida; TAL-VT, TestAmerica Laboratory, Burlington, Vermont; TC, total carbon; TIC, total inorganic carbon; TN, total nitrogen; TOC, total organic carbon; TP, total phosphorus; TS, total sulfur; USEPA, U.S. Environmental Protection Agency; USGS, U.S. Geological Survey; 1x, one of (or 2x means two of, etc.) the type of container that follows; oC, degrees Celsius; <, less than; μm, micrometer]

Sample collected Analysis Lab Method or schedule Container Citations

Pre-landfall PAH and other SVOC NWQL GC/MS O-5506-06; schedules 

5506, 5507

100 g. in 1x 1-L wide-mouth glass. 

Chill to 4°C

Zaugg and others (2006)

PAH TAL-VT GC/MS SIM/isotope dilution 

(8270C SIM)

Reanalysis of frozen samples (above) 

sent to NWQL

USEPA (1986), 

Method SW-846-8270c

Post-landfall PAH and other SVOC TAL-FL GC/MS (8270D) 1x 8-oz. wide-mouth glass. (Sample 

combined with oil & grease.) Chill to 4°C

USEPA (1986), 

Method SW-846-8270d

PAH TAL-VT GC/MS SIM/isotope dilution 

(8270C SIM)

1x 4 oz. wide mouth glass. Chill to 4°C USEPA (1986), 

Method SW-846-8270c

Pre-landfall Oil & grease TAL-CO 1664A-HEM 1x 8-oz. wide-mouth glass. (Sample 

combined with SVOC.) Chill to 4°C

USEPA (1999)

Post-landfall Oil & grease TAL-FL 1664A-HEM 1x 8-oz. wide-mouth glass. (Sample 

combined with SVOC.) Chill to 4°C

USEPA (1999)

Pre- and post-landfall Trace and major elements, TN, 

TP, TS, TOC, and TIC

USGS SCL Strong acid digestion; flame AAS 

(Ag, Cd, Pb), CVAA (Hg), or ICP-OES (other trace elements); combustion (TC, TN, TOC) 

2x 18-oz. WhirlPak, whole sediments; 

1x 18-oz. WhirlPak, <63 μm sediments. Keep away from light. Chill to 4°C without freezing

Horowitz and Stephens 

(2008); Wilde and Skrobialowski (2011), Appendix C-5
Methods 11

For most trace and major elements, whole sediment was 

subjected to strong acid digestion prior to chemical analyses at 

the USGS Sediment Chemistry Laboratory (SCL) in Atlanta, 

Georgia (table 3). This analysis generated total concentrations 

of trace and major elements, that is, 95 percent or more of 

the element present in sediment (Horowitz and Stephens, 

2008). Silver, cadmium, and lead were determined by flame 

atomic absorption spectrometry, and other constituents were 

determined by ICP-OES. Mercury was digested separately 

and determined by cold vapor atomic absorption spectrometry. 

Total nitrogen, total carbon, and total organic carbon were 

determined by combustion. 

Additional sediment subsamples were wet-sieved through 

a 63-μm polyester mesh to obtain the silt-clay fraction, 

which was subjected to the same strong acid-digestion 

procedure and analyzed for the same trace and major 

elements as whole sediment, for comparison to national 

baseline concentrations in fine sediment. Sieving sediment 

at 63 μm limits the grain-size effect, which results from 

finer material that typically contains higher trace-element 

concentrations than coarser material, and facilitates spatial 

and temporal comparisons (Horowitz and Stephens, 2008). 

The less than 63-μm fraction tended to have markedly lower 

sample mass than whole sediment. For about 20 samples, 

the less than 63-μm sample mass was insufficient to run a 

chemical analysis. 

References for the analytical methods used are cited in 

table 3, and individual analytes and their reporting levels in 

sediment are listed in appendix tables 1-2, 1-4, and 1-5.

Quality-Control Samples

Three types of field QC samples were collected: blanks, 

replicates, and matrix spikes. The number of blanks, replicate 

sets, and matrix samples for laboratory spiking submitted to 

the various laboratories are shown in table 4.

Blanks

Blanks consist of samples prepared with water that is 

certified to be free of the analytes that will be measured by 

the laboratory. Blanks are used to estimate positive bias that 

can be caused by incidental contamination, which is the 

unintentional introduction of an analyte into the sample. For 

evaluation of potential contamination in water samples, three 

types of blanks were collected: field blanks, trip blanks, and 

equipment blanks. For evaluation of potential contamination 

in sediment samples, the only blanks collected were 

equipment blanks.

Table 4. Number of blanks, matrix samples for laboratory spiking, and replicate sets from the 2010 Deepwater Horizon oil spill, 

submitted to U.S. Geological Survey and TestAmerica laboratories.

[Abbreviations: NWQL, National Water Quality Laboratory, Denver, Colorado; OCRL, Organic Carbon Research Laboratory, Boulder, Colorado; SCL, 

Sediment Chemistry Laboratory, Atlanta, Georgia; TAL-CO, TestAmerica Laboratory, Denver, Colorado; TAL-FL, TestAmerica Laboratory, Pensacola, Florida; 

TAL-VT, TestAmerica Laboratory, Burlington, Vermont; USGS, U.S. Geological Survey; –, no applicable samples of this type]

Laboratory

Blanks Replicates Matrix spikes

Pre-landfall Post-landfall Pre-landfall Post-landfall Pre-landfall Post-landfall

Field Equipment Field Trip Water Sediment Water Sediment Water Sediment Water Sediment

Water Sediment

USGS NWQL 7 – – – – 27 22 – – 5 4 – –

USGS SCL – – – – – – 9 – 9 – – – –

USGS OCRL 5 6 4 – – 9 – 3 – – – – –

TAL-CO 5 – – – – 9 9 – – – – – –

TAL-FL – 5 3 4 31 – – 7 7 – – 5 3

TAL-VT – – – – – – 24 – 7 – – – –
12 Contaminants in Water and Sediment Sampled in Response to the Deepwater Horizon Oil Spill 

 Field blanks were prepared by pouring blank water 

directly into sample bottles under ambient conditions at 

field sites. These are “field” blanks because they were 

prepared in the field by the same procedure used to collect 

environmental samples. In general, they did not contact any 

sampling equipment other than the sample bottles. In Wilde 

and Skrobialowski (2011), they are called “ambient” blanks 

because they were exposed to the atmosphere. Blanks and 

environmental samples for DOC and total nitrogen collected 

during the pre-landfall period were pumped from a collection 

bottle through a filter into a sample bottle. Field blanks enable 

the assessment of potential contamination of environmental 

water samples during sample preparation. Sources of 

contamination are not necessarily the same for pre-landfall and 

post-landfall samples, however, because (1) conditions could 

vary from one sampling period to the next and (2) pre-landfall 

samples and post-landfall samples were not analyzed at the 

same time and, in some cases, were analyzed by different 

laboratories (tables 2 and 4). Thus, pre-landfall field blanks 

should be compared only to pre-landfall water samples, and 

post-landfall field blanks compared only to post-landfall 

water samples. 

Trip blanks were prepared at the TestAmerica 

Laboratory in Florida during the post-landfall period. These 

blanks were shipped to USGS offices, transported to field 

sites during sampling trips, and returned to the laboratory 

with environmental samples. Trip blanks generally are 

prepared only for VOCs and are used to evaluate whether 

environmental samples were contaminated during sample 

transport and analysis. Absence of detectable contaminants in 

a trip blank indicates there is no evidence that environmental 

samples were contaminated during transport and processing, 

but does not necessarily rule out contamination from other 

sources, such as ambient conditions at the site. 

Equipment blanks were prepared in USGS offices by 

pumping blank water through water-sampling equipment, or 

by pouring blank water over sediment-sampling equipment, 

and collecting the rinsate in sample bottles. Blanks prepared 

by using water-sampling equipment are useful in this study 

only for comparison to environmental samples that were 

pumped through a filter—that is, pre-landfall samples 

analyzed for organic carbon and total nitrogen. Even for these 

analytes, the field blanks provide a more useful comparison 

than equipment blanks because they more completely 

represent potential sources of contamination. For sediment, 

equipment rinsate blanks were intended to indicate the 

potential for incidental contamination of environmental 

sediment samples from collection equipment and containers. 

Blank-water rinsate can be assumed to pick up contaminants 

that are removed easily from the sampling equipment, but it 

might not represent certain processes, such as abrasion, that 

can occur during sediment-sample collection. Also, laboratory 

analysis of the blanks is done by using methods for water, 

rather than methods for sediment, and the potential sources 

of contamination during sample processing and laboratory 

analysis are not exactly the same for water as for sediment.

Data from blank samples can be used to estimate 

the potential for contamination in environmental samples 

in excess of concentrations that actually occur in the 

sampled matrix, which in this study is water or sediment. 

If a representative blank can be associated with each 

environmental sample, analytical results for the blanks can 

be used to qualify results for the environmental samples 

(U.S. Environmental Protection Agency, 1989, pages 16–17 

in chapter 5). If the blank contains detectable levels of an 

analyte, concentrations of that analyte in the associated 

environmental samples should be censored unless they 

exceed five times the amount in the blank or, if the analyte 

is considered a common laboratory contaminant (such as 

acetone), ten times the amount in the blank.

Field Replicates

Field replicates are two or more environmental samples 

that are collected and prepared such that they are considered 

to be essentially identical in composition. Replicates are used 

to estimate variability of the analytical result. In this study, 

replicate water samples were collected sequentially by filling 

one set of sample bottles, followed immediately by filling 

a second, third, and, in some cases, a fourth set of bottles. 

Replicate sediment samples were collected by compositing a 

large amount of material in a single container. This material 

was homogenized, and replicate subsamples were scooped into 

separate sample containers.

Statistical evaluation of replicate variability is based 

on the standard deviation of measured values in the primary 

environmental sample and the replicate sample, or samples. 

For many analytes, variability is correlated with the mean 

concentration of that analyte in the replicates (Martin, 

2002; Mueller and Titus, 2005). Within a range of low 

concentrations, standard deviation of replicates generally 

is uniform, but at higher concentrations, standard deviation 

tends to increase in proportion to concentration. Within this 

higher range, the relative standard deviation (RSD), defined 

as the standard deviation of replicate results divided by 

the mean concentration, is generally uniform. Therefore, 

over the low-concentration range, variability is estimated 

as the average standard deviation of replicates; over the 

high-concentration range, variability is estimated as the 

average RSD. 
Methods 13

Typically, replicate variability is similar to the analytic 

error of laboratory methods, having RSDs ranging from a few 

percent to around 10 percent. If variability is substantially 

higher than this range, it could interfere with certain types 

of data interpretation. For example, high variability adds 

uncertainty when comparing data to a standard or benchmark. 

Also, it can reduce the likelihood of finding statistically 

significant differences in comparisons among groups of data 

over time or space. Variability is less likely to affect the 

central tendency (for example, the mean and median) of data 

distributions, but can increase the spread and range.

Matrix Spikes

Matrix spikes are samples fortified, or “spiked,” with 

known concentrations of analytes that will be measured by the 

laboratory. Spikes are used to estimate positive or negative 

bias in the analytical result caused by matrix effects—that is, 

chemical, physical, or biological characteristics of the sample 

material (water or sediment itself) that can interfere with 

chemical analysis of the sample. Matrix spike samples were 

collected in the same manner as field replicates; subsequently, 

these samples were spiked in the laboratory to introduce a 

known amount of the analytes of interest.

Method performance is determined by spike recovery, 

which is the measured amount of analyte expressed as 

a percentage of the known spiked amount. Recovery is 

calculated from analyte concentrations in the spiked sample 

compared to a replicate environmental sample that was not 

spiked. Recovery can be poorly estimated if the analyte 

concentration in the background environmental sample is 

similar to, or greater than, the expected concentration of the 

spiked addition.

Generally, recovery is within a few percent of 100 for 

analytes that are not affected by method or sample-matrix 

interferences, though the acceptable range can extend to 

within 10 to 20 percent for some analytes. Poor recovery is 

more typically low, rather than high. For constituents with 

chronically poor recovery, some aspects of data interpretation 

require qualification; for example, the detection frequency and 

the likelihood of exceeding a standard or benchmark can be 

underestimated.

Spikes are used most often for organic compounds 

because the analytical methods involve extraction and 

analysis steps that can be affected by other chemicals in the 

sample. For example, naturally occurring organic matter can 

be co-extracted with anthropogenic organic compounds in a 

sample and interfere with GC analysis. 

Laboratory Quality-Control Procedures

Laboratory QC procedures include analysis of reagent 

blanks (also called method blanks), spikes, standard reference 

materials, and surrogate compounds. Each laboratory has 

its own QC procedures and analyses in order to assess the 

quality of the data and meet performance standards. It is 

beyond the scope of this report to describe the laboratory QC 

sampling, except in one regard—where contamination was 

detected in reagent blanks, this information was considered 

in data analysis for this report. Laboratory reagent blanks are 

processed and analyzed along with each set of environmental 

samples and are used to monitor for incidental contamination 

introduced during sample processing and analysis at 

the laboratory.

Water- and Sediment-Quality Benchmarks 

Concentrations of trace and major elements and organic 

contaminants were compared to various benchmarks to assess 

the potential for adverse effects on human health or aquatic 

life. Benchmark comparisons were made for all available 

samples, including field replicate samples and samples from 

sites sampled in only one study period, to maximize the 

information gained from the dataset regarding benchmark 

exceedance at the sampled sites.

Contaminant concentrations in water were compared to 

benchmarks for protection of human health and aquatic life, 

whereas concentrations in whole sediment were compared 

to sediment-quality benchmarks for protection of benthic 

organisms. The benchmarks used were those recommended by 

the U.S. Environmental Protection Agency (2010, 2011a, and 

2011b) on its web site, “EPA Response to BP Spill in the Gulf 

of Mexico, Coastal Water Sampling” (U.S. Environmental 

Protection Agency, 2011c), supplemented by screening-level 

benchmarks from the NOAA Office of Response and 

Restoration (Buchman, 2008). In addition, trace- and 

major-element and nutrient concentrations in the less than 

63-μm sediment fraction were compared to national baseline 

concentrations in bed sediments of U.S. rivers from Horowitz 

and Stephens (2008). 

Benchmark values are listed for organic contaminants in 

table 5 and for trace and major elements in table 6. Table 6D

lists baseline concentrations for trace and major elements and 

nutrients in the less than 63-μm sediment fraction. 
14 Contaminants in Water and Sediment Sampled in Response to the Deepwater Horizon Oil Spill 

Human-Health Benchmarks for Water

Human-health benchmarks are based on potential cancer 

and non-cancer risks associated with recreational exposure 

to oil-contaminated water. They were developed by U.S. 

Environmental Protection Agency (2010) in coordination 

with the U.S. Department of Health and Human Services. 

These benchmarks consider both skin contact and incidental 

ingestion of water by a child swimmer, assuming 90 hours of 

exposure. Human-health benchmark values are available for 

five VOCs, six PAHs, and two trace elements—nickel and 

vanadium—in water (tables 5C and 6B). 

Aquatic-Life Benchmarks for Water

For water samples, potential toxicity to aquatic life 

was assessed by comparison to two types of benchmarks: 

(1) a toxic-unit (TU) approach for mixtures of PAHs and 

BTEX compounds (table 5A) and (2) marine benchmarks for 

individual contaminants (tables 5B and 6A). 

Toxic-Unit Benchmarks for PAH-BTEX Mixtures in Water

Because PAHs and BTEX compounds share a common 

mechanism of action, toxicity is expected to be additive. 

A toxic-unit approach is used, therefore, in which the 

concentration of each component (i) of the mixture is divided 

by a potency factor to determine its toxic-unit concentration 

(TUi). The TUi values for all components in the mixture are 

summed and the sum (∑TUi) is compared to a hazard index 

of 1 (U.S. Environmental Protection Agency, 2011a). Separate 

TU computations are made for acute and chronic toxicity 

by using acute and chronic potency factors, respectively 

(table 5A). Because alkylated PAHs (for example, C1- and 

C2-alkylated naphthalenes) tend to have comparable or 

greater toxicity to aquatic life than parent PAHs (for example, 

naphthalene itself), it is important to include alkylated PAHs in 

TU calculations. Because alkylated PAHs were not measured 

in water in this study, concentrations of alkylated PAHs were 

estimated from parent PAHs by using appropriate alkylation 

multipliers, as recommended by USEPA (Mount, 2010). 

USEPA developed these multipliers by using the analysis of a 

tarball that was collected at Dauphin Island during the current 

oil spill and checked them against oil composition data from 

other sources, including the Exxon Valdez oil. Because the 

present study did not analyze 2 of the 18 parent PAHs that 

should be included in the ∑TUi

 value for water—benzo(e)

pyrene and perylene—these two compounds were omitted 

from ∑TUi calculations, which therefore could be biased low. 

An acute or chronic ∑TUi value greater than 1 indicates 

that the sample has the potential to cause an acute or chronic 

effect, respectively, on aquatic organisms such as fish, crabs, 

and clams. The PAHs and BTEX contaminants included in 

the ∑TUi calculations for water are provided in table 5A, 

along with their acute and chronic potency factors and 

alkylation multipliers. 

Marine Benchmarks

Marine benchmarks for acute or chronic exposure to 

individual contaminants are available from various sources 

for many organic contaminants (table 5B) and trace elements 

(table 6A). These values were obtained from Buchman 

(2008), who compiled acute and chronic marine benchmarks 

from multiple sources. Most values were from the USEPA, 

such as ambient water-quality criteria and Tier II SpeciesAcute Values, which were supplemented by benchmarks 

from Canada, British Columbia, and New Zealand. As such, 

individual benchmarks were not necessarily derived the same 

way, and exceedance of one benchmark can mean something 

slightly different from exceedance of another, as shown in 

these examples: 

• The USEPA chronic water-quality criterion is the 

highest concentration of a pollutant that aquatic 

organisms can be exposed to for an extended period 

without deleterious effects. The acute water-quality 

criterion is the highest concentration that aquatic 

organisms can be exposed to for a short period (1-hour 

average) without deleterious effects. Both are intended 

to protect 95 percent of a diverse group of genera and 

should not be exceeded more than once every 3 years.

• Canadian aquatic-life guidelines are based on toxicity 

data for the most sensitive species of plants and 

animals found in Canadian waters; they are intended 

to protect all forms of aquatic life during all stages 

of the aquatic life cycles and should not be exceeded 

at any time (Canadian Council of Ministers of the 

Environment, 1999).

• The British Columbia guidelines set safe conditions 

or levels that have province-wide application and 

are designed to protect marine aquatic life (British 

Columbia Ministry of Environment, 2010). They are 

intended to protect all forms of aquatic life and all 

stages of their life cycle during indefinite exposure 

(Meays, 2010). If a single guideline is recommended, 

it represents a long-term no-effect level and should not 

be exceeded at any time. For some substances, both 

maximum (acute) and average (chronic) guidelines 

are recommended; acute guidelines apply in the initial 

dilution zone, and chronic guidelines apply everywhere 

else (Meays, 2010). In addition, British Columbia 

has working guidelines for additional contaminants 
Methods 15

that were obtained from various North American 

jurisdictions, but have not yet been fully assessed by 

the Ministry of Environment; they represent the best 

guidance the Ministry can provide about safe levels 

of these substances in the environment (Nagpal and 

others, 2006).

• Trigger values from New Zealand are derived by 

fitting an appropriate statistical distribution to the 

no-observed-effect-concentration data available for 

a given contaminant, and estimating a concentration 

that protects 95 percent of species in the environment 

(Australian and New Zealand Environment and 

Conservation Council, 2000).

Organic 

contaminant CASRN Acute divisor1

 (μg/L)

Chronic divisor1 

(μg/L) Multiplier2 Analyzed 

in this study

Benzene 71-43-2 27,000 5,300 1 Yes

Cyclohexane 110-82-7 1,900 374 1 Yes

Ethylbenzene 100-41-4 4,020 790 1 Yes

Isopropylbenzene (cumene) 98-82-8 2,140 420 1 Yes

Total xylene (o, m and/or p) 108-38-3 3,560 700 1 Yes

Methylcyclohexane 108-87-2 463 91.0 1 Yes

Toluene 108-88-3 8,140 1,600 1 Yes

Naphthalene 91-20-3 803 193 120 Yes

Acenaphthylene 208-96-8 1,280 307 1 Yes

Acenaphthene 83-32-9 232 55.8 1 Yes

Fluorene 86-73-7 164 39.3 14 Yes

Phenanthrene 85-01-8 79.7 19.1 6.8 Yes

Anthracene 120-12-7 86.1 20.7 1 Yes

Fluoranthene 206-44-0 29.6 7.11 1 Yes

Pyrene 129-00-0 42.0 10.1 2.1 Yes

Benz[a]anthracene 56-55-3 9.28 2.23 1 Yes

Chrysene 218-01-9 8.49 2.04 5 Yes

Perylene 198-55-0 3.75 0.901 1 No

Benzo[b]fluoranthene 205-99-2 2.82 0.677 1 Yes

Benzo[k]fluoranthene 207-08-9 2.67 0.642 1 Yes

Benzo[e]pyrene 192-97-2 3.75 0.901 1 No

Benzo[a]pyrene 50-32-8 3.98 0.957 1 Yes

Indeno[1,2,3-cd]pyrene 193-39-5 1.14 0.275 1 Yes

Dibenz[a,h]- anthracene 53-70-3 1.17 0.282 1 Yes

Benzo[g,h,i]perylene 191-24-2 1.83 0.439 1 Yes

1

The Toxic Unit (∑TUi) benchmark is computed by dividing the concentration of each individual compound by its potency divisor (acute or chronic), then 

adding the ratios for all compounds in the sample to calculate the combined toxicity. A ∑TUi benchmark value >1 indicates an exceedance.

2

Because alkylated PAHs were not analyzed in water, their concentrations were estimated by applying a multiplier to the parent PAH concentration.

Table 5A. Benchmark values for organic contaminants: toxic-unit benchmarks (∑TUi) for PAH and BTEX compounds in water.

[Abbreviations: BP, British Petroleum; BTEX, benzene, toluene, ethylbenzene, xylenes and related compounds; CASRN, Chemical Abstracts Service Registry 

Number; PAH, polycyclic aromatic hydrocarbons; TU, toxic unit; μg/L, microgram per liter; >, greater than]
16 Contaminants in Water and Sediment Sampled in Response to the Deepwater Horizon Oil Spill 

Table 5B. Benchmark values for organic contaminants: supplemental aquatic-life benchmarks for organic contaminants in water.

[Abbreviations: ANZ, Australian and New Zealand guideline trigger value (Australian and New Zealand Environment and Conservation Council, 2000); 

BC, British Columbia water-quality guideline for marine aquatic life (British Columbia Ministry of Environment, 2010; Nagpal and others, 2006); C, Value 

for chemical class; CA, Canadian water-quality guideline for the protection of marine aquatic life (Canadian Council of Ministers of the Environment, 

2011); Eco, Ecotox threshold (U.S. Environmental Protection Agency [USEPA], 1996); LOEL, USEPA LOEL value (unverified) from Buchman (2008), who 

compiled LOELs previously published by USEPA; MW, molecular weight; p, proposed value (unverified) from Buchman (2008); PAH, polycyclic aromatic 

hydrocarbons; S, value for summation of isomers; #, chronic value derived by division of acute value by 10; <, less than; –, no benchmark]

Contaminant Marine acute 

(μg/L)1,2

Marine chronic

(μg/L)1,2

1,1,1-Trichloroethane 31,200 LOEL 3,120 #

1,1,2,2-Tetrachloroethane 9,020 LOEL 902 #

1,1,2-Trichloroethane – 1,900 ANZ

1,1-Dichloroethene 224,000 S, LOEL –

1,2,4-Trichlorobenzene 160 C, LOEL 5.4 CA

1,2-Dichlorobenzene <1,970 S, LOEL 42 CA

1,2-Dichloroethane 113,000 LOEL 11,300 #

1,2-Dichloroethene (cis or 

trans)

224,000 S, LOEL –

1,2-Dichloropropane 10,300 S, LOEL 3,040 S, LOEL

1,3-Dichlorobenzene <1,970 S, LOEL –

1,3-Dichloropropene (cis or 

trans)

790 S, LOEL –

1,4-Dichlorobenzene <1,970 S, LOEL 129 C, LOEL

2,4,5-Trichlorophenol 240 p 11 p

2,4-Dinitrophenol 4,850 C, LOEL –

2,4-Dinitrotoluene 590 S, LOEL 370 S, LOEL

2-Chloronaphthalene 7.5 C, LOEL –

2-Methylnaphthalene 300 C, LOEL –

4-Chloroaniline 160 C, LOEL 129 C, LOEL

4-Nitrophenol 4,850 C, LOEL –

Acenaphthene 970 LOEL 40 Eco

Acenaphthylene 300 C, LOEL –

Anthracene 300 C, LOEL –

Benzene 5,100 LOEL 110 CA

Benzo(a)anthracene 300 C, LOEL –

Benzo(a)pyrene 300 C, LOEL –

Benzo(b)fluoranthene 300 C, LOEL –

Benzo(ghi)perylene 300 C, LOEL –

Benzo(k)fluoranthene 300 C, LOEL –

Benzyl n-butyl phthalate 2,944 C, LOEL 3.4 C, LOEL

Bis(2-chloroethoxy)methane 12,000 C, LOEL 6,400 C, LOEL

Bis(2-ethylhexyl) phthalate 400 p 360 p

Bromodichloromethane 12,000 C, LOEL 6,400 C, LOEL

Chrysene 300 C, LOEL –

cis-1,2-Dichloroethene 224,000 S, LOEL –

cis-1,3-Dichloropropene 790 S, LOEL –

Dibenzo(ah)anthracene 300 C, LOEL –

Dibromochloromethane 12,000 C, LOEL 6,400 C, LOEL

Contaminant Marine acute 

(μg/L)1,2

Marine chronic

(μg/L)1,2

Dibromomethane 

(methylene bromide)

12,000 C, LOEL 6,400 C, LOEL

Dichlorobenzenes 1,970 S, LOEL –

Dichloromethane 

(methylene chloride)

12,000 C, LOEL 6,400 C, LOEL

Diethyl phthalate 2,944 C, LOEL 3.4 C, LOEL

Dimethyl phthalate 2,944 C, LOEL 3.4 C, LOEL

Di-n-butyl phthalate 2,944 C, LOEL 3.4 C, LOEL

Di-n-octyl phthalate 2,944 C, LOEL 3.4 C, LOEL

Ethylbenzene 430 LOEL 25 CA

Fluoranthene 40 C, LOEL 11 Eco

Fluorene 300 C, LOEL –

Hexachlorobenzene 160 C, LOEL 129 C, LOEL

Hexachlorobutadiene 32 LOEL 3.2 #

Hexachlorocyclopentadiene 7 LOEL 0.7 #

Hexachloroethane 940 LOEL 94 #

Indeno[1,2,3-cd]pyrene 300 C, LOEL –

Isophorone 12,900 LOEL 1,290 #

Methyl tert-butyl ether 

(MTBE)

– 5,000 CA

Monochlorobenzene 160 C, LOEL 25 CA

Naphthalene 2,350 LOEL 1.4 CA

Nitrobenzene 6,680 LOEL 668 #

N-Nitrosodiphenylamine 3,300,000 C, LOEL –

PAHs, high MW 300 C, LOEL –

PAHs, low MW 300 C, LOEL –

PAHs, total 300 C, LOEL –

Pentachlorophenol 13 7.9

Phenanthrene 7.7 p 4.6 p

Sum dichloroethenes 224,000 S, LOEL –

Tetrachloroethene (PCE) 10,200 LOEL 450 LOEL

Tetrachloromethane 50,000 LOEL 5,000 #

Toluene 6,300 LOEL 215 CA

trans-1,2-Dichloroethene 224,000 S, LOEL –

trans-1,3-Dichloropropene 790 S, LOEL –

Trichlorobenzenes 160 C, LOEL <5.4 CA

Trichloroethene (TCE) 2,000 LOEL 200 #

Trichlorofluoromethane 12,000 C, LOEL 6,400 C, LOEL
Methods 17

Sediment-Quality Benchmarks

Potential effects of sediment contaminants on benthic 

organisms were assessed by comparing contaminant 

concentrations to benchmarks derived by using two different 

approaches: equilibrium partitioning and empirical biologicaleffects correlation. In the equilibrium-partitioning approach, 

an equilibrium-partition coefficient (Koc) is used to calculate 

the contaminant concentration in sediment that corresponds 

to the concentration in interstitial water, or pore water, above 

which toxic effects on aquatic organisms could occur (Di Toro 

and others, 1991). This approach assumes that contaminants 

are in equilibrium between water and sediment organic carbon, 

and postulates a theoretical causal relation between chemical 

bioavailability and chemical toxicity in different sediments. 

Equilibrium-partitioning (EqP) benchmarks are available for 

nonionic-organic contaminants, including PAH mixtures and 

some individual organic contaminants, and are described later 

in this section. 

In contrast, the biological-effects correlation approach 

consists of matching sediment-chemistry measurements with 

biological-effects measurements to relate the incidence of 

biological effects in field sediments to the concentration of 

an individual contaminant at a particular site. The matching 

measurements come primarily from field studies, and 

sometimes from spiked sediment bioassays. The dataset of 

matching measurements is used to identify a level of concern 

for an individual contaminant that is associated with a certain 

probability of observing adverse effects on benthic organisms 

in studies where that contaminant was measured. This 

approach is empirically based and does not indicate a direct 

cause-and-effect relation between chemical contamination 

and biological effects. It assumes that the contaminant 

measured is responsible for the effects observed, although 

field sediment samples typically contain complex mixtures 

of chemical contaminants (see, for example, MacDonald and 

others, 1996; Burgess and others, 2003; Hyland and others, 

2003). Empirical, or correlative, benchmarks for both organic 

contaminants and trace elements are available from a number 

of sources, which are described later in this section. 

Equilibrium-Partitioning Sediment Benchmarks for 

PAH Mixtures 

As in water, toxicity to PAHs and BTEX compounds 

in sediment is expected to be additive. The bioavailability 

of nonionic organic compounds in sediment, however, is 

assumed to be controlled by sorption to sediment organic 

carbon. Therefore, the toxic unit approach in sediment first 

requires that measured concentrations of the contaminants be 

normalized to the total organic carbon (TOC) content of the 

sediment. Then, the TOC-normalized concentration of each 

component compound (i) is divided by its potency factor 

to obtain its equilibrium-partitioning sediment benchmark 

toxic-unit concentration (ESBTUi), and the ESBTUi values are 

summed for all components in the sediment mixture to obtain 

the equilibrium-partitioning sediment benchmark toxic units 

(∑ESBTUi) for that sediment sample (U.S. Environmental 

Protection Agency, 2011b). Separate calculations are made 

for acute and chronic exposure by using acute and chronic 

potency factors. The PAHs included in ∑ESBTUi calculations 

consist of both parent PAHs and alkylated PAHs because the 

latter have comparable, or greater, toxicity than the former 

(table 5D). Just as in the TU procedure for water, the ESBTU 

procedure for sediment calls for using alkylation multipliers 

if data for alkylated PAH groups are not available. In this 

study, data were available for alkylated PAHs in all sediment 

samples, so alkylation multipliers were not used. BTEX 

compounds were not determined in sediment, however, so 

calculated ∑ESBTUi

 values could be slightly low; this bias is 

expected to be minimal in shoreline sediments because BTEX 

compounds are volatile, were not detected in weathered M-1 

oil (State of Florida Oil Spill Academic Task Force, 2010), and 

are not expected to persist in sediment (Mount, 2010). 

An acute or chronic ∑ESBTUi value greater than 1 

indicates that the sample has the potential to cause an acute or 

chronic effect, respectively, on sediment-dwelling organisms, 

such as crabs, clams, and worms. The contaminants included 

in the ESBTU calculations, and their potency factors and 

multipliers, are provided in table 5D. 

Table 5C. Benchmark values for organic contaminants: 

human-health benchmarks (recreational contact) for organic 

contaminants in water.

[Abbreviations: C, cancer endpoint; CASRN, Chemical Abstracts Service 

Registry Number; HH, human health; NC, noncancer effects endpoint; μg/L, 

microgram per liter]

Organic 

contaminant CASRN

HH benchmark 

(child swimmer)

(μg/L)

Cancer/

noncancer

Benzene 71-43-2 380 C

Isopropylbenzene 

(cumene)

98-82-8 20,000 NC

Ethylbenzene 100-41-4 610 C

Total xylene1 108-38-3 18,000 NC

Toluene 108-88-3 120,000 NC

2-Methylnaphthalene 91-57-6 170 NC

Naphthalene 91-20-3 1,800 NC

Acenaphthene 83-32-9 2,500 NC

Fluorene 86-73-7 12,000 NC

Anthracene 120-12-7 22,000 NC

Pyrene 129-00-0 4,100 NC

1

Analyzed in this study as total xylene in some samples, and as the summed 

concentrations of ortho, meta, and para isomers in other samples.
18 Contaminants in Water and Sediment Sampled in Response to the Deepwater Horizon Oil Spill 

Table 5D. Benchmark values for organic contaminants: equilibrium-partitioning sediment benchmark toxic units (∑ESBTUi) for PAH 

and BTEX compounds in sediment.

[Abbreviations: BP, British Petroleum; BTEX, benzene, toluene, ethylbenzene, xylenes and related compounds; CASRN, Chemical Abstracts Service Registry 

Number; ΣESBTUi , equilibrium-partitioning sediment benchmark toxic unit; PAH, polycyclic aromatic hydrocarbons; μg/kg-oc, microgram per kilogram of 

sediment organic carbon; >, greater than; –, not applicable]

Organic 

contaminant CASRN Acute divisor1(μg/kg-oc)

Chronic divisor1 

 (μg/kg-oc) Multiplier2 Analyzed 

in this study

Benzene 71-43-2 3,360,000 660,000 1 No

Cyclohexane 110-82-7 4,000,000 786,000 1 No

Ethylbenzene 100-41-4 4,930,000 970,000 1 No

Isopropylbenzene (cumene) 98-82-8 5,750,000 1,130,000 1 No

Total xylene 108-38-3 4,980,000 980,000 1 No

Methylcyclohexane 108-87-2 4,960,000 976,000 1 No

Toluene 108-88-3 4,120,000 810,000 1 No

Naphthalene 91-20-3 1,600,000 385,000 120 Yes

C1-Naphthalenes – 1,850,000 444,000 – Yes

C2-Naphthalenes – 2,120,000 510,000 – Yes

C3-Naphthalenes – 2,420,000 581,000 – Yes

C4-Naphthalenes – 2,730,000 657,000 – Yes

Acenaphthylene 208-96-8 1,880,000 452,000 1 Yes

Acenaphthene 83-32-9 2,040,000 491,000 1 Yes

Fluorene 86-73-7 2,240,000 538,000 14 Yes

C1-Fluorenes – 2,540,000 611,000 – Yes

C2-Fluorenes – 2,850,000 686,000 – Yes

C3-Fluorenes – 3,200,000 769,000 – Yes

Phenanthrene 85-01-8 2,480,000 596,000 6.8 Yes

Anthracene 120-12-7 2,470,000 594,000 1 Yes

C1-Phenanthrenes/anthracenes – 2,790,000 670,000 – Yes

C2-Phenanthrenes/anthracenes – 3,100,000 746,000 – Yes

C3-Phenanthrenes/anthracenes – 3,450,000 829,000 – Yes

C4-Phenanthrenes/anthracenes – 3,790,000 912,000 – Yes

Fluoranthene 206-44-0 2,940,000 707,000 1 Yes

Pyrene 129-00-0 2,900,000 697,000 2.1 Yes

C1-pyrene/fluoranthenes – 3,200,000 770,000 – Yes

Benz(a)anthracene 56-55-3 3,500,000 841,000 1 Yes

Chrysene 218-01-9 3,510,000 844,000 5 Yes

C1-Chrysenes/benzanthracenes – 3,870,000 929,000 – Yes

C2-Chrysenes/benzanthracenes – 4,200,000 1,010,000 – Yes

C3-Chrysenes/benzanthracenes – 4,620,000 1,110,000 – Yes

C4-Chrysenes/benzanthracenes – 5,030,000 1,210,000 – Yes

Perylene 198-55-0 4,020,000 967,000 1 Yes

Benzo(b)fluoranthene 205-99-2 4,070,000 979,000 1 Yes

Benzo(k)fluoranthene 207-08-9 4,080,000 981,000 1 Yes

Benzo(e)pyrene 192-97-2 4,020,000 967,000 1 Yes

Benzo(a)pyrene 50-32-8 4,020,000 965,000 1 Yes

Indeno(1,2,3-cd)pyrene 193-39-5 4,620,000 1,110,000 1 Yes

Dibenz(a,h) anthracene 53-70-3 4,660,000 1,120,000 1 Yes

Benzo(g,h,i)perylene 191-24-2 4,540,000 1,090,000 1 Yes

1

The ΣESBTUi benchmark is computed by dividing the sediment organic carbon-normalized concentration of each individual compound by its potency divisor 

(acute or chronic), then adding the ratios for all compounds to calculate the combined toxicity. An ΣESBTUi benchmark value >1 indicates an exceedance.

2

For samples with no data available for alkylated PAHs, concentrations were estimated by applying a multiplier to the parent PAH concentration.
Methods 19

Equilibrium-Partitioning Sediment Benchmarks for 

Individual Contaminants 

As with the ESBTU approach described previously for 

PAH-BTEX mixtures, these EqP benchmarks are based on 

equilibrium-partitioning theory, but they apply to individual 

contaminants rather than contaminant mixtures. The acute 

and chronic EqP benchmarks are in units of microgram per 

gram (μg/g) of sediment TOC, so that measured contaminant 

concentrations in dry weights must be normalized to sediment 

TOC prior to comparison with these benchmarks (table 5E). 

Acute and chronic EqP benchmarks are based on acute or 

chronic toxicity to aquatic life, respectively, and represent 

the concentration of chemicals in sediment that are predictive 

of biological effects, protective of the presence of benthic 

organisms, and applicable to the range of natural sediments 

from lakes, streams, estuaries, and near-coastal marine waters 

(U.S. Environmental Protection Agency, 2008). Exceedance of 

an individual EqP benchmark indicates that effects can occur 

if the contaminant in question is bioavailable as predicted by 

EqP theory; in general, the degree of effect that is expected 

increases with increasing exceedance of the benchmark (U.S. 

Environmental Protection Agency, 2008). Individual EqP 

benchmark values are listed in table 5E. 

Empirical Sediment Benchmarks

Several types of empirical benchmarks have been 

developed on the basis of correlations between measured 

chemical concentrations and observed toxicity in field 

sediments. As such, they define concentrations in sediments 

that are associated with certain types and levels of toxicity. 

These benchmarks typically come in pairs: lower screening 

values define concentrations below which adverse effects are 

not expected and upper screening values define concentrations 

above which adverse effects are likely or frequent. Four such 

pairs of sediment benchmarks are listed; benchmark types 

and values are shown in tables 5E and 6C. In this study, two 

supplementary benchmarks—Washington State’s apparent 

effect threshold (AET; tables 5E and 6C) and the USEPA’s 

EqP benchmark (table 5E)—are grouped with upper screening 

values because they indicate concentrations above which 

toxicity is likely. 

• Apparent Effect Threshold. These values are based 

on matching sediment chemistry and toxicity data 

from Puget Sound. The AET is the concentration of 

an individual contaminant above which a particular 

adverse biological effect is always expected (Barrick 

and others, 1988). Different types of AETs represent 

different indicators of toxicity, including amphipod 

mortality, benthic abundance, Microtox, and oyster 

larval development. For a given contaminant, the AET 

value shown in table 5E or 6C represents the lowest 

available AET value, as determined by Buchman 

(2008). Because of its definition, the AET was 

considered an upper screening value in this study.

• Effects-Range Low and Effects-Range Median.

These were derived from matching sediment 

chemistry and toxicity data. The effects range-low 

(ERL) corresponds to the lower 10th percentile of the 

matched data for a given contaminant and represents 

the contaminant concentration below which effects 

are rarely observed. The effects range-median (ERM) 

corresponds to the 50th percentile of the matched data 

and represents the contaminant concentration above 

which adverse effects frequently occur (Long and 

Morgan, 1991). 

• Threshold Effect Level and Probable Effect Level.

The Canadian threshold effect level (TEL) defines a 

concentration below which adverse effects are rarely 

anticipated and above which adverse effects are 

occasionally anticipated, whereas the probable effect 

level (PEL) defines a concentration above which 

adverse effects are frequently anticipated. Both the 

Canadian TEL and PEL are empirically based and 

were derived by compiling data from multiple types 

of studies in the literature, including equilibrium 

partitioning studies, guidelines from other jurisdictions, 

spiked-sediment toxicity tests, and field studies from 

throughout North America (Canadian Council of 

Ministers of the Environment, 1995 and 2001). The 

TEL and PEL values for a given contaminant were 

selected so that fewer than 25 percent of adverse 

effects occur below the TEL and more than 50 percent 

of adverse effects occur above the PEL (Canadian 

Council of Ministers of the Environment, 2001).

• Threshold Effect Concentration and Probable 

Effect Concentration. The consensus-based threshold 

effect concentration (TEC) from MacDonald and 

others (2000) defines the concentration below which 

adverse effects on sediment-dwelling organisms are 

not expected to occur. The consensus-based probable 

effect concentration (PEC) defines the concentration 

of sediment-associated contaminants above which 

adverse effects on sediment-dwelling organisms are 

likely to be observed. These guidelines were developed 

by compiling multiple sediment-quality guidelines 

for a given contaminant, including both causally 

and empirically based guidelines, identifying those 

that meet certain selection criteria, and selecting the 

geometric mean as the consensus-based guideline.

• T20 and T50. These were derived from logistic 

regression models that predict the probability of 

toxicity to marine amphipods by using a large database 

of matching sediment chemistry and toxicity data 

representing coastal North America (Field and others, 

2002). The T20 and T50 for an individual contaminant 

consist of concentrations of that contaminant that are 

associated with a 20 percent or 50 percent probability, 

respectively, of observing toxicity.
20 Contaminants in Water and Sediment Sampled in Response to the Deepwater Horizon Oil Spill Table 5E. Benchmark values for organic contaminants: supplemental aquatic-life benchmarks for organic contaminants in sediment.—Continued

[Abbreviations: AET, apparent effects threshold; B, bivalve; E, echinoderm larvae; EqP, equilibrium partitioning sediment benchmark; ERL, effects range–low; ERM, effects range–median; I, infaunal community index; L, larvae; M, microtox assay; N, neanthes bioassay; NOAA, National Oceanic and Atmospheric Administration; O, oyster larvae; PEC, probable effect concentration; PEL, probable effect level; SV, screening value; T20, chemical concentration corresponding to 20 percent probability of toxicity to marine amphipods; T50, chemical concentration corresponding to 50 percent probability of toxicity to marine amphipods; TEC, threshold effect concentration; TEL, threshold effects level; USEPA, U.S. Environmental Protection Agency; WA DOE, Washington Department of Ecology; wt, weight; μg/g-oc, microgram per gram of sediment organic carbon; μg/kg, microgram per kilogram; –, no benchmark available]Benchmark Type: Lower SV1 Upper SV1 Lower SV1 Upper SV1 Lower SV1 Upper SV1 Lower SV1 Upper SV1 Upper SV1 EqP1 EqP1Benchmark source: NOAA2 NOAA2 Canada/ Florida3 Canada/ Florida3 MacDonald4 MacDonald4 Field5 Field5 WA DOE6 USEPA7 USEPA7Units: μg/kg dry wt μg/kg dry wt μg/kg dry wt μg/kg dry wt μg/kg dry wt μg/kg dry wt μg/kg dry wt μg/kg dry wt μg/kg dry wt μg/g-oc μg/g-oc

Contaminant/benchmark name: ERL, marine ERM, marine TEL, marine PEL, marine TEC PEC T20 T50 AET EqP- acute EqP- chronic

1,2,4-Trichlorobenzene – – – – – – – – >4.8 E 6,100 920

1-Methylnaphthalene – – – – – – 21 94 – – –

1-Methylphenanthrene – – – – – – 18 112 – – –

2,4,5-Trichlorophenol – – – – – – – – 3 I – –

2,4,6-Trichlorophenol – – – – – – – – 6 I – –

2,4-Dichlorophenol – – – – – – – – 0.2083 – –

2,4-Dimethylphenol – – – – – – – – 18 N – –

2-Chlorophenol – – – – – – – – 0.333 – –

2-Methylnaphthalene 70 670 20.2 201 – – 21 128 64 E – –4-Bromophenyl phenyl ether – – – – – – – – – 2,300 130

Acenaphthene 16 500 6.71 88.9 – – 19 116 130 E – –

Acenaphthylene 44 640 5.87 128 – – 14 140 71 E – –Anthracene 85.3 1,100 46.9 245 57.2 845 34 290 280 E – –Benz(a)anthracene 261 1,600 74.8 693 108 1,050 61 466 960 E – –

Benzo(a)pyrene 430 1,600 88.8 763 150 1,450 69 520 1,100 E – –Benzo(b)fluoranthene – – – – – – 130 1,107 1,800 EI – –

Benzo(ghi)perylene – – – – – – 67 497 670 M – –

Benzo(k)fluoranthene – – – – – – 70 537 1,800 EI – –

Benzyl n-butyl phthalate – – – – – – – – 63 M 15,000 1,100

Biphenyl – – – – – – 17 73 – 850 110

Bis(2-ethylhexyl) phthalate – – 8182 82,647 – – – – 1,300 I – –

Chrysene 384 2,800 108 846 166 1,290 82 650 950 E – –Dibenzo(ah)anthracene 63.4 260 6.22 135 33.0 – 19 113 230 OM – –

Dibenzofuran – – – – – – – – 110 E 3,700 200

Diethyl phthalate – – – – – – – – 6 BL 1,100 63

Dimethyl phthalate – – – – – – – – 6 B – –

Di-n-butyl phthalate – – – – – – – – 58 BL 8,000 1,100

Di-n-octyl phthalate – – – – – – – – 61 BL – –

Fluoranthene 600 5,100 113 1,494 423 2,230 119 1,034 1,300 E – –

Fluorene 19 540 21.2 144 77.4 536 19 114 120 E – –

Table 5E. Benchmark values for organic contaminants: supplemental aquatic-life benchmarks for organic contaminants in sediment.
Methods 21

Table 5E. Benchmark values for organic contaminants: supplemental aquatic-life benchmarks for organic contaminants in sediment.—Continued[Abbreviations: AET, apparent effects threshold; B, bivalve; E, echinoderm larvae; EqP, equilibrium partitioning sediment benchmark; ERL, effects range–low; ERM, effects range–median; I, infaunal community index; L, larvae; M, microtox assay; N, neanthes bioassay; NOAA, National Oceanic and Atmospheric Administration; O, oyster larvae; PEC, probable effect concentration; PEL, probable effect level; SV, screening value; T20, chemical concentration corresponding to 20 percent probability of toxicity to marine amphipods; T50, chemical concentration corresponding to 50 percent probability of toxicity to marine amphipods; TEC, threshold effect concentration; TEL, threshold effects level; USEPA, U.S. Environmental Protection Agency; WA DOE, Washington Department of Ecology; wt, weight; μg/g-oc, microgram per gram of sediment organic carbon; μg/kg, microgram per kilogram; –, no benchmark available]Benchmark Type: Lower SV1 Upper SV1 Lower SV1 Upper SV1 Lower SV1 Upper SV1 Lower SV1 Upper SV1 Upper SV1 EqP1 EqP1Benchmark source: NOAA2 NOAA2 Canada/ Florida3 Canada/ Florida3 MacDonald4 MacDonald4 Field5 Field5 WA DOE6 USEPA7 USEPA7Units: μg/kg dry wt μg/kg dry wt μg/kg dry wt μg/kg dry wt μg/kg dry wt μg/kg dry wt μg/kg dry wt μg/kg dry wt μg/kg dry wt μg/g-oc μg/g-oc

Contaminant/benchmark name: ERL, marine ERM, marine TEL, marine PEL, marine TEC PEC T20 T50 AET EqP- acute EqP- chronic

Hexachlorobenzene – – – – – – – – 6 B – –

Hexachlorobutadiene – – – – – – – – 1.3 E – –

Hexachloroethane – – – – – – – – 73 BL 1,800 100

Indeno(123-cd)pyrene – – – – – – 68 488 600 M – –

m-Cresol plus p-cresol – – – – – – – – 9100 B – –

Naphthalene 160 2,100 34.6 391 176 561 30 217 230 E – –Nitrobenzene – – – – – – – – 21 N – –

N-Nitrosodiphenylamine – – – – – – – – 28 I – –

o-Cresol – – – – – – – – 8 B – –

Pentachlorophenol – – – – – – – – 17 B – –

Perylene – – – – – – 74 453 – – –

Phenanthrene 240 1,500 86.7 544 204 1,170 68 455 660 E – –Phenol – – – – – – – – 130 E – –

Pyrene 665 2,600 153 1,398 195 1,520 125 932 2,400 E – –Sum high MW PAH 1,700 9,600 655 6,676 – – – – 7,900 E – –

Sum low MW PAH 552 3,160 312 1,442 – – – – 1,200 E – –

Sum total PAH 4,022 44,792 1,684 16,770 1,610 22,800 – – – – –

1EqP, Equilibrium partitioning sediment benchmark, which is mechanistically based and derived from equilibrium-partitioning theory; Lower SV, empirical screening value below which adverse effects are not 

expected; Upper SV, empirical screening value above which there is a high probability of adverse effects.

2From Long and others (1995). 3Except as noted, values are common to both Canada (Canadian Council of Ministers of the Environment, 2011) and Florida Department of Environmental Protection (MacDonald and others, 1996). 4From MacDonald and others (2000).5From Field and others (2002).6From Buchman (2008). Value shown is the lowest reliable AET value among available tests, as determined by Buchman (2008). Some values also appear in Barrick and others (1998) or Gries and Waldow 

(1994). Abbreviations indicate types of bioassays, and are defined in the table headnote.

7EqP, Equilibrium partitioning sediment benchmark for either acute or chronic effects on benthic organisms from U.S. Environmental Protection Agency (2004).8Value applies to Florida only (not Canada). 9Benchmark applies to para isomer.
22 Contaminants in Water and Sediment Sampled in Response to the Deepwater Horizon Oil Spill 

Table 6A. Benchmark values for trace and major elements: aquatic-life benchmarks for trace 

elements in water.

[Abbreviations: ANZ, Australian and New Zealand Environment and Conservation Council; BC, British 

Columbia; CMC, criteria maximum concentration; LOEL, lowest observable effect level; NOAA, National 

Oceanic and Atmospheric Administration; p, proposed; USEPA, U.S. Environmental Protection Agency; WQC, 

water-quality criteria; μg/L, microgram0 per liter; –, no benchmark available]

Element Symbol Acute, marine

(μg/L)1

Chronic, marine

(μg/L) 1 Source2

Antimony Sb 31,500 3500 NOAA

Arsenic As 69 36 USEPA WQC

Barium Ba 1,000 200 BC

Beryllium Be 1,500 100 BC

Boron4 B – 1,200 BC

Cadmium Cd 40 8.8 USEPA WQC

Cobalt Co – 1 ANZ

Copper4 Cu 4.8 3.1 USEPA WQC

Lead Pb 210 8.1 USEPA WQC

Manganese Mn – 100 BC

Mercury Hg 1.8 0.94 USEPA WQC

Molybdenum Mo – 23 ANZ

Nickel Ni 74 8.2 USEPA WQC; USEPA response

Selenium Se 290 71 USEPA WQC

Silver Ag 5

0.95 – NOAA

Thallium Tl 6

2,130 17 Acute: NOAA; chronic: ANZ

Vanadium V – 50 BC; USEPA response

Zinc Zn 90 81 USEPA WQC

1

Values are USEPA ambient water-quality criteria supplemented by the lowest of Tier II Species Acute 

Values or other guidelines, as selected by Buchman (2008). Values were verified (except as noted) in the cited 

references. 

2

ANZ, Australian and New Zealand Environment and Conservation Council (2000); BC, British Columbia 

Ministry of Environment (2010); NOAA, Buchman (2008); USEPA WQC, water-quality criteria from U.S. 

Environmental Protection Agency (2009); USEPA response, USEPA Response to British Petroleum Spill in the 

Gulf of Mexico from U.S. Environmental Protection Agency (2011a).

3

p, proposed values from Buchman (2008).

4

Detected in 1 of 4 field blanks for post-landfall samples, so data were censored prior to comparison with 

benchmarks (see “Censoring Based on Quality Control Results” in text).

5

The criterion maximum concentration (CMC, which is USEPA’s acute water-quality criterion) was halved to 

correspond to the 1985 guideline derivation (Buchman, 2008).

6

USEPA’s LOEL; values (unverified) are from Buchman (2008), who compiled LOELs previously published 

by USEPA.

Table 6B. Benchmark values for trace and major elements: 

human-health benchmarks (recreational contact) for trace 

elements in water.

[Abbreviations: HH, human health; NC, noncancer effects endpoint; μg/L, 

micrograms per liter]

Element Symbol

HH Benchmark 

(child swimmer)1

(μg/L)

Cancer/ 

noncancer

Nickel Ni 15,000 NC

Vanadium V 5,400 NC

1

From U.S. Environmental Protection Agency (2010).
Methods 23

Table 6C. Benchmark values for trace and major elements: aquatic-life benchmarks for trace elements in whole sediment.[Abbreviations: A, amphipod; AET, apparent effects threshold; B, bivalve; E, Echinoderm; ERL, effects range–low; ERM,effects range–median; I, infaunal community index; L, larvae; M, Microtox assay; mg/kg dw, milligram per kilogram dry weight; N, Neanthes bioassay; NOAA, National Oceanic and Atmospheric Administration; O, oyster larvae; PEC, probable effect concentration; PEL, probable effect level; SV, screening value; T20, chemical concentration corresponding to 20 percent probability of toxicity to marine amphipods; T50, chemical concentration corresponding to 50 percent probability of toxicity to marine amphipods; TEC, threshold effect concentration; TEL, threshold effects level; USEPA, U.S. Environmental Protection Agency; WA DOE, Washington Department of Ecology; >, greater than; –, no benchmark]

Benchmark type: Lower SV1 Upper SV2 Lower SV1 Upper SV2 Lower SV1 Upper SV2 Lower SV1 Upper SV2 Upper SV2

Benchmark source: NOAA2 NOAA2 Canada/ Florida3 Canada/ Florida3 MacDonald4 MacDonald4 Field5 Field5 WA DOE6

Element Symbol

Units/

benchmark 

name:

ERL, marine ERM, marine TEL, marine PEL, marine TEC PEC T20 T50 AET

Aluminum Al percent – – – – – – – – 1.8 N

Antimony Sb mg/kg dw – – – – – – 0.63 2.4 9.3 E

Arsenic As mg/kg dw 8.2 70 7.24 41.6 9.79 33 7.4 20 35 B

Barium Ba mg/kg dw – – 7130.1 – – – – – 48 A

Cadmium Cd mg/kg dw 1.2 9.6 0.7 4.2 0.99 4.98 0.38 1.4 3 N

Cobalt Co mg/kg dw – – – – – – – – 10 N

Chromium Cr mg/kg dw 81 370 52.3 160 43.4 111 49 141 62 N

Copper Cu mg/kg dw 34 270 18.7 108 31.6 149 32 94 390 MO

Iron Fe percent – – – – – – – – 22 N

Lead Pb mg/kg dw 46.7 218 30.2 112 35.8 128 30 94 400 B

Manganese Mn mg/kg dw – – – – – – – – 260 N

Mercury Hg mg/kg dw 0.15 0.71 0.13 0.70 0.18 1.06 0.14 0.48 0.41 MO

Nickel Ni mg/kg dw 20.9 51.6 815.9 842.8 22.7 48.6 15 47 110 EL

Selenium Se mg/kg dw – – – – – – – – 1 A

Silver Ag mg/kg dw 1 3.7 80.73 81.77 – – 0.23 1.1 3.1 B

Tin Sn mg/kg dw – – 90.048 – – – – – >3.4 N

Vanadium V mg/kg dw – – – – – – – – 57 N

Zinc Zn mg/kg dw 150 410 124 271 121 459 94 245 410 I

1Lower SV, empirical screening value below which adverse effects are not expected; Upper SV, empirical screening value above which there is a high probability of adverse effects.2From Long and others (1995). 3Except as noted, values are common to both Canada (Canadian Council of Ministers of the Environment, 2011) and Florida Department of Environmental Protection (MacDonald and others, 1996). 4From MacDonald and others (2000).5From Field and others (2002).6From Buchman (2008). Value shown is the lowest reliable AET value among available tests, as determined by Buchman (2008). Some values also appear in Barrick and others (1998) or Gries and Waldow 

(1994). Abbreviations indicate types of bioassays, and are defined in the table headnote.

7Based on Screening Level Concentration approach using sensitive species, HC5 (hazardous concentration for 5 percent of species). From Leung and others (2005).8Value applies to Florida only (not Canada).9Based on equilibrium-partitioning approach using the current criterion continuous concentration (CCC, USEPA’s chronic ambient water-quality criterion). From Buchman (2008).
24 Contaminants in Water and Sediment Sampled in Response to the Deepwater Horizon Oil Spill 

Table 6D. Benchmark values for trace and major elements: national baseline concentrations for trace and major elements in the less 

than 63-micrometer sediment fraction.

[Abbreviations: mg/kg, milligram per kilogram; <, less than; ≤, less than or equal to; ±, plus or minus]

Constituent Symbol Units Baseline minimum1 Baseline median1 Baseline maximum1

Aluminum Al percent 4.9 5.9 6.9

Antimony Sb mg/kg 0.5 0.7 1.2

Arsenic As mg/kg 4.4 6.6 8.8

Barium Ba mg/kg 380 490 600

Beryllium Be mg/kg 1 1.8 2.6

Cadmium Cd mg/kg 0.2 0.37 0.6

Calcium Ca percent 0.5 1.8 3.1

Cerium Ce mg/kg 54 69 84

Chromium Cr mg/kg 45 58 71

Cobalt Co mg/kg 8 12 16

Copper Cu mg/kg 14 20 26

Iron Fe percent 2.2 2.9 3.6

Lanthanum La mg/kg 31 39 47

Lead Pb mg/kg 14 20 26

Lithium Li mg/kg 20 30 40

Magnesium Mg percent 0.5 0.9 1.3

Manganese Mn mg/kg 480 840 1,200

Mercury Hg mg/kg 0.02 0.04 0.06

Molybdenum Mo mg/kg 0.7 1 1.3

Nickel Ni mg/kg 16 23 30

Phosphorus P mg/kg 800 1,000 1,200

Potassium K percent 1.2 1.5 1.8

Selenium Se mg/kg 0.5 0.65 0.9

Silver Ag mg/kg 0.1 0.2 0.3

Sodium Na percent 0.3 0.6 0.9

Strontium Sr mg/kg 90 150 210

Sulfur S percent 0.04 0.08 0.12

Tin Sn mg/kg 1.5 2.5 4

Titanium Ti percent 0.25 0.33 0.41

Total carbon TC percent 1.7 3.3 4.9

Total organic carbon TOC percent 1.3 2.4 3.5

Vanadium V mg/kg 62 83 104

Zinc Zn mg/kg 71 90.5 110

1

Baseline median, median concentration associated with sites (1) that were predominantly agricultural or undeveloped, (2) where urban land use was ≤5 

percent, and (3) where population densities were ≤27 people per square kilometer, calculated from 450 bed-sediment samples collected from streams across 

the United States. The baseline minimum and baseline maximum values are equivalent to the median baseline ±30 percent median absolute deviation. From 

Horowitz and Stephens (2008).
Methods 25

National Baseline Concentrations for Trace and 

Major Elements and Nutrients in Fine Sediment

Trace and major elements and nutrients in the less than 

63-μm sediment fraction were compared to national baseline 

concentrations from Horowitz and Stephens (2008). Although 

not technically benchmarks, these baseline concentrations can 

be used to indicate anthropogenic enrichment. Horowitz and 

Stephens (2008) determined national baseline concentrations 

for trace and major elements, and some nutrients, in stream 

sediments collected from agricultural or undeveloped areas or 

areas with population density less than or equal to 27 people 

per square kilometer and urban land use less than or equal 

to 5 percent. These authors found that enrichment of some 

elements above baseline was associated with urban land 

use and population density. These elements, in generally 

decreasing likelihood of enrichment, are lead, mercury, 

silver, zinc, cadmium, copper, antimony, sulfur, nickel, tin, 

chromium, arsenic, cobalt, iron, and phosphorus. Horowitz 

and Stephens (2008) computed the minimum, median, and 

maximum baseline concentrations for each element, where 

the range between the minimum and maximum baseline 

concentrations represents the range of natural geochemical 

variance. In Horowitz and Stephens (2008), sediment was 

wet-sieved through a less than 63-μm mesh and subjected to 

total digestion prior to analysis; thus, these authors determined 

total concentrations, that is 95 percent or more of the 

constituent present, in the less than 63-μm sediment fraction. 

The processing and analytical methods used by these authors 

are comparable to those used in the present study. 

In the present study, the measured concentration of each 

element was divided by its maximum baseline concentration to 

obtain a maximum baseline quotient. The maximum baseline 

concentration is the upper end of the range in baseline values 

for a given element as determined by Horowitz and Stephens 

(2008) and listed in table 6D. “Enrichment” above baseline 

is defined as having the maximum baseline quotient greater 

than 1, with the following exception. For samples in which the 

less than 63-μm fraction makes up less than 1 percent of the 

total sediment, analytical errors are elevated, and there often is 

insufficient material to run duplicate analyses to determine the 

degree of precision. In this case, the precision could be as poor 

as a 100 percent difference, especially at concentrations near 

the detection level (Arthur J. Horowitz, Research Chemist, 

USGS, Atlanta, Georgia, written comm., Feb. 3, 2011). For 

individual samples with less than 1 percent of total sediment 

in the less than 63-μm fraction, therefore, maximum baseline 

quotients needed to be elevated above 2 in order to indicate 

enrichment. By itself, enrichment, as indicated by maximum 

baseline exceedance, does not necessarily indicate a potential 

for adverse effects. 

Interpretation of Benchmark Exceedances 

For organic contaminants, exceedance of either an EqP 

benchmark or an upper screening value was considered to 

be an indication of potential toxicity to benthic organisms. 

Trace elements were considered to be of most concern if 

they met the following exceedance criteria for both potential 

toxicity and anthropogenic enrichment: (1) they exceeded one 

or more upper screening values in whole sediment samples 

and (2) they were enriched relative to national baseline 

concentrations in less than 63-μm sediment samples. Because 

sediment samples were analyzed for total trace-element 

concentrations, exceedance rates for upper screening values 

could be overestimated but are not likely to be underestimated; 

therefore, these rates, and resulting inferences about potential 

toxicity, can be considered conservatively high.

In addition, for both organic contaminants and trace 

elements, sediment samples were classified into one of three 

effect ranges using terminology from Canadian Council of 

Ministers of the Environment (2001): (1) minimal-effect 

range, within which adverse biological effects rarely occur 

(that is, all constituents were below their lower screening 

values); (2) possible-effect range, within which adverse 

biological effects occasionally occur (one or more constituents 

exceeded a lower screening value, but no elements exceeded 

an upper screening value); or (3) probable-effect range, within 

which adverse biological effects frequently occur (one or more 

constituents exceeded an upper screening value). 

Data Compilation 

Each distinct sampling event is recorded in the USGS 

database with a unique combination of agency code for the 

site, station-identification number, sample-collection start date, 

sample-collection end date, and sample medium. The agency 

code associated with the samples described in this report is 

“USGS,” and the station-identification numbers are presented 

in table 1. In the database, sediment samples are assigned 

sampling-medium designations of either bottom material or 

soil. 

The results for environmental samples from water and 

sediment can be retrieved from the USGS by supplying the 

station-identification numbers to one of the following web 

sites: 

• NWISWeb (http://nwis.waterdata.usgs.gov/usa/nwis/

qwdata) or

• Water-Quality Data Portal (http://qwwebservices.usgs.

gov/portal.html)
26 Contaminants in Water and Sediment Sampled in Response to the Deepwater Horizon Oil Spill 

The Data Portal provides data in a manner consistent with 

similar data provided by the STORET database, except that a 

few of the observational metadata available from NWISWeb 

are omitted. Samples collected prior to July 15, 2010, are 

categorized as “pre-landfall,” and subsequent samples are 

categorized as “post-landfall.” 

Sometimes, one or more constituents in a particular 

sample were reanalyzed to verify the results or to employ 

an analytical method with improved sensitivity to low 

concentrations. When verification reruns were performed, 

the earliest analytical result is presented in the database, and 

additional results from a subsequent analysis are preserved 

in the “result-laboratory” comments field. When a more 

sensitive method was employed, however, the results from 

the more sensitive method are presented in the database, and 

results from the less sensitive method are preserved in the 

“result-laboratory” comments.

Data Analyses 

Data for all analyses described in this report were 

obtained on March 28, 2011 (March 24 DWH GOM Data 

Release), and used as received from the participating 

laboratories without further rounding. Benchmark comparisons 

were made for all samples, including environmental and 

field-replicate samples. For most sites, if multiple samples 

were collected during either the pre-landfall or post-landfall 

sampling period, one was designated as the primary, or 

environmental sample, and any others were considered to be 

replicates for that sampling period. If no primary sample was 

designated, however, or if the primary sample was missing 

data for either trace elements or organic analytes, then the 

replicate sample with the earliest date and time, or with data 

for the fullest suite of analytes, typically was designated as a 

primary sample. This “primary-sample” dataset was used for 

statistical summaries of contaminant occurrence, so that each 

site was represented only once for each sampling period and 

analytical method. 

A subset of the primary-sample dataset, consisting 

of paired pre- and post-landfall samples, was used for 

statistical comparison of pre-landfall to post-landfall sample 

concentrations at these sites. This “paired-sample” dataset 

was generated by dropping data for all sites that were sampled 

during only one sampling period, either pre-landfall or 

post-landfall. The resulting paired-sample dataset contained 

exactly two samples per site—one collected during each of the 

pre-landfall and post-landfall periods. 

Detection frequencies and percentile concentrations 

were determined by using procedures in the statistical 

software package, SAS 9.2 TS Level 2M3 (SAS Institute 

Inc., 2009a and 2009b). Summary statistics are presented 

separately for each chemical class (organic contaminants, 

or trace and major elements and nutrients) in each sampling 

medium (water, whole sediment, or less than 63-μm sediment 

fraction). The detection frequency for a given analyte varies 

with the sensitivity of the analytical method; for example, 

of two methods for a given analyte, the method with the 

lower reporting level is likely to result in a higher detection 

frequency. Therefore, to facilitate comparison of detection 

frequencies between sampling periods and for different 

contaminants, detection frequencies were calculated at 

multiple detection thresholds appropriate for the chemical 

class and sampling medium. These detection thresholds 

are discussed in detail in the section on “Data Censoring.” 

Briefly, for each analyte, one “optimal” detection threshold 

was determined to facilitate comparison between pre-landfall 

and post-landfall samples. In addition, detection frequencies 

for all analytes within the same contaminant class and 

sampling medium were computed at each of four common 

detection thresholds to allow comparison of detection 

frequencies among analytes. In the context of this study, data 

censoring refers to the process of distinguishing detections, 

or quantified values, from nondetections, or censored values; 

censored datasets are datasets with some portion of the results 

composed of nondetections. 

Percentiles of concentrations were determined in the 

primary-sample dataset by using one of four methods, 

depending on the amount of censored data, or nondetections, 

for a given analyte (fig. 2). For analytes detected in 100 

percent of samples, or having no censored data, the SAS 

UNIVARIATE procedure was used to compute concentration 

percentiles. For analytes with some, but less than 50-percent, 

censored data, percentiles were estimated by using the 

nonparametric Kaplan-Meier method (Helsel, 2005) in 

the SAS LIFETEST procedure. For analytes with 50- to 

80-percent censored data, percentiles were estimated by 

using a SAS freeware macro, Censored Data Regression 

on Order Statistics (Helsel, 2005). For analytes with more 

than 80-percent censored data, all data for that analyte were 

censored at a common detection threshold, and only the 95th 

percentile concentration was calculated. 

Statistical comparisons of contaminant concentrations 

in pre-landfall to post-landfall samples were made by using 

the paired Prentice-Wilcoxon (PPW) test. This test was 

implemented by using the USGS S-PLUS library version 4.0 

(Lorenz and others, 2011) for the statistical software package 

Spotfire S+ (TIBCO Software, Inc., 2008). The PPW test is 

appropriate for comparing two groups with matched pairs 

of data and can be applied to censored datasets. This test 

evaluates whether there is a difference in the distributions of 

the two sample groups. To do so, first the data are stacked 

into one column, a score is computed for each observation 

(both censored and uncensored data) on the basis of the 

Kaplan-Meier estimate of the survival function, and then 

the scores are divided back into the two groups of matched 

pairs. The PPW test computes the differences between the 

paired scores and determines whether the sum of these 

differences is significantly different from zero by using a 

normal approximation for the test statistic (Helsel, 2005). In 

this study, the PPW test was performed on the paired-sample 

dataset, which represents the 48 sites that were sampled 

during both the pre-landfall and post-landfall periods, as 

described previously. 
Methods 27

Additional PPW tests were used to compare 

concentrations in pre-landfall and post-landfall samples 

collected at a subset of 19 paired-sample sites that were 

identified by Rosenbauer and others (2010) as having 

geochemical evidence, or a fingerprint, of M-1 well oil in postlandfall samples of sediment, tarballs, or both. At this subset of 

sites, which is called the “fingerprint-sample” dataset, there is 

direct evidence from Rosenbauer and others (2010) of residual 

M-1 well oil at the sites during the post-landfall period. 

Benchmark exceedance frequencies were computed by 

using the Spotfire S+ program. All field samples, including 

primary and replicate samples, were compared to benchmarks 

to maximize the information on benchmark exceedance. 

However, direct comparison between exceedance frequencies 

for the pre-landfall and post-landfall sampling periods must be 

qualified because data from the two sampling periods do not 

represent exactly the same sites. Specifically, 22 pre-landfall 

sites and 1 post-landfall site were not sampled during the other 

sampling period (table 1); also, 20 of the 71 total sites were 

sampled more than once during one or both sampling periods. 

For each combination of contaminant class and sampling 

medium, Fisher’s exact test was used to determine whether 

the proportion of samples exceeding applicable benchmarks 

was significantly different (p<0.05) between the pre-landfall 

and post-landfall sampling periods. This test was performed 

on the 48 sites in the paired-sample dataset, so that the same 

sites are represented only once in both sampling periods. In 

addition, the paired-sample sign test was used to compare 

selected benchmark exceedance results, such as ∑TUi and

∑ESBTUi values, and benchmark exceedances for individual 

trace elements, between pre-landfall and post-landfall samples 

in the paired-sample dataset. A nonparametric test with few 

assumptions, this tests whether the pre-landfall values were 

generally larger or smaller than the post-landfall values 

(p<0.05; Helsel and Hirsch, 2002). 

175

150

125

100

75

50

25

0

NUMBER OF ANALYTES IN CLASS

PRE ORGANICS WTRPOST ORGANICS WTRPRE ORGANICS SEDPOST ORGANICS SEDPRE TMN WTRPOST TMN WTRPRE TMN SEDPOST TMN SED

sac12-0452_Figure 02

157

118

70

98

33 31

68 68

EXPLANATION

CENSOR CATEGORY

HIGH (>80% censored) 

Regression on ordered

statistics using censored

data (50–80% censored) 

None (100% censored) 

Nonparametric

 percentiles

 (0% censored) 

None (< 5 samples) 

Kaplan Meier

 estimation

 (0–50% censored) 

PRE is Pre-landfall; POST is Post-landfall; SED is sediment; TMN is trace and major elements and nutrients;

WTR is water; > is greater than; < is less than; % is percent of data censored 

Figure 2. Number of analytes for which percentiles were determined by using four different methods, shown by 

contaminant class, sampling medium, and sampling period from the 2010 Deepwater Horizon oil spill in the Gulf of Mexico.
28 Contaminants in Water and Sediment Sampled in Response to the Deepwater Horizon Oil Spill 

For comparison of measured contaminant concentrations 

to various benchmarks for human health and aquatic life, some 

data manipulations were necessary because of the nature of the 

dataset. Specifically, the following apply:

• In this study, trace-element concentrations are 

reported as total concentrations in water. Because 

most benchmarks for trace elements are expressed in 

terms of dissolved concentration in the water column, 

estimates of these benchmarks as total trace-element 

concentrations were calculated by using saltwater 

conversion factors from U.S. Environmental Protection 

Agency (2011d) prior to comparison with measured 

concentrations (Buchman, 2008). 

• As previously described, water samples were not 

analyzed for the alkylated PAH groups required for 

calculation of USEPA benchmarks for mixtures of 

PAH and BTEX compounds (∑TUi). Concentrations 

of each alkylated PAH group were estimated from the 

corresponding parent PAH concentrations by using 

multipliers, as specified in the USEPA procedures for 

benchmark calculation (Mount, 2010).

• For sediment samples, BTEX compounds were not 

determined, so calculated ∑ESBTUi values could 

be slightly low; however, this bias is expected to be 

minimal because BTEX compounds are volatile, were 

not detected in weathered M-1 oil (State of Florida 

Oil Spill Academic Task Force, 2010), and are not 

expected to persist in sediment (Mount, 2010). 

Results and Discussion 

The results are presented first for QC analyses because 

these findings affect interpretation of field sample data. 

Following the QC data discussion, results are presented 

separately for each combination of contaminant class and 

sampling medium. In each case, contaminant occurrence 

is assessed, statistical comparisons are made between 

concentrations in pre-landfall and post-landfall samples, and 

measured concentrations are compared to applicable water- or 

sediment-quality benchmarks. 

Quality-Control Analyses

Analytical results for the various QC samples follow. 

These results were considered in computing occurrence 

statistics and making benchmark comparisons, as discussed 

later in this section.

Blank Samples

Results were available for 166 analytes in at least 

4 pre-landfall field blanks. Most of these results were from 

the USGS NWQL. In addition, results were available from 

TestAmerica Laboratory in Colorado for six analytes, four 

of which overlap with analytes determined by the USGS 

NWQL, and results were available from the USGS OCRL 

for dissolved organic carbon. Of the 885 total results, 861 

(97 percent) were reported as censored values (nondetections). 

There were 24 quantified results, or detections, reported in 

blanks, affecting a total of 21 analytes (table 7). Five of the 

quantified values were less than the highest reporting level 

for that analyte. These were quantified by using corroborating 

evidence of analyte presence in the mass spectrogram, even 

though the concentration was below the typical reporting level 

for the method.

During the post-landfall sampling period, four field 

blanks were collected and shipped to the TestAmerica 

Laboratory in Florida for analysis. Of the 584 total reported 

results for 146 analytes, 564 (97 percent) were nondetections. 

There were 20 quantified detections reported for 12 analytes 

(table 8), of which only 3 are organic contaminants. Ammonia 

plus organic nitrogen and phosphorus were quantified in 

each of the four blanks. Trip blanks also were analyzed by 

the TestAmerica Laboratory during post-landfall sampling. 

These have limited utility for comparison to environmental 

samples; however, quantified detections reported for three 

analytes (table 8) could indicate potential for contamination 

during laboratory processing and analysis. None of these 

three analytes were detected in field blanks analyzed at this 

laboratory. The benzene result was from a blank associated 

with an environmental sample collected in Louisiana on 

October 12; the other results were from a blank associated 

with a sample collected in Florida on October 13.

There was little consistency in blank contamination 

between sampling periods. Only four analytes—calcium, 

magnesium, naphthalene, and sodium—were detected in 

blanks from both the pre-landfall and post-landfall periods. 

Six analytes detected in the pre-landfall blanks—1,4-

dichlorobenzene, 4-chloro-3-methylphenol, arsenic, 

dichloromethane, ethyl methyl ketone, and silver—were 

quantified at concentrations less than the reporting level 

for post-landfall blanks. Similarly, copper was detected in 

two post-landfall blanks, but at concentrations less than the 

highest reporting level for pre-landfall blanks. Because of 

these discrepancies, it was not possible to evaluate differences 

in incidental contamination between sampling periods. 

In subsequent data analyses, potential contamination in 

environmental samples was determined separately for each 

period by using field blanks collected during that period. 
Results and Discussion 29

Table 7. Analytes with quantified detections in field blanks collected during the pre-landfall sampling period from the Deepwater 

Horizon oil spill, Gulf of Mexico, 2010.1

[Abbreviations: BTEX, benzene, toluene, ethylbenzene, xylenes and related compounds; mg/L, milligram per liter; USGS, U.S. Geological Survey; μg/L, 

microgram per liter]

Analyte Units Number 

of blanks

Highest 

reporting 

level

Number of 

quantified 

results

Maximum 

quantified 

value

Raised 

censoring 

level2

USGS National Water-Quality Laboratory

Organic contaminants

1,2,3,5-Tetramethylbenzene μg/L 5 0.08 1 0.032 0.16

1,2,3-Trimethylbenzene μg/L 5 0.06 1 0.022 0.11

1,2,4-Trimethylbenzene μg/L 5 0.016 1 0.026 0.13

1,4-Dichlorobenzene μg/L 6 0.22 1 0.014 0.07

4-Chloro-3-methylphenol μg/L 6 0.55 1 0.058 0.29

Acetone μg/L 5 1.7 1 4.5 45

Dichloromethane μg/L 5 0.019 1 0.64 6.4

Ethyl methyl ketone μg/L 5 1.6 1 0.49 4.9

Ethylbenzene μg/L 5 0.018 1 0.031 0.155

Naphthalene μg/L 6 0.22 1 0.057 0.285

Toluene μg/L 5 0.009 1 0.083 0.83

Trichloromethane μg/L 5 0.015 1 1.8 9

Xylene, meta plus para μg/L 5 0.04 1 0.10 0.5

Xylene, ortho μg/L 5 0.016 1 0.12 0.6

Trace and major elements

Arsenic μg/L 34 0.09 1 0.15 0.75

Calcium mg/L 44 0.02 1 0.02 0.1

Lithium μg/L 5 0.04 1 0.23 1.15

Magnesium mg/L 5 0.012 1 0.013 0.065

Silver μg/L 5 0.12 1 0.57 2.85

Sodium mg/L 5 0.36 1 0.41 2.05

USGS Organic Carbon Research Laboratory

Dissolved organic carbon mg/L 5 0.7 4 0.70 3.5

1

Blanks for BTEX compounds, gasoline range organics, and diesel range organics were submitted to the TestAmerica Laboratory in Colorado; all results were 

censored.

2

The censoring level was raised to 5 times the maximum quantified value or, for common laboratory contaminants, to 10 times the maximum quantified value.

3

One result with an elevated reporting level of 1.35 μg/L was excluded.

4

One result with an elevated reporting level of 0.06 μg/L was excluded.

Sediment-equipment rinsate blank results were available 

for 146 analytes from the TestAmerica Laboratory in Florida 

and for one analyte from the USGS OCRL. Of the 389 

total reported results, 365 (94 percent) are nondetections. 

There were 24 quantified detections reported for 14 analytes 

(table 9). Similar to results for the post-landfall field blanks, 

ammonia plus organic nitrogen and phosphorus were detected 

in each of the sediment-equipment rinsate blanks. Naphthalene 

and toluene were the only organic compounds detected. The 

extremely high concentration of boron in one blank could 

have been caused by residue from a cleaning solution that 

was used on the sampling equipment. If so, the potential for 

contamination of a sediment sample collected by using this 

equipment is probably much less than the concentration in a 

blank-water rinse. Any residue would likely be washed away 

during field rinsing of the equipment.
30 Contaminants in Water and Sediment Sampled in Response to the Deepwater Horizon Oil Spill 

Table 8. Analytes with quantified detections in field and trip blanks collected during the post-landfall sampling period and analyzed at

the TestAmerica Laboratory in Pensacola, Florida, from the 2010 Deepwater Horizon oil spill in the Gulf of Mexico.

[Abbreviations: mg/L, milligrams per liter; μg/L, micrograms per liter; –, no results were censored]

Analyte Units Number of 

blanks

Highest 

reporting 

level 

Number of 

quantified 

results

Maximum 

quantified 

value

Raised 

censoring 

level1

Field blanks

Organic contaminants

Diesel range organics μg/L 4 46 1 50 250

Diethyl phthalate μg/L 4 0.26 1 0.42 4.2

Naphthalene μg/L 4 0.15 1 0.16 0.8

Trace and major elements, and nutrients

Ammonia plus organic nitrogen as N mg/L 4 0.02 4 1.7 8.5

Boron μg/L 4 5 1 10 50

Calcium mg/L 4 0.03 1 0.072 0.36

Copper μg/L 4 2.0 2 2.2 11

Magnesium mg/L 4 0.03 1 0.2 1

Mercury μg/L 4 0.07 2 0.18 0.9

Phosphorus as P mg/L 4 – 4 0.13 0.65

Potassium mg/L 4 0.1 1 0.16 0.8

Sodium mg/L 4 0.5 1 2.2 11

Trip blanks

Organic contaminants

Benzene μg/L 31 0.34 1 0.42 2.1

Dichloromethane μg/L 31 1 1 3.1 15.5

Trichlorofluoromethane μg/L 31 0.52 1 0.62 3.1

1

The censoring level was raised to 5 times the maximum quantified value in blanks or, for common laboratory contaminants, to 10 times the maximum 

quantified value in blanks.

Table 9. Analytes with quantified detections in sediment-equipment rinsate blanks from the Deepwater Horizon oil spill, Gulf of 

Mexico, 2010.

[Abbreviations: mg/L, milligrams per liter; USGS, U.S. Geological Survey; μg/L, micrograms per liter; –, not applicable]

Analyte Units Number of 

blanks

Highest 

reporting 

level

Number of 

quantified 

results

Maximum 

quantified 

value

TestAmerica Laboratory—Florida

Organic contaminants

Naphthalene μg/L 3 0.15 1 0.76

Toluene μg/L 2 0.70 1 8.7

Trace and major elements, and nutrients

Ammonia plus organic nitrogen as N mg/L 3 – 3 1.6

Boron μg/L 3 5.0 2 500

Calcium mg/L 3 0.030 2 0.088

Copper μg/L 3 2.0 1 4.4

Magnesium mg/L 3 0.030 1 0.22

Manganese μg/L 3 1.0 1 1.5

Mercury μg/L 3 0.070 1 0.11

Phosphorus as P mg/L 3 – 3 0.18

Potassium μg/L 3 0.10 1 0.25

Sodium mg/L 3 0.50 2 2.7

Zinc μg/L 3 8.0 1 19

USGS Organic Carbon Research Laboratory

Dissolved organic carbon mg/L 4 – 4 0.50
Results and Discussion 31

Field Replicates

Replicate samples were analyzed at all laboratories used 

in this study (table 4). Replicate-sample data analysis requires 

quantified detections for at least two samples in a set in order 

to compute a standard error. In this study, many analytes, 

particularly organic compounds in water, were not detected 

in most or all replicate samples. Only those analytes with at 

least two quantified detections in at least four replicate sets 

were included in this analysis of variability.

Generally, the number of replicate sets was too 

small to evaluate variability over low and high ranges of 

concentration, so variability was simply estimated as the 

average RSD. This can be considered a conservatively 

high estimate of variability because RSD values for lowconcentration replicates typically are much higher than the 

average for high-concentration replicates. In subsequent 

interpretation of environmental data, variability was noted as 

a possible source of uncertainty for any contaminant with a 

replicate RSD greater than 10 percent for water or 20 percent 

for sediment. 

Replicate water samples collected during the pre-landfall 

period were analyzed at the USGS NWQL, the USGS OCRL, 

and the TestAmerica Laboratory in Colorado. The USGS 

OCRL also analyzed replicate water samples from the postlandfall period, and these were combined with the pre-landfall 

samples for data analysis. Replicate sets with quantified 

detections were available for only 21 analytes: 2 organic 

compounds and 17 major ions, nutrients, or trace elements 

from the USGS NWQL, plus dissolved organic carbon and 

dissolved nitrogen from the USGS OCRL. The number of 

pre-landfall replicate sets ranged from 4 to 27, depending on 

the analyte, and the resulting mean RSD ranged from about 

1 percent to almost 19 percent (table 10). The mean RSD 

exceeded 10 percent for 8 of the 21 analytes in pre-landfall 

water samples. 

Table 10. Mean relative standard deviation for water analytes with quantified detections in at least two samples in at least four sets of

replicate water samples from the Deepwater Horizon oil spill, Gulf of Mexico, 2010.1

[Abbreviations: mg/L, milligrams per liter; RSD, relative standard deviation; USGS, U.S. Geological Survey; μg/L, micrograms per liter; –, not applicable]

Analyte Units

USGS National Water 

Quality Laboratory 

(pre-landfall)

TestAmerica 

Laboratory, Florida 

(post-landfall)

Number of 

replicate sets

Mean RSD 

(percent)

Number of 

replicate sets

Mean RSD 

(percent)

Organic contaminants

Isophorone μg/L 6 7.59 – –

Dissolved organic carbon2 mg/L 13 3.81 – –

Trace and major elements, and nutrients

Aluminum μg/L 10 13.87 5 9.23

Ammonia plus organic nitrogen as N mg/L 27 12.76 7 16.16

Ammonia as N mg/L 22 12.66 – –

Arsenic μg/L 26 8.68 – –

Barium μg/L 26 4.59 7 8.13

Boron μg/L – – 7 0.83

Calcium mg/L 26 2.63 7 1.48

Cobalt μg/L 8 11.15 – –

Iron μg/L 21 18.72 4 19.18

Lithium μg/L 26 2.98 – –

Magnesium mg/L 26 2.78 7 0.56

Manganese μg/L 21 14.06 5 12.09

Mercury μg/L – – 4 29.63

Molybdenum μg/L 26 1.57 – –

Phosphorus as P mg/L 18 15.38 7 9.05

Potassium mg/L 26 3.06 7 4.96

Selenium μg/L 4 5.77 – –

Sodium mg/L 26 1.01 7 2.10

Strontium μg/L 26 2.78 – –

Dissolved nitrogen2 mg/L 13 5.64 – –

1

Replicates collected during the pre-landfall period were submitted to the TestAmerica Laboratory in Colorado for analysis of diesel range organics, but only 

one set had more than one quantified result.

2

Analyzed by USGS Organic Carbon Research Laboratory; samples collected during both sampling periods.
32 Contaminants in Water and Sediment Sampled in Response to the Deepwater Horizon Oil Spill 

Replicate water samples collected during the postlandfall period were analyzed at the TestAmerica Laboratory 

in Florida. Quantified detections were available to assess the 

variability for 12 major ions, nutrients, or trace elements. 

The number of replicates sets ranged from 4 to 7, depending 

on the analyte, and the mean RSD ranged from less than 

1 percent to almost 30 percent (table 10). The mean RSD 

exceeded 10 percent for 4 of the 12 analytes in post-landfall 

water samples. 

Replicate sediment samples collected during the 

pre‐landfall period were analyzed at the USGS NWQL, the 

USGS SCL, and the TestAmerica Laboratories in Colorado 

and Vermont (table 4). Samples collected during the postlandfall period were analyzed at the USGS SCL and the 

TestAmerica Laboratories in Florida and Vermont. There 

were too few detections in replicate data from the USGS 

NWQL and the TestAmerica Laboratory in Florida to compute 

representative mean RSD values. For the other laboratories, 

replicate data from both sampling periods were combined for 

this analysis. Quantified results were available for 15 organic 

contaminants from the TestAmerica laboratories and for 

31 trace and major elements and nutrients from the USGS 

SCL. Analyses at the SCL included both whole sediment and 

the less than 63-μm sediment fraction. Mean RSD values were 

computed for all 31 analytes in the less than 63-μm sediment 

fraction, but quantified detections were available to compute 

mean RSD values for only two analytes—molybdenum and 

tin—in the whole-sediment samples. 

Table 11 lists mean RSD values for organic contaminants 

in whole sediment and for trace and major elements and 

nutrients in the less than 63-μm sediment fraction. For organic 

contaminants, the number of replicate sets ranged from 5 to 

17, depending on the contaminant, and the resulting mean 

RSD ranged from about 9 percent to more than 47 percent. 

Mean RSD exceeded 20 percent for 12 of the 15 organic 

contaminants in sediment. For trace and major elements and 

nutrients, the number of replicate sets ranged from 4 to 17, 

and the mean RSD ranged from about 2 percent to more 

than 28 percent. Mean RSD exceeded 20 percent for 4 of the 

31 constituents in sediment.

Matrix Spikes

The USGS NWQL spiked 85 organic compounds 

in 5 separate water-matrix samples collected during the 

pre-landfall period. Mean recovery for individual analytes 

ranged from about 52 to 134 percent. The lowest recovery was 

for dichlorodifluoromethane; otherwise, all recoveries were 

greater than 60 percent. The highest recovery was for acetone, 

which is a common laboratory contaminant and was measured 

at 4.5 micrograms per liter (μg/L) in one field blank analyzed 

at the USGS NWQL. The next highest recovery was only 

about 110 percent. Thus, almost all recoveries for this group of 

spikes were between 60 and 110 percent.

The TestAmerica Laboratory in Florida prepared 

duplicate spikes for 107 organic compounds and 24 trace 

elements in 5 water-matrix samples during the postlandfall period. Mean recovery for individual analytes 

ranged from about 19 to 124 percent. The lowest mean 

recoveries were for 3, 3’-dichlorobenzidine at 19.2 percent 

and N-nitrosodiphenylamine at 43.4 percent; otherwise, 

all recoveries were greater than 52 percent. The highest 

recoveries were for aluminum at 124 percent and mercury 

at 117 percent. Mercury also was found in two field blanks 

at the TestAmerica Laboratory in Florida, at a maximum 

concentration of 0.18 μg/L; therefore, the high recovery could 

have been due to contamination.

Spikes in water-matrix samples at the two laboratories 

had 41 analytes in common. Differences in recoveries were 

generally small—less than 17 percent for all but five analytes.

The USGS NWQL spiked 37 organic compounds into 

4 separate sediment-matrix samples collected during the prelandfall period. Mean recovery for individual analytes ranged 

from about 23 to 62 percent. The lowest mean recoveries were 

for 1,2,4-trichlorobenzene at 22.9 percent and naphthalene 

at 33.7 percent; otherwise, all recoveries were greater than 

44 percent. The TestAmerica Laboratory in Florida prepared 

duplicate spikes for 59 organic compounds in either 3 or 

4 sediment-matrix samples during the post-landfall period. 

Mean recovery for individual analytes ranged from 43 to 

about 88 percent. The lowest mean recoveries were for 

N-nitrosodiphenylamine at 43.0 percent and 4-chloroaniline 

Table 11. Mean relative standard deviation for analytes with 

quantified detections in at least two samples in at least four sets 

of replicate sediment samples from the Deepwater Horizon oil 

spill, Gulf of Mexico, 2010.1,2

[Abbreviations: mg/kg, milligrams per liter; RSD, relative standard 

deviation; USGS, U.S. Geological Survey; μg/kg, micrograms per kilogram]

Analyte Units Number of 

replicate sets

Mean RSD 

(percent)

Selenium mg/kg 16 12.05

Sodium percent 17 28.44

Strontium mg/kg 17 10.28

Sulfur percent 17 17.17

Tin mg/kg 5 23.84

Titanium percent 15 7.94

Vanadium mg/kg 16 8.30

Zinc mg/kg 17 16.97

1

Replicates collected during the pre-landfall period were submitted to the 

USGS National Water Quality Laboratory for analysis of several organic 

compounds, but none had more than one quantified result in more than three 

sets.

2

Replicates collected during the post-landfall period were submitted to the 

TestAmerica Laboratory in Florida for analysis of oil and grease, but only 3 

sets had more than one quantified result.
Results and Discussion 33

at 56.2 percent; otherwise, all recoveries were greater than 

61 percent. Spikes at the 2 laboratories had 18 analytes in 

common; mean recoveries in spikes from the TestAmerica 

Laboratory in Florida were consistently higher by about 13 to 

35 percent.

Analytes with low spike recovery could also have a low 

bias in environmental-sample results. In the present study, 

recovery is considered to be within acceptable limits if it is 

between 70 and 115 percent for organic analytes in water 

samples and between 50 and 115 percent for organic analytes 

in sediment samples. Table 12 provides a list of analytes 

with less than 70 percent or more than 115 percent recovery 

in water spikes, or with less than 50 percent or more than 

115 percent recovery in sediment spikes. Concentrations 

reported for these analytes in environmental samples could 

be substantially lower than their true concentrations. Analytes 

with overly high spike recovery could have a high bias in 

environmental-sample results, possibly due to laboratory 

contamination. This condition primarily affects acetone in 

water samples analyzed at the USGS NWQL and aluminum 

and mercury in water samples analyzed by the TestAmerica 

Laboratory in Florida. Concentrations were not recoverycorrected, but analytes with exceptionally low or high 

recovery are footnoted in tables within this report.

Table 12. Analytes with less than 70 percent or more than 115 percent recovery in water matrix spikes, or with less than 50 percent or 

more than 115 percent recovery in sediment matrix spikes from the Deepwater Horizon oil spill, Gulf of Mexico, 2010.1

[Abbreviations: mg/L, milligram per liter; P, phosphorus; USGS, U.S. Geological Survey; μg/L, microgram per liter; μg/kg, microgram per kilogram; –, no 

spiked samples or mean recovery greater than 70 percent] 

Analyte Units

USGS National Water Quality Laboratory 

(pre-landfall)

TestAmerica Laboratory, Florida 

(post-landfall)

Number of 

spikes

Mean recovery 

(percent)

Number of 

spike sets

Mean recovery 

(percent)

Water

1,1,2-Trichloro-1,2,2-trifluoroethane μg/L 5 67.9 3 93.0

2,4-Dimethylphenol μg/L – – 5 59.3

3,3'-Dichlorobenzidine μg/L – – 5 19.2

4-Isopropyltoluene μg/L 5 69.3 – –

4-Nitroaniline μg/L – – 5 61.3

4-Nitrophenol μg/L – – 5 68.9

Acetone μg/L 5 134 – –

Aluminum μg/L – – 3 124

Benzo[a]pyrene μg/L – – 5 67.3

Carbon disulfide μg/L 5 63.4 3 88.2

Dichlorodifluoromethane μg/L 5 52.3 3 97.0

Hexachlorobutadiene μg/L 5 60.7 5 74.8

Hexachlorocyclopentadiene μg/L – – 5 53.3

Hexachloroethane μg/L 5 76.7 5 66.2

Mercury μg/L 3 117

n-Butylbenzene μg/L 5 65.6 – –

N-Nitrosodiphenylamine μg/L – – 5 43.4

n-Propylbenzene μg/L 5 67.9 – –

Styrene μg/L 5 61.2 3 88.8

Phosphorus as P mg/L – – 3 52.5

Sediment

1,2,4-Trichlorobenzene μg/kg 4 22.9 – –

1,6-Dimethylnaphthalene μg/kg 4 47.9 – –

2,6-Dimethylnaphthalene μg/kg 4 47.4 – –

2-Ethylnaphthalene μg/kg 4 46.3 – –

Acenaphthylene μg/kg 4 47.0 3 75.7

Naphthalene μg/kg 4 33.7 3 69.0

N-Nitrosodiphenylamine μg/kg – – 3 43.0

Pentachloronitrobenzene μg/kg 4 44.6 – –

1

Environmental samples also were analyzed at the USGS Sediment Chemistry Laboratory and the TestAmerica Laboratories in Colorado and Vermont, but no 

matrix-spike results were reported.
34 Contaminants in Water and Sediment Sampled in Response to the Deepwater Horizon Oil Spill 

Data Censoring

If an analyte cannot be reliably quantified—for example, 

if the measured value is less than the detection level or if 

there is no evidence, such as from mass spectra, that the 

analyte is present—then the analytical result reported by 

the laboratory is censored, that is, reported as less than a 

specified concentration, called a reporting level. In statistical 

terms, this practice results in censored data, which require 

special methods for data analysis. Many constituents were 

not quantified in any environmental sample collected for 

this study. Table 13 lists 114 organic contaminants that were 

censored—that is, not detected—in every water sample, 

and table 14 lists 51 organic contaminants and 3 trace 

elements that were censored in every sediment sample. These 

constituents were excluded from subsequent statistical tests 

and benchmark comparisons. In addition, concentrations of 

some detected analytes in environmental samples were subject 

to post-laboratory censoring on the basis of the QC analysis 

results, as described in the next subsection.

Table 13. Constituents that were not detected in any environmental water samples analyzed from the Deepwater Horizon oil spill, Gulf 

of Mexico, 2010.—Continued

[Abbreviations: BTEX, benzene, toluene, ethylbenzene, xylene and related compounds; CARB, carbon, including petroleum hydrocarbons and hexaneextractable oil and grease; PAH, polycyclic aromatic hydrocarbon, including parent and alkylated compounds; SVOC, semi-volatile organic compound 

(excluding PAHs); TME, trace and major elements; VOC, volatile organic compound; – not analyzed for that time period]

Analytes Chemical class Number of samples less than the reporting level

Pre-landfall Post-landfall

 Organic constituents

1,1,1,2-Tetrachloroethane VOC 60 –

1,1,1-Trichloroethane VOC 62 48

1,1,2,2-Tetrachloroethane VOC 62 48

1,1,2-Trichloro-1,2,2-trifluoroethane VOC 62 48

1,1,2-Trichloroethane VOC 62 48

1,1-Dichloroethane VOC 62 48

1,1-Dichloroethene VOC 62 48

1,1-Dichloropropene VOC 60 –

1,2,3,4-Tetramethylbenzene VOC 60 –

1,2,3,5-Tetramethylbenzene VOC 60 –

1,2,3-Trichlorobenzene VOC 60 –

1,2,3-Trichloropropane VOC 60 –

1,2,3-Trimethylbenzene VOC 60 –

1,2,4-Trichlorobenzene VOC 68 48

1,2,4-Trimethylbenzene VOC 60 –

1,2-Dibromo-3-chloropropane VOC 62 48

1,2-Dibromoethane VOC 62 48

1,2-Dichlorobenzene VOC 68 48

1,2-Dichloroethane VOC 62 48

1,2-Dichloropropane VOC 62 48

1,2-Diphenylhydrazine SVOC 65 –

1,3-Dichlorobenzene VOC 68 48

1,3-Dichloropropane VOC 60 –

1,4-Dichlorobenzene VOC 68 48

2,2-Dichloropropane VOC 60 –

2,4,5-Trichlorophenol SVOC 2 48

2,4,6-Trichlorophenol SVOC 67 48

2,4-Dichlorophenol SVOC 67 48

2,4-Dimethylphenol SVOC 67 48

2,4-Dinitrophenol SVOC 64 48

2,4-Dinitrotoluene VOC 67 48

2-Chloronaphthalene PAH 67 48

2-Chlorophenol SVOC 67 48

2-Chlorotoluene VOC 60 –

2-Methyl-4,6-dinitrophenol SVOC 67 48

Table 13. Constituents that were not detected in any environmental water samples analyzed from the Deepwater Horizon oil spill, Gulf 

of Mexico, 2010.
Results and Discussion 35

Table 13. Constituents that were not detected in any environmental water samples analyzed from the Deepwater Horizon oil spill, Gulf 

of Mexico, 2010.—Continued

[Abbreviations: BTEX, benzene, toluene, ethylbenzene, xylene and related compounds; CARB, carbon, including petroleum hydrocarbons and hexaneextractable oil and grease; PAH, polycyclic aromatic hydrocarbon, including parent and alkylated compounds; SVOC, semi-volatile organic compound 

(excluding PAHs); TME, trace and major elements; VOC, volatile organic compound; – not analyzed for that time period]

Analytes Chemical class Number of samples less than the reporting level

Pre-landfall Post-landfall

 Organic constituents—Continued

2-Methylnaphthalene PAH 2 48

2-Naphthylamine SVOC 2 48

2-Nitrophenol SVOC 67 48

3,3'-Dichlorobenzidine SVOC 67 48

3-Chloropropene VOC 60 –

3-Nitroaniline SVOC 2 48

4-Bromophenyl phenyl ether SVOC 67 48

4-Chloro-3-methylphenol SVOC 67 48

4-Chloroaniline SVOC 2 48

4-Chlorophenyl phenyl ether SVOC 67 48

4-Chlorotoluene VOC 60 –

4-Isopropyltoluene VOC 60 –

4-Nitroaniline SVOC 2 48

4-Nitrophenol SVOC 67 48

Acetone VOC 62 48

Acetophenone SVOC 2 48

Acrylonitrile VOC 60 –

Atrazine SVOC 2 48

Benzaldehyde SVOC 2 48

Benzyl n-butylphthalate PAH 67 48

Biphenyl SVOC 2 48

Bis(2-Chloroisopropyl) ether SVOC 67 48

Bis-2-Chloroethoxymethane VOC 67 48

Bromobenzene VOC 60 –

Bromochloromethane VOC 60 –

Bromodichloromethane VOC 62 48

Bromoethene VOC 60 –

Bromomethane VOC 62 48

Caprolactam SVOC 2 48

Carbazole SVOC 2 48

Chlorobenzene VOC 62 48

Chloroethane VOC 62 48

cis-1,2-Dichloroethene VOC 62 48

cis-1,3-Dichloropropene VOC 62 48

Cyclohexane VOC/BTEX 2 48

Dibenzofuran SVOC 2 48

Dibromochloromethane VOC 62 48

Dichlorodifluoromethane VOC 62 48

Dichloromethane VOC 62 48

Diethyl ether VOC 60 –

Diisopropyl ether VOC 60 –

Dimethyl phthalate VOC 67 48

Ethyl methacrylate VOC 60 –

Ethyl methyl ketone VOC 62 48

Ethylbenzene VOC/BTEX 63 48

Gasoline range organics CARB 1 –

Hexachlorobenzene SVOC 67 48
36 Contaminants in Water and Sediment Sampled in Response to the Deepwater Horizon Oil Spill 

Table 13. Constituents that were not detected in any environmental water samples analyzed from the Deepwater Horizon oil spill, Gulf 

of Mexico, 2010.—Continued

[Abbreviations: BTEX, benzene, toluene, ethylbenzene, xylene and related compounds; CARB, carbon, including petroleum hydrocarbons and hexaneextractable oil and grease; PAH, polycyclic aromatic hydrocarbon, including parent and alkylated compounds; SVOC, semi-volatile organic compound 

(excluding PAHs); TME, trace and major elements; VOC, volatile organic compound; – not analyzed for that time period]

Analytes Chemical class Number of samples less than the reporting level

Pre-landfall Post-landfall

 Organic constituents—Continued

Hexachlorobutadiene VOC 68 48

Hexachlorocyclopentadiene SVOC 67 48

Hexachloroethane VOC 68 48

Iodomethane VOC 60 –

Isobutyl methyl ketone VOC 62 48

Isopropylbenzene VOC/BTEX 62 48

m-plus p-Cresol SVOC 2 48

m-plus p-Xylene VOC 60 –

Methyl acetate VOC 2 48

Methyl acrylate VOC 60 –

Methyl acrylonitrile VOC 60 –

Methyl methacrylate VOC 60 –

Methyl tert-butyl ether VOC 62 48

Methyl tert-pentyl ether VOC 60 –

Methylcyclohexane VOC 2 48

Naphthalene PAH 68 48

n-Butyl methyl ketone VOC 62 48

n-Butylbenzene PAH 60 –

Nitrobenzene SVOC 67 48

N-Nitrosodimethylamine SVOC 65 –

N-Nitrosodi-n-propylamine SVOC 67 48

N-Nitrosodiphenylamine SVOC 67 48

o-Cresol SVOC 2 48

Oil and grease CARB – 48

o-Xylene VOC 60 –

sec-Butylbenzene VOC 60 –

Styrene VOC 62 48

tert-Butyl ethyl ether VOC 60 –

tert-Butylbenzene VOC 60 –

Tetrachloroethene VOC 62 48

Tetrachloromethane VOC 62 48

Tetrahydrofuran VOC 60 –

trans-1,2-dichloroethene VOC 62 48

trans-1,3-dichloropropene VOC 62 48

trans-1,4-Dichloro-2-butene VOC 60 –

Trichloroethene VOC 62 48

Trichlorofluoromethane VOC 62 48

Vinyl chloride VOC 62 48

 Trace and major elements

Antimony TME 2 48

Mercury TME – 48

Silver TME 63 48

Thallium TME 2 48
Results and Discussion 37

Table 14. Constituents that were not detected in any environmental sediment samples analyzed from the Deepwater Horizon oil spill, 

Gulf of Mexico, 2010.—Continued

[Sediment samples are whole sediment unless specified otherwise. Abbreviations: CARB, carbon, including petroleum hydrocarbons and hexane-extractable oil 

and grease; PAH, polycyclic aromatic hydrocarbon; SVOC, semi-volatile organic compound (excluding PAHs); TME, trace and major elements; VOC, volatile 

organic compound; <, less than; – not analyzed for that time period]

Analytes Chemical class Number of samples less than the reporting level

Pre-landfall Post-landfall

Organic constituents

1,2,4-Trichlorobenzene SVOC 68 –

1-Methylfluorene PAH 69 –

2,4,5-Trichlorophenol SVOC – 48

2,4,6-Trichlorophenol SVOC – 48

2,4-Dichlorophenol SVOC – 48

2,4-Dimethylphenol SVOC – 48

2,4-Dinitrophenol SVOC – 48

2,4-Dinitrotoluene SVOC – 48

2,6-Dinitrotoluene SVOC – 48

2-Chloronaphthalene PAH – 48

2-Chlorophenol SVOC – 48

2-Methyl-4,6-dinitrophenol SVOC – 48

2-Methylanthracene PAH 69 –

2-Naphthylamine PAH – 48

2-Nitrophenol SVOC – 48

3,3'-Dichlorobenzidine SVOC – 48

3-Nitroaniline SVOC – 48

4-Bromophenyl phenyl ether SVOC – 48

4-Chloro-3-methylphenol SVOC – 48

4-Chloroaniline SVOC – 48

4-Chlorophenyl phenyl ether SVOC – 48

4-Nitroaniline SVOC – 48

4-Nitrophenol SVOC – 48

Acetophenone SVOC – 48

Atrazine SVOC – 48

Benzaldehyde SVOC – 48

Benzyl n-butylphthalate SVOC – 48

Bis(2-Chloro-1-methylethyl) ether SVOC – 48

Bis(2-Chloroethoxy)methane SVOC – 48

Bis(2-Chloroethyl) ether SVOC – 48

Caprolactam SVOC – 48

Dibenzofuran SVOC – 48

Diesel range organics (C10-C36) CARB 2 –

Diethylphthalate SVOC 69 48

Dimethylphthalate SVOC – 48

Di-n-butyl phthalate SVOC – 48

Di-n-octyl phthalate SVOC – 48

Hexachlorobenzene SVOC 69 48

Hexachlorobutadiene VOC – 48

Hexachlorocyclopentadiene SVOC – 48

Hexachloroethane SVOC – 48

Isophorone SVOC – 48

m-plus p-Cresol SVOC – 48

Nitrobenzene SVOC – 48

Table 14. Constituents that were not detected in any environmental sediment samples analyzed from the Deepwater Horizon oil spill, 

Gulf of Mexico, 2010.
38 Contaminants in Water and Sediment Sampled in Response to the Deepwater Horizon Oil Spill 

Censoring on the Basis of Quality-Control Results

For analytes detected in laboratory, field, or trip blanks, 

concentrations in environmental samples were censored at 

raised censoring levels on the basis of guidance from the 

U.S. Environmental Protection Agency (1989, pages 16–17 

in chapter 5). Field and trip blanks were available for water 

samples only, and laboratory reagent blanks were available for 

both water and sediment. For analytes detected in these blanks, 

a raised censoring level equal to five times the maximum 

concentration detected in the blanks was applied to results in 

any associated environmental samples. This raised censoring 

level ensures that a reported detection has a high probability 

of reflecting the actual concentration in the environmental 

sample, rather than the effect of incidental contamination from 

sampling and analysis procedures. Quantified results less than 

this raised censoring level were changed to censored values 

and reported as less than the quantified value. For example, 

naphthalene was detected in a post-landfall field blank, so 

was censored at a raised censoring level of 0.8. A quantified 

result of 0.5 would be censored to less than 0.5, indicating that 

the environmental contaminant concentration in that sample 

is no more than 0.5, but it could be less. For a few common 

laboratory contaminants—acetone, dichloromethane, diethyl 

phthalate, methyl ethyl ketone, and toluene—the censoring 

level was raised to 10 times the maximum concentration 

detected in the blank. 

Four organic contaminants in sediment, four trace 

or major elements in water, and two nutrients in water 

had one or more detections in laboratory reagent blanks. 

Concentrations in all environmental samples, however, 

were more than five times the reagent blank concentration, 

except for the two nutrients in water—ammonia plus organic 

nitrogen and phosphorus. Because a reagent blank sample 

is associated with a particular set of environmental samples, 

censoring for reagent-blank contamination was applied only 

to those environmental samples that had contamination in the 

associated reagent blank. Therefore, results for ammonia plus 

organic nitrogen were censored in 8 of the 48 post-landfall 

water samples, and phosphorus was censored in 26 of the 

48 post-landfall water samples and in 15 of the 68 pre-landfall 

water samples.

In this study, it was not possible to associate a particular 

field blank with each environmental sample, so an alternative 

procedure had to be used to estimate potential contamination. 

One option was to determine the statistical distribution of 

concentrations in a set of representative blanks and assume 

this same distribution applied to potential contamination in the 

environmental samples (Mueller and Titus, 2005; Apodaca and 

others, 2006). This procedure requires more than 20 blanks to 

estimate the 90th percentile of this distribution with reasonable 

confidence. Using the six blanks available for this study, 

only the lower 60th to 70th percentile of this distribution can 

be estimated; therefore, this approach could underestimate 

the extent of contamination in environmental samples. In 

the present study, the most conservative approach was used, 

which assumes that contamination identified in any field or 

trip blank could occur in all environmental samples collected 

during the same sampling period. Although this approach 

can overestimate the extent of incidental contamination, no 

other procedure would ensure that this extent would not be 

underestimated. Therefore, detection of an analyte in any field 

or trip blank resulted in the censoring of concentrations of that 

analyte in all environmental samples collected during the same 

sampling period.

Table 14. Constituents that were not detected in any environmental sediment samples analyzed from the Deepwater Horizon oil spill, 

Gulf of Mexico, 2010.—Continued

[Sediment samples are whole sediment unless specified otherwise. Abbreviations: CARB, carbon, including petroleum hydrocarbons and hexane-extractable oil 

and grease; PAH, polycyclic aromatic hydrocarbon; SVOC, semi-volatile organic compound (excluding PAHs); TME, trace and major elements; VOC, volatile 

organic compound; <, less than; – not analyzed for that time period]

Analytes Chemical class Number of samples less than the reporting level

Pre-landfall Post-landfall

 Organic constituents—Continued

N-Nitrosodi-n-propylamine SVOC – 48

N-Nitrosodiphenylamine SVOC – 48

o-Cresol SVOC – 48

Pentachloroanisole SVOC 69 –

Pentachloronitrobenzene SVOC 69 –

Pentachlorophenol SVOC – 48

Phenanthridine SVOC 69 –

Phenol SVOC – 48

 Trace and major elements

Thallium, in <63-micrometer sediment TME 63 37

Thallium TME 70 49

Uranium TME 70 49
Results and Discussion 39

The results for 19 constituents in water were affected by 

censoring on the basis of contamination in laboratory, field, 

and trip blanks, as shown in table 15. Nine organic compounds 

and two trace elements were left with no detections in either 

sampling period after blank-censoring. Four additional organic 

compounds were left with no detections in the pre-landfall 

period; benzene and ammonia plus organic nitrogen were 

left with no detections in the post-landfall period. Four other 

constituents were censored to some extent, although some 

results still were quantified; two of these constituents were 

left with only one quantified value during the post-landfall 

period. Overall, 236 results out of a total of 1,189 results 

for the 19 constituents in table 15 were censored because of 

contamination in laboratory blanks (49 results) or field and trip 

blanks (187 results); however, 80 percent of these censored 

results were for only 5 constituents: toluene, ammonia plus 

organic nitrogen, mercury, organic carbon, and phosphorus. 

Determination of Common Censoring Thresholds

Although the PPW test can be used with data censored at 

multiple reporting levels, it requires that the different reporting 

levels be randomly distributed between the two sample groups 

being compared. In this study, however, there were systematic 

differences in reporting levels between pre-landfall and postlandfall samples, especially for analytes that were determined 

by using different methods, by different laboratories, or both, 

for the two sampling periods (appendixes 1, 2). Therefore, all 

data for a given contaminant were censored to an “optimal” 

censoring threshold prior to statistical analysis, which is 

described in the next paragraph. For example, acenaphthene 

in sediment has an optimal censoring threshold of 0.36 

micrograms per kilogram (μg/kg). Reported concentrations 

of 0.4, 0.2, and less than 1 μg/kg would be equivalent after 

censoring, respectively, to 0.4 μg/kg, less than 0.36 μg/kg, 

and indeterminate, which is defined in the next paragraph. 

Two-sided PPW tests were performed, and the sign of the test 

statistic indicated whether pre-landfall concentrations were 

higher than post-landfall concentrations or vice versa. 

An optimal censoring threshold was computed for 

each analyte for which data were censored for one or more 

of the 96 samples in the paired-sample dataset, which 

consists of primary samples for sites sampled during both 

the pre-landfall and post-landfall periods. Many analytes 

had a wide range of reporting levels—one to three orders 

of magnitude. Selection of an optimal censoring threshold 

balanced two competing objectives: to include as many 

quantified detections as possible, but also to minimize the 

number of “indeterminate” samples. An indeterminate sample 

is defined as a sample with censored data—that is, reported 

less than a specified reporting level—for which the specified 

reporting level is higher than the applied censoring threshold, 

so the sample cannot be classified as either a detection or 

nondetection at that threshold. As an example, censored data 

for acenaphthene in sediment ranged from less than 0.2 to 

less than 19 μg/kg, and quantified detections ranged from 

0.34 to 2.1 μg/kg. If acenaphthene data are censored at the 

lowest possible censoring threshold of 0.2, then any censored 

value with a higher reporting threshold (for example, from 

less than 0.22 to less than 19 μg/kg) must be considered 

as indeterminate because we do not know whether the 

acenaphthene concentration is less than 0.2 or greater than 

or equal to 0.2 μg/kg. On the other hand, if we censor at the 

highest threshold of 19 μg/kg, then all samples with a detected 

concentration less than 19 μg/kg—in this case, all of the 

reported detections—become censored, reported as less than 

19 μg/kg. The optimal censoring threshold was operationally 

defined as the lowest censoring level that converted no more 

than 5 percent of results from censored to indeterminate 

values, maximized the number of quantifiable detections, 

and if possible also minimized the number of indeterminate 

values. Because the optimal censoring threshold was designed 

for comparison of pre-landfall to post-landfall samples, it was 

determined by using the paired-sample dataset. For practical 

reasons, the maximum limit allowed for indeterminate values 

was raised slightly for some analytes that were determined in 

substantially fewer than the 96 samples typical of the pairedsample dataset, because it was difficult to meet the 5 percent 

maximum indeterminate value requirement and still preserve 

detections. Therefore, up to 7 percent indeterminate values 

were allowed for trace and major elements in the less than 

63-μm sediment fraction, for which there were only about 

70 samples, and up to 8 percent for selected analytes measured 

only during one sampling period, for which there were up to 

48 samples. 

The procedure for calculating the optimal censoring 

threshold for comparison of pre-landfall to post-landfall 

samples for a given analyte is illustrated for acenaphthene 

in sediment in figure 3. The x-axis shows possible censoring 

threshold concentrations for acenaphthene, which consist of all 

the reporting levels for censored samples. For acenaphthene, 

there are 94 samples, of which nine are quantified values. 

All of the observed reporting levels, from 0.2 to 19 μg/

kg, were considered as possible censoring thresholds for 

this analyte, and each is represented in figure 3 with a gray 

bar showing the percentage of quantified values that would 

be “detections” if data were censored at that censoring 

threshold, except for 19 μg/kg, which is off the x-axis scale. 

The blue bars represent the percentage of samples that would 

be indeterminate at that threshold concentration because 

their reporting levels exceed the censoring threshold. The 

highest censoring threshold at which all 9 quantified values 

would still be “detections” after censoring would be 0.34. 
40 Contaminants in Water and Sediment Sampled in Response to the Deepwater Horizon Oil Spill Table 15. Constituents analyzed in water that were affected by censoring because of contamination detected in laboratory, field, and trip blanks from the Deepwater Horizon oil spill, Gulf of Mexico, 2010.

[Abbreviations: BTEX, benzene, toluene, ethylbenzene, xylene and related compounds; CARB, carbon, including petroleum hydrocarbons and hexane-extractable oil and grease; NUTR, nutrient; PAH, polycyclic aromatic hydrocarbon; post, post-landfall; pre, pre-landfall; TME, trace and major elements; VOC, volatile organic compound; –, not fully censored]

Analyte Chemical class Sampling period Samples

Results after laboratory-blank censoring Results after field and trip-blank censoring

Quantified 

results

Detection 

frequency

(percent)

Samples 

censored due 

to blanks

Quantified 

results

Detection 

frequency

(percent)

100 percent 

censored1

 Organic contaminants

1,2,3,5-Tetramethyl-benzene VOC Pre 60 1 2 1 0 0 Yes2

1,2,3-Trimethyl-benzene VOC Pre 60 2 3 2 0 0 Yes21,2,4-Trimethyl-benzene VOC Pre 60 3 5 3 0 0 Yes2Acetone VOC Pre 62 5 8 5 0 0 Yes3Benzene VOC/BTEX Post 48 3 6 3 0 0 Post only

Dichloromethane VOC Pre 62 3 5 3 0 0 Yes

Dichloromethane VOC Post 48 4 8 4 0 0 Yes

Dissolved organic carbon CARB Pre 62 62 100 41 21 34 –

Diesel range organics CARB Post 48 6 13 5 1 2 –

Ethylbenzene VOC/BTEX Pre 63 3 5 3 0 0 Yes3

Naphthalene PAH Post 48 1 2 1 0 0 Yes3Toluene VOC/BTEX Pre 63 15 24 15 0 0 Pre only

Trichloromethane VOC Pre 62 3 5 3 0 0 Pre only

Xylene, meta plus para VOC/BTEX Pre 60 4 7 4 0 0 Yes2

Xylene, ortho VOC/BTEX Pre 60 3 5 3 0 0 Yes2

 Trace and major elements, and nutrients in water

Ammonia plus organic 

nitrogen as N

NUTR Post 48 440 83 40 0 0 Post only

Copper TME Post 48 22 46 3 19 40 –

Mercury TME Post 48 23 48 23 0 0 Yes2

Phosphorus as P NUTR Post 48 422 46 21 1 2 –

Phosphorus as P NUTR Pre 68 453 78 0 53 78 –Silver TME Pre 63 4 6 4 0 0 Yes3

1Lists analytes that are 100 percent censored (no detections remaining) after blank-censoring. Post only, detected in pre-landfall samples; pre only, detected in post-landfall samples.2Data available only for one sampling period.3Not detected (without blank-censoring) in the other sampling period.4Because of laboratory-blank contamination, results were censored for ammonia plus organic nitrogen in 8 of 48 post-landfall samples, phosphorus in 26 of 48 post-landfall samples, and phosphorus in 15 of 

68 pre-landfall samples.
Results and Discussion 41

0 

10 

20 

30 

40 

50 

60 

70 

80 

90 

100 

0.2 0.3 0.4 0.5 0.8 0.9 1.0 1.1 

POSSIBLE CENSORING THRESHOLD, IN MICROGRAMS PER KILOGRAM 

EXPLANATION 

ACENAPHTHENE IN SEDIMENT, IN PERCENT 

Quantified values preserved,

 in percent

Indeterminate values,

 in percent

5% (Maximum allowed indeterminate) 

sac12-0452_Figure 03

Figure 3. The effect of censoring threshold on the percentages of quantified values that are retained (gray bars) and 

indeterminate values (blue bars) for an example contaminant from the Deepwater Horizon oil spill, Gulf of Mexico, 2010: 

acenaphthene in sediment.

At a censoring threshold of 0.34, however, 6 percent of 

samples would be considered indeterminate because their 

reporting levels exceed 0.34. The maximum allowable limit 

for indeterminate samples is 5 percent, which is shown as the 

red line in figure 3, so a censoring threshold of 0.34 would not 

be acceptable. The lowest censoring threshold that meets the 

maximum indeterminate sample requirement is 0.35, which 

corresponds to 5 percent indeterminate samples. Raising 

the censoring threshold slightly to 0.36, however, would 

decrease the percentage of indeterminate samples slightly, to 

4 percent, without censoring any quantified values. Increasing 

the censoring threshold again, such as to 0.40, would further 

reduce the indeterminate samples to 3 percent, but it also 

would result in loss of one more detection. The optimal 

censoring threshold selected was 0.36, which minimized the 

indeterminate samples and maximized quantifiable detections, 

while meeting the less than or equal to 5 percent criterion for 

maximum indeterminate samples. 

Optimal censoring thresholds are shown in table 16

for individual analytes with at least 38 samples. Detection 

frequencies were calculated for each analyte at its optimal 

censoring threshold so that pre-landfall and post-landfall 

samples can be compared at a common detection threshold. 

Also, contaminant concentrations were censored at the optimal 

censoring threshold prior to statistical comparisons between 

sampling periods. 

For all analytes of the same contaminant class and 

sampling medium, detection frequencies also were computed 

by using four common detection thresholds that allowed 

comparison among analytes with different MDLs. A range of 

common thresholds was used because the lower thresholds 

preserve more of the low-level quantified values, whereas higher 

thresholds allowed comparisons among a greater number of 

analytes. The four detection thresholds for a given contaminant 

class and sampling medium correspond to the 10th, 25th, 50th, 

and 70th percentiles in the distribution of optimal censoring 

thresholds for that contaminant type and sampling medium. 
42 Contaminants in Water and Sediment Sampled in Response to the Deepwater Horizon Oil Spill Table 16A. Optimal censoring thresholds and sample counts from the Deepwater Horizon oil spill, Gulf of Mexico, 2010: organic contaminants in water.—Continued

[Abbreviations: A, constituent was analyzed in samples from only one sampling period; B, constituent was not detected in any samples after blank censoring; BTEX, benzene, toluene, ethylbenzene, xylene and related compounds; C, constituent was not detected in paired-sample dataset; CARB, carbon, including petroleum hydrocarbons and hexane-extractable oil and grease; D, constituent was not detected in any samples after optimal censoring threshold was applied; F(x), field blank affected all samples collected during sampling period x; Lab, laboratory; na, not applicable; nc, not censored at optimal censoring threshold because no quantified detections remained after blank censoring; PAH, polycyclic aromatic hydrocarbon; post, post-landfall; PPW, paired Prentice-Wilcoxon; pre, pre-landfall; SVOC, semi-volatile organic compound (excluding PAHs); T(x), trip blank affected all samples collected during sampling period x; VOC, volatile organic compound; μg/L, microgram per liter; mg/L, milligram per liter; –, not detected in any blanks; <, less than]

Analyte Chemical class

Type of 

blank with 

contamination 

(sampling 

period)1

Optimal 

censoring 

threshold2

Units

Before censoring After censoring at optimal threshold

PPW test 

performed

Reason no 

PPW test 

was run

Number of 

samples 

with data

Number of 

quantified 

values that 

were censored

Number of 

censored values 

that are 

indeterminate3

1,2,3,5-Tetramethyl-benzene VOC F(pre) nc μg/L 38 na na No A,B

1,2,3-Trimethylbenzene VOC F(pre) nc μg/L 38 na na No A,B

1,2,4-Trimethylbenzene VOC F(pre) nc μg/L 38 na na No A,B

1,3,5-Trimethylbenzene VOC – 0.064 μg/L 38 1 0 No

A

2,6-Dinitrotoluene VOC – 2.3 μg/L 92 0 4 No

C

2-Ethyltoluene VOC – 0.064 μg/L 38 1 0 No

A

Acenaphthene PAH – 0.28 μg/L 93 1 0 No

D

Acenaphthylene PAH – 0.3 μg/L 93 1 0 No

D

Acetone VOC F(pre) nc μg/L 87 na na No

B

Anthracene PAH – 0.39 μg/L 93 1 0 No

D

Benzene VOC/BTEX T(post) 0.34 μg/L 88 3 3 No

D

Benzo[a]anthracene PAH – 0.26 μg/L 93 1 0 Yes na

Benzo[a]pyrene PAH – 0.33 μg/L 93 1 0 Yes na

Benzo[b]fluoranthene PAH – 0.3 μg/L 93 2 0 Yes na

Benzo[ghi]perylene PAH – 0.38 μg/L 43 0 0 No

A

Benzo[k]fluoranthene PAH – 0.4 μg/L 92 0 4 No

C

Bis(2-chloroethyl)ether SVOC – 2.1 μg/L 92 0 4 No

C

Bis(2-ethylhexyl) phthalate SVOC – 7.4 μg/L 93 1 4 Yes na

Carbon disulfide VOC – 0.5 μg/L 84 1 0 Yes na

Chloromethane VOC – 0.53 μg/L 85 1 0 No

D

Chrysene PAH – 0.33 μg/L 93 2 1 Yes na

Dibenzo[a,h]anthracene PAH – 0.42 μg/L 92 0 0 No

C

Dibromomethane VOC – 0.1 μg/L 38 0 0 No A,C

Dichloromethane VOC F(pre), T(post) nc μg/L 88 na na No

B

Diesel range organics CARB F(post) 73 μg/L 47 0 2 No

A

Diethyl phthalate SVOC F(post) 0.61 μg/L 93 1 0 No

D

Di-n-butyl phthalate SVOC – 2 μg/L 93 3 0 No

D

Di-n-octyl phthalate SVOC – 0.6 μg/L 92 0 0 No

C

Dissolved organic carbon CARB Lab 3 mg/L 87 25 4 Yes na

Ethylbenzene VOC/BTEX F(pre) nc μg/L 88 na na No

B

Fluoranthene PAH – 0.3 μg/L 93 3 0 No

D

Fluorene PAH – 0.33 μg/L 93 1 0 No

D

Table 16A. Optimal censoring thresholds and sample counts from the Deepwater Horizon oil spill, Gulf of Mexico, 2010: organic contaminants in water.
Results and Discussion 43

Table 16A. Optimal censoring thresholds and sample counts from the Deepwater Horizon oil spill, Gulf of Mexico, 2010: organic contaminants in water.—Continued[Abbreviations: A, constituent was analyzed in samples from only one sampling period; B, constituent was not detected in any samples after blank censoring; BTEX, benzene, toluene, ethylbenzene, xylene and related compounds; C, constituent was not detected in paired-sample dataset; CARB, carbon, including petroleum hydrocarbons and hexane-extractable oil and grease; D, constituent was not detected in any samples after optimal censoring threshold was applied; F(x), field blank affected all samples collected during sampling period x; Lab, laboratory; na, not applicable; nc, not censored at optimal censoring threshold because no quantified detections remained after blank censoring; PAH, polycyclic aromatic hydrocarbon; post, post-landfall; PPW, paired Prentice-Wilcoxon; pre, pre-landfall; SVOC, semi-volatile organic compound (excluding PAHs); T(x), trip blank affected all samples collected during sampling period x; VOC, volatile organic compound; μg/L, microgram per liter; mg/L, milligram per liter; –, not detected in any blanks; <, less than]

Analyte Chemical class

Type of 

blank with 

contamination 

(sampling 

period)1

Optimal 

censoring 

threshold2

Units

Before censoring After censoring at optimal threshold

PPW test 

performed

Reason no 

PPW test 

was run

Number of 

samples 

with data

Number of 

quantified 

values that 

were censored

Number of 

censored values 

that are 

indeterminate3

Gasoline range organics (C6-C10) CARB – 50 μg/L 49 1 0 No A

Indeno(1,2,3-cd)pyrene PAH – 0.38 μg/L 92 0 0 No C

Isophorone SVOC – 0.61 μg/L 93 10 5 No D

Naphthalene PAH F(pre, post) nc μg/L 94 na na No Bn-Propylbenzene VOC – 0.072 μg/L 38 0 0 No A

Oil range organics (C28-C35) CARB – 46 μg/L 47 0 4 No A

Organics (C8-C36) CARB – 47 μg/L 47 0 3 No A

Pentachlorophenol SVOC – 3.1 μg/L 93 1 1 No D

Phenanthrene PAH – 0.32 μg/L 93 1 0 No D

Phenol SVOC – 1.5 μg/L 93 2 1 No D

Pyrene PAH – 0.35 μg/L 93 3 0 No D

Toluene VOC/BTEX F(pre) 0.7 μg/L 88 0 0 Yes na

Tribromomethane VOC – 0.6 μg/L 88 1 0 No D

Trichloromethane VOC F(pre) 0.6 μg/L 88 0 0 Yes na

Xylene, ortho VOC/BTEX F(pre) nc μg/L 39 na na No A,B

Xylenes, meta and para VOC/BTEX F(pre) nc μg/L 39 na na No A,B

Xylenes, total VOC/BTEX – 1.6 μg/L 88 1 0 Yes na
44 Contaminants in Water and Sediment Sampled in Response to the Deepwater Horizon Oil Spill Table 16B. Optimal censoring thresholds and sample counts from the Deepwater Horizon oil spill, Gulf of Mexico, 2010: organic contaminants in whole sediment.—Continued

[Abbreviations: A, constituent was analyzed in samples from only one sampling period; B, constituent was not detected in any samples after optimal censoring threshold was applied; CARB, carbon, including petroleum hydrocarbons and hexane-extractable oil and grease; Lab, laboratory; na, not applicable; PAH, polycyclic aromatic hydrocarbon; PPW, paired Prentice-Wilcoxon; SVOC, semi-volatile organic compound (excluding PAHs); μg/kg, microgram per kilogram; mg/kg, milligram per kilogram; –, not detected in any blanks; <, less than]

Analyte Chemical class

Type of 

blank with 

contamination 

(sampling 

period)1

Optimal 

censoring 

threshold2

Units

Before censoring After censoring at optimal threshold

PPW test 

performed

Reason no 

PPW test 

was run

Number of 

samples 

with data

Number of 

quantified 

values that 

were censored

Number of 

censored values 

that are 

indeterminate3

1,2-Dimethyl-naphthalene PAH – 90 μg/kg 48 1 4 No

A

1,6-Dimethyl-naphthalene SVOC – 90 μg/kg 48 1 4 No

A

1-Methylnaphthalene PAH – 0.4 μg/kg 93 2 4 Yes na

1-Methylphenanthrene PAH – 0.38 μg/kg 94 1 2 Yes na

1-Methylpyrene PAH – 90 μg/kg 48 1 4 No

A

2,3,5-Trimethyl-naphthalene PAH – 0.27 μg/kg 47 0 3 No

A

2,3,6-Trimethyl-naphthalene PAH – 90 μg/kg 48 1 4 No

A

2,6-Dimethyl-naphthalene PAH – 0.47 μg/kg 94 1 2 Yes na

2-Ethylnaphthalene PAH – 90 μg/kg 48 2 4 No

A

2-Methylnaphthalene PAH – 0.53 μg/kg 93 2 2 Yes na

4H-Cyclopenta[d,e,f]-phenanthrene PAH – 90 μg/kg 48 2 4 No

A

9,10-Anthraquinone SVOC – 80 μg/kg 45 3 4 No

A

Acenaphthene PAH – 0.36 μg/kg 94 1 4 Yes na

Acenaphthylene PAH – 0.38 μg/kg 94 2 2 Yes na

Anthracene PAH – 0.38 μg/kg 94 0 1 Yes na

Benzo[a]anthracene PAH – 0.25 μg/kg 94 0 3 Yes na

Benzo[a]pyrene PAH – 0.25 μg/kg 94 2 3 Yes na

Benzo[b]fluoranthene PAH – 0.23 μg/kg 94 1 0 Yes na

Benzo[e]pyrene PAH – 0.38 μg/kg 94 0 2 Yes na

Benzo[ghi]perylene PAH Lab 0.25 μg/kg 94 0 3 Yes na

Benzo[k]fluoranthene PAH – 0.4 μg/kg 94 1 1 Yes na

Biphenyl SVOC – 0.47 μg/kg 93 0 2 Yes na

Bis(2-ethylhexyl) phthalate SVOC – 80 μg/kg 94 0 4 Yes na

C1 Chrysene PAH – 1.5 μg/kg 93 0 1 Yes na

C1 Dibenzothiophenes PAH – 1 μg/kg 93 0 4 Yes na

C1 Fluoranthenes/pyrenes PAH – 0.91 μg/kg 93 0 4 Yes na

C1 Fluorenes PAH – 1.5 μg/kg 93 0 2 Yes na

C1 Naphthalenes PAH – 1.3 μg/kg 93 0 4 Yes na

C1 Phenanthrenes/anthracenes PAH – 1.5 μg/kg 93 2 1 Yes na

C2 Chrysenes PAH – 1 μg/kg 93 0 4 Yes na

C2 Dibenzothiophenes PAH – 1 μg/kg 93 2 4 Yes na

C2 Fluoranthenes/pyrenes PAH – 1.3 μg/kg 93 2 3 Yes na

C2 Fluorenes PAH – 1.3 μg/kg 93 0 4 Yes na

C2 Naphthalenes PAH – 0.91 μg/kg 93 0 2 Yes na

C2 Phenanthrenes/anthracenes PAH – 1 μg/kg 93 0 4 Yes na

Table 16B. Optimal censoring thresholds and sample counts from the Deepwater Horizon oil spill, Gulf of Mexico, 2010: organic contaminants in whole sediment.
Results and Discussion 45

Table 16B. Optimal censoring thresholds and sample counts from the Deepwater Horizon oil spill, Gulf of Mexico, 2010: organic contaminants in whole sediment.—Continued[Abbreviations: A, constituent was analyzed in samples from only one sampling period; B, constituent was not detected in any samples after optimal censoring threshold was applied; CARB, carbon, including petroleum hydrocarbons and hexane-extractable oil and grease; Lab, laboratory; na, not applicable; PAH, polycyclic aromatic hydrocarbon; PPW, paired Prentice-Wilcoxon; SVOC, semi-volatile organic compound (excluding PAHs); μg/kg, microgram per kilogram; mg/kg, milligram per kilogram; –, not detected in any blanks; <, less than]

Analyte Chemical class

Type of 

blank with 

contamination 

(sampling 

period)1

Optimal 

censoring 

threshold2

Units

Before censoring After censoring at optimal threshold

PPW test 

performed

Reason no 

PPW test 

was run

Number of 

samples 

with data

Number of 

quantified 

values that 

were censored

Number of 

censored values 

that are 

indeterminate3

C3 Chrysenes PAH – 1 μg/kg 93 0 4 Yes na

C3 Dibenzothiophenes PAH – 1 μg/kg 93 1 4 Yes na

C3 Fluoranthenes/pyrenes PAH – 1.5 μg/kg 93 0 1 Yes na

C3 Fluorenes PAH – 1.8 μg/kg 93 0 1 Yes na

C3 Naphthalenes PAH – 0.91 μg/kg 93 0 2 Yes na

C3 Phenanthrenes/qnthracenes PAH – 1 μg/kg 93 1 4 Yes na

C4 Chrysenes PAH – 1.3 μg/kg 93 2 4 Yes na

C4 Dibenzothiophenes PAH – 1.8 μg/kg 93 3 1 Yes na

C4 Naphthalenes PAH – 1.2 μg/kg 93 0 4 Yes na

C4 Phenanthrenes/anthracenes PAH – 1.3 μg/kg 93 0 3 Yes na

Carbazole SVOC – 80 μg/kg 91 4 5 No BChrysene PAH – 0.23 μg/kg 94 1 0 Yes na

Dibenzo[ah]anthracene PAH – 0.38 μg/kg 94 1 3 Yes na

Dibenzothiophene SVOC – 0.38 μg/kg 94 1 2 Yes naFluoranthene PAH – 0.26 μg/kg 94 0 0 Yes naFluorene PAH – 0.44 μg/kg 94 1 3 Yes naIndeno[123cd]pyrene PAH Lab 0.23 μg/kg 94 0 1 Yes naNaphthalene PAH – 0.29 μg/kg 94 6 5 Yes naOil and grease CARB Lab 110 mg/kg 94 16 2 Yes na

Perylene PAH Lab 0.22 μg/kg 94 0 5 Yes na

Petroleum hydrocarbons CARB – 340 mg/kg 46 1 4 No na

Phenanthrene PAH – 0.23 μg/kg 94 2 2 Yes na

Pyrene PAH – 0.24 μg/kg 94 0 1 Yes na

Total organic carbon CARB – 0.1 percent 93 0 0 Yes na

Total organic carbon CARB – 1100 mg/kg 46 0 4 No A

1In affected samples, reported concentrations were censored at five times the maximum concentration detected in the corresponding laboratory blank. 2Lowest censoring level that maximizes the number of quantifiable detections, minimizes the number of indeterminate samples, and for which the percent indeterminate samples is no more than 5 to 8 

percent, depending on sample size.

3Indeterminate samples are censored data for which the reporting level (for example, <1) is higher than the applied censoring threshold (for example, 0.2), so it cannot be classified as either a detection or 

nondetection at that threshold (for example, it is unknown whether the contaminant is present at levels above 0.2).
46 Contaminants in Water and Sediment Sampled in Response to the Deepwater Horizon Oil Spill Table 16C. Optimal censoring thresholds and sample counts from the Deepwater Horizon oil spill, Gulf of Mexico, 2010: trace and major elements and nutrients in water. —Continued

[Abbreviations: A, constituent was not detected in any samples after optimal censoring threshold was applied; B, constituent was analyzed in samples from only one sampling period; C, constituent was not detected in any samples after blank censoring; F(x), field blank affected all samples collected during sampling period x; Lab, laboratory; na, not applicable; nc, data not censored; NUTR; nutrient; post, post-landfall; PPW, paired Prentice-Wilcoxon; pre, pre-landfall; TME, trace and major element; μg/L, microgram per liter; mg/L, milligram per liter; na, not applicable; nc, not censored; –, not detected in any blanks; <, less than]

Analyte Symbol or abbreviation Chemical class

Type of 

blank with 

contamination 

(sampling period)1

Optimal 

censoring 

threshold2

Units

Before censoring After censoring at optimal threshold

PPW test 

performed

Reason no 

PPW test 

was run

Number of 

samples 

with data

Number of 

quantified values 

that were 

censored

Number of 

censored 

values that are 

indeterminate3

Aluminum Al TME – 400 μg/L 88 12 3 Yes na

Ammonia as N N (ammonia) NUTR – 0.04 mg/L 91 14 0 Yes na

Ammonia as NH4 N (ammonium) NUTR – 0.0515 mg/L 91 14 0 Yes na

Ammonia plus organic nitrogen N (Kjeldahl) NUTR Lab, F(post) 2.4 mg/L 93 46 5 No

A

Arsenic As TME F(pre) 40 μg/L 80 39 0 No

A

Barium Ba TME – nc4 μg/L 80 na na Yes na

Beryllium Be TME – 10 μg/L 80 4 0 No

A

Boron

B TME Lab, F(post) nc4 μg/L 42 na na No

B

Cadmium Cd TME – 10 μg/L 80 3 0 No

A

Calcium Ca TME Lab, 

F(pre, post)

nc4 mg/L 86 na na Yes na

Chromium Cr TME – 20 μg/L 80 20 0 Yes na

Cobalt Co TME – 30 μg/L 80 26 0 No

A

Copper Cu TME F(post) 38 μg/L 80 17 0 No

A

Dissolved nitrogen N (total) NUTR – nc4 mg/L 86 na na Yes na

Iron Fe TME – 500 μg/L 80 17 0 Yes na

Lead Pb TME – 20 μg/L 80 20 0 Yes na

Lithium Li TME F(pre) nc4 μg/L 39 na na No

B

Magnesium Mg TME Lab, 

F(pre, post)

nc4 mg/L 86 na na Yes na

Manganese Mn TME – 10 μg/L 80 5 5 Yes na

Mercury Hg TME F(post) nc5 μg/L 40 na na No B,C

Molybdenum Mo TME – 20 μg/L 80 52 0 Yes na

Nickel Ni TME – 75 μg/L 80 22 0 No

A

Organic nitrogen N (organic) NUTR – 2.4 mg/L 91 33 4 Yes na

Phosphorus as P

P NUTR Lab, F(post) 0.18 mg/L 94 29 4 Yes na

Table 16C. Optimal censoring thresholds and sample counts from the Deepwater Horizon oil spill, Gulf of Mexico, 2010: trace and major elements and nutrients in water.
Results and Discussion 47

Table 16C. Optimal censoring thresholds and sample counts from the Deepwater Horizon oil spill, Gulf of Mexico, 2010: trace and major elements and nutrients in water.

—Continued

[Abbreviations: A, constituent was not detected in any samples after optimal censoring threshold was applied; B, constituent was analyzed in samples from only one sampling period; C, constituent was not detected in any samples after blank censoring; F(x), field blank affected all samples collected during sampling period x; Lab, laboratory; na, not applicable; nc, data not censored; NUTR; nutrient; post, post-landfall; PPW, paired Prentice-Wilcoxon; pre, pre-landfall; TME, trace and major element; μg/L, microgram per liter; mg/L, milligram per liter; na, not applicable; nc, not censored; –, not detected in any blanks; <, less than]

Analyte Symbol or abbreviation Chemical class

Type of 

blank with 

contamination 

(sampling period)1

Optimal 

censoring 

threshold2

Units

Before censoring After censoring at optimal threshold

PPW test 

performed

Reason no 

PPW test 

was run

Number of 

samples 

with data

Number of 

quantified values 

that were 

censored

Number of 

censored 

values that are 

indeterminate3

Potassium K TME Lab, F(post) nc4 mg/L 86 na na Yes na

Selenium Se TME – 40 μg/L 80 15 0 No A

Silver Ag TME F(pre) nc5 μg/L 80 na na No C

Sodium Na TME Lab, 

F(pre, post)

nc4 mg/L 86 na na Yes na

Strontium Sr TME – nc4 μg/L 39 na na No B

Vanadium V TME – 20 μg/L 42 na na No B

Zinc Zn TME – 80 μg/L 80 12 0 Yes na

1For constituents detected in one or more laboratory-, field- or trip-blank samples, reported concentrations were censored at five times the concentration in the corresponding laboratory blank, or at five times 

the maximum concentration detected in field or trip blanks for that sampling period. 

2Lowest detection threshold that maximizes the number of quantifiable detections, minimizes the number of indeterminate samples, and for which the percent indeterminate samples is no more than 5 to 

8 percent, depending on sample size. 

3Indeterminate samples are censored data for which the reporting level (for example, <1) is higher than the applied censoring threshold (for example, 0.2), so it cannot be classified as either a detection or 

nondetection at that threshold (for example, it is unknown whether the contaminant is present at levels above 0.2).

4Data not censored because constituent was detected in all samples.5Optimal censoring threshold was not applied because no quantified detections remained after blank censoring.
48 Contaminants in Water and Sediment Sampled in Response to the Deepwater Horizon Oil Spill Table 16D. Optimal censoring thresholds and sample counts from the Deepwater Horizon oil spill, Gulf of Mexico, 2010: trace and major elements and nutrients in whole sediment.

[Abbreviations: CARB, carbon; mg/kg, milligram per kilogram; na, not applicable; nc, not censored because constituent was detected in all samples; NUTR; nutrient; PHYS, physical property; PLT63, percent of sediment sample that passes through a 63-μm sieve; PPW, paired Prentice-Wilcoxon; TME, trace and major element; <, less than; μm, micrometer]

Analyte Symbol or abbreviation Chemical class

Optimal 

censoring 

threshold 

PPW test1

Units

Before censoring After censoring at optimal threshold

PPW test 

performed

Number of 

samples 

with data

Number of 

quantified values 

that were censored

Number of censored 

values that are 

indeterminate2

Aluminum Al TME 0.1 percent 96 0 2 YesAntimony Sb TME 0.1 mg/kg 96 0 2 Yes

Arsenic As TME 0.1 mg/kg 96 0 0 YesBarium Ba TME 1 mg/kg 96 0 2 Yes

Beryllium Be TME 0.1 mg/kg 96 0 2 Yes

Cadmium Cd TME 0.1 mg/kg 96 0 3 Yes

Calcium Ca TME 0.1 percent 96 0 2 Yes

Carbon, total TC CARB 0.1 percent 96 0 0 YesChromium Cr TME 2 mg/kg 96 0 0 YesCobalt Co TME 1 mg/kg 96 0 2 Yes

Copper Cu TME 1 mg/kg 96 0 2 Yes

Iron Fe TME 0.1 percent 96 0 2 Yes

Lead Pb TME 1 mg/kg 96 0 0 Yes

Lithium Li TME 1 mg/kg 96 0 2 Yes

Magnesium Mg TME 0.1 percent 96 0 2 Yes

Manganese Mn TME 1 mg/kg 96 0 0 Yes

Mercury Hg TME 0.01 mg/kg 96 0 0 Yes

Molybdenum Mo TME 1 mg/kg 96 0 3 Yes

Nickel Ni TME 1 mg/kg 96 0 2 YesNitrogen

N NUTR 0.1 percent 95 20 0 Yes

Phosphorus

P NUTR nc mg/kg 96 na na Yes

Potassium

K TME 0.1 percent 96 0 2 Yes

Selenium Se TME 0.1 mg/kg 96 0 3 YesSilver Ag TME 0.5 mg/kg 96 0 3 Yes

Sodium Na TME 0.1 percent 96 0 0 YesStrontium Sr TME 1 mg/kg 96 0 0 Yes

Sulfur S TME 0.01 percent 96 0 0 Yes

Tin Sn TME 1 mg/kg 96 0 2 Yes

Titanium Ti TME 0.01 percent 96 0 1 YesVanadium

V TME 1 mg/kg 96 0 2 Yes

Zinc Zn TME 1 mg/kg 96 0 2 Yes

Percent of sediment <63-μm PLT63 PHYS 1 percent 95 0 0 Yes

1Lowest detection threshold that maximizes the number of quantifiable detections, minimizes the number of indeterminate samples, and for which the percent indeterminate samples is no more than 5 to 8 

percent, depending on sample size.

2Indeterminate samples are censored data for which the reporting level (for example, <1) is higher than the applied censoring threshold (for example, 0.2), so it cannot be classified as either a detection or 

nondetection at that threshold (it is unknown whether the contaminant is present at levels above 0.2).
Results and Discussion 49

Table 16E. Optimal censoring thresholds and sample counts from the Deepwater Horizon oil spill, Gulf of Mexico, 2010: trace and 

major elements and nutrients in the less than 63-micrometer (μm) sediment fraction

[Abbreviations: A, constituent was not detected in any samples after optimal censoring threshold was applied; CARB, carbon; mg/kg, milligram per kilogram; 

na, not applicable; nc, not censored because constituent was detected in all samples; NUTR, nutrient; PHYS, physical property; PPW, paired Prentice-Wilcoxon; 

TME, trace and major element; <, less than]

Analyte or 

parameter Symbol Chemical class

Optimal 

censoring 

threshold1

Units

Before censoring After censoring at optimal threshold

PPW test 

perfromed

Reason 

no PPW 

test was 

run

Number of 

samples 

with data

Number of 

quantified 

values that 

were censored

Number of 

censored values 

that are 

indeterminate2

Aluminum Al TME 0.3 percent 70 0 1 Yes na

Antimony Sb TME 0.4 mg/kg 70 3 5 Yes na

Arsenic As TME nc mg/kg 70 na na Yes na

Barium Ba TME nc mg/kg 70 na na Yes na

Beryllium Be TME 0.9 mg/kg 70 7 5 Yes na

Cadmium Cd TME 1.3 mg/kg 70 42 3 No A

Calcium Ca TME 0.2 percent 70 0 1 Yes na

Carbon, total TC CARB nc percent 39 na na Yes na

Chromium Cr TME 9 mg/kg 79 3 3 Yes na

Cobalt Co TME 10 mg/kg 70 24 5 Yes na

Copper Cu TME 5 mg/kg 79 0 1 Yes na

Iron Fe TME 0.2 percent 70 0 1 Yes na

Lead Pb TME 3 mg/kg 70 0 5 Yes na

Lithium Li TME 7 mg/kg 70 0 1 Yes na

Magnesium Mg TME nc percent 79 0 1 Yes na

Manganese Mn TME nc mg/kg 70 na na Yes na

Mercury Hg TME 0.01 mg/kg 47 0 0 Yes na

Molybdenum Mo TME 13 mg/kg 70 20 5 Yes na

Nickel Ni TME 2 mg/kg 70 0 1 Yes na

Nitrogen N NUTR nc percent 39 na na Yes na

Phosphorus P NUTR 1 mg/kg 79 0 0 Yes na

Potassium K TME 0.6 percent 70 0 4 Yes na

Selenium Se TME 1.2 mg/kg 70 45 5 Yes na

Sodium Na TME 0.5 percent 70 0 2 Yes na

Strontium Sr TME nc mg/kg 70 na na Yes na

Sulfur S TME nc percent 70 na na Yes na

Tin Sn TME 13 mg/kg 70 29 5 No A

Titanium Ti TME 0.03 percent 70 0 4 Yes na

Uranium U TME 600 mg/kg 70 1 5 No A

Vanadium V TME 6 mg/kg 79 0 1 Yes na

Zinc Zn TME 20 mg/kg 79 0 0 Yes na

1

Lowest detection threshold that maximizes the number of quantifiable detections, minimizes the number of indeterminate samples, and for which the percent 

indeterminate samples is no more than 7 percent.

2

Indeterminate samples are censored data for which the reporting level (for example, <1) is higher than the applied censoring threshold (for example, 0.2), so 

it cannot be classified as either a detection or nondetection at that threshold (for example, it is unknown whether the contaminant is present at levels above 0.2).
50 Contaminants in Water and Sediment Sampled in Response to the Deepwater Horizon Oil Spill 

Organic Contaminants in Water 

For organic contaminants in water, samples were 

analyzed by different laboratories; pre-landfall samples were 

analyzed by the USGS NWQL, and post-landfall samples 

by the TestAmerica Laboratories in either Colorado or 

Florida. This complicates the comparison of contaminant 

occurrence between sampling periods, as described in the 

following section. 

Contaminant Occurrence

Few organic contaminants were detected in water 

samples (table 17). For each contaminant, table 17 provides 

an optimal censoring threshold, as described previously, to 

use in comparing detection frequencies between pre-landfall 

and post-landfall samples, as well as a series of four common 

detection thresholds to use in comparing detection frequencies 

among analytes. A common detection threshold must be 

applied when comparing detection frequencies for analytes 

with different or variable reporting levels, as is discussed later 

in this report.

Of the 41 contaminants analyzed only in pre-landfall 

samples, where the number of samples (n) is 60 to 65 sites 

depending on the analyte, 5 contaminants were detected in 

one or more samples: 1,3,5-trimethylbenzene, 2-ethyltoluene, 

n-propylbenzene, dibromomethane, and benzo[g,h,i]

perylene. Of the 24 contaminants analyzed only in postlandfall samples, where n is 48 sites, 5 contaminants were 

detected in one or more samples: a mixture of C8 to C36 

organics, oil range organics (C28 to C35), gasoline-range 

organics (C6 to C10), diesel-range organics, and total xylene. 

Of 94 organic contaminants analyzed in both pre-landfall 

samples and post-landfall samples, one or more detections 

were observed for 28 analytes in pre-landfall samples and for 

9 analytes in post-landfall samples, with 7 of these analytes, 

including dissolved organic carbon, detected in samples 

from both sampling periods. Two analytes—toluene and 

trichloromethane—were detected in one or more post-landfall 

samples but no pre-landfall samples. Although more analytes 

were detected in pre-landfall than post-landfall samples, two 

factors need to be considered: (1) more sites distributed over 

a wider geographic area were sampled during the pre-landfall 

period, typically 60 to 68, than during the post-landfall 

period, which typically had 47 to 48 sites; and (2) reporting 

levels were lower for many analytes in pre-landfall than in 

post-landfall samples, which were analyzed by different 

laboratories. Thus, the detection frequencies are not directly 

comparable without adjustment for these factors.

This is illustrated in figure 4, which shows the cumulative 

frequency distributions of concentrations determined 

for two example contaminants in water, isophorone and 

benzene. (Appendix 2 provides a complete set of cumulative 

frequency plots for all individual contaminants determined 

in water and sediment.) For isophorone in water (fig. 4A), 

the detections observed in many pre-landfall samples were 

well below the reporting level for isophorone in post-landfall 

samples. Although it is possible that isophorone was present 

in post-landfall samples at concentrations comparable to 

those in pre-landfall samples, the analytical method used 

for post-landfall samples was not sensitive enough to detect 

these values. Similar results were observed for several 

PAHs in water (appendix 2-1). The benzene example 

(fig. 4B) illustrates the effect of blank censoring. In this 

case, comparison of pre-landfall to post-landfall occurrence 

is limited because the censoring level for all post-landfall 

samples was raised to 2.1 μg/L as a result of benzene detection 

in a blank from the post-landfall period. Because the raw 

benzene concentrations detected in post-landfall samples 

were less than the censoring threshold, there is uncertainty as 

to whether these concentrations were the result of incidental 

contamination; therefore, all post-landfall samples were 

reported as less than 2.1 μg/L. Concentrations of 0.02 to 

0.05 μg/L that were detected in pre-landfall samples were 

much lower than the less than 2.1 μg/L censored results 

for post-landfall samples, so pre-landfall and post-landfall 

sample concentrations cannot be compared quantitatively for 

this analyte. 

When detection frequencies above the optimal censoring 

threshold, which varies by analyte, as shown in table 17, 

were computed for organic contaminants in water, dissolved 

organic carbon was detected in about 40 percent of samples 

from both pre-landfall and post-landfall sampling periods, 

and 14 additional analytes were detected in one or more 

samples. Of these 14 analytes, 12 were detected in only one 

sample each. The remaining two detected analytes were 

toluene and the mixture of C8 to C36 organics. Toluene was 

detected above an optimal censoring threshold of 0.7 μg/L 

in 13 percent of post-landfall samples and no pre-landfall 

samples; the C8 to C36 organics were detected above 

an optimal censoring threshold of 47 μg/L in 7 percent 

detection of post-landfall samples but were not analyzed 

in pre-landfall samples. Toluene is the only analyte of the 

94 determined in water during both sampling periods to 

show much difference between the two sampling periods in 

detection frequencies above the optimal censoring threshold 

(table 17). A more rigorous, statistical comparison between 

contaminant concentrations in pre-landfall and post-landfall 

samples follows. 

Table 17. Summary statistics for organic contaminants in water from the Deepwater Horizon oil spill, Gulf of Mexico, 2010.

This table is available as a Microsoft© Excel spreadsheet. It can be accessed and downloaded at URL http://pubs.usgs.gov/

sir/2012/5228.
Results and Discussion 51

sac12-0452_Figure 04ab CUMULATIVE FREQUENCY, IN PERCENT

100

80

60

40

20

0

0.0 0.2 0.4 0.6

CONCENTRATION, IN MICROGRAMS PER LITER

Pre-landfall N = 67

Post-landfall N = 48

N is number of samples

N is number of samples

Pre-landfall N = 63

Post-landfall N = 48

Pre-landfall 

Post-landfall 

Pre-landfall censored

Pre-landfall quantified 

Post-landfall censored 

CUMULATIVE FREQUENCY 

EXPLANATION

DATA

CUMULATIVE FREQUENCY, IN PERCENT

100

80

60

40

20

0

0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4

CONCENTRATION, IN MICROGRAMS PER LITER

Pre-landfall 

Post-landfall 

Pre-landfall censored

Pre-landfall quantified 

Post-landfall censored 

CUMULATIVE FREQUENCY 

EXPLANATION

DATA

A Isophorone Medium is surface water; parameter code is 34408

B Benzene Medium is surface water; parameter code is 34030

Figure 4. Examples of the data distribution of contaminant concentrations from the Deepwater Horizon oil spill, Gulf of 

Mexico, 2010: (A) isophorone in water, (B) benzene in water, (C) C3-alkylated fluorenes in sediment, (D) zinc in water, (E) 

molybdenum in water, (F) phosphorus in water, (G) ammonia plus organic nitrogen in water, (H) potassium in water, (I) 

calcium in whole sediment, (J) lead in whole sediment, and (K) phosphorus in whole sediment. N, number of samples.
52 Contaminants in Water and Sediment Sampled in Response to the Deepwater Horizon Oil Spill 

sac12-0452_Figure 04cd CUMULATIVE FREQUENCY, IN PERCENT

100

80

60

40

20

0

0 2 4 6 8 10

CONCENTRATION, IN MICROGRAMS PER KILOGRAM

Pre-landfall N = 69

Post-landfall N = 48

Pre-landfall N = 63

Post-landfall N = 48

Pre-landfall 

Post-landfall 

Pre-landfall censored

Pre-landfall quantified 

Post-landfall quantified 

Post-landfall quantified 

Post-landfall censored 

CUMULATIVE FREQUENCY 

EXPLANATION

DATA

CUMULATIVE FREQUENCY, IN PERCENT

100

80

60

40

20

0

0 20 40 60 80 100

CONCENTRATION, IN MICROGRAMS PER LITER

Pre-landfall 

Post-landfall 

Pre-landfall censored

Pre-landfall quantified 

Post-landfall censored 

CUMULATIVE FREQUENCY 

EXPLANATION

DATA

C C3-alkylated fluorenes Medium is sediment; parameter code is 68091

D Zinc Medium is surface water; parameter code is 01092

N is number of samples

N is number of samples

Figure 4.—Continued
Results and Discussion 53

sac12-0452_Figure 04ef CUMULATIVE FREQUENCY, IN PERCENT

100

80

60

40

20

0

0 10 20 30

CONCENTRATION, IN MICROGRAMS PER LITER

Pre-landfall N = 63

Post-landfall N = 48

Pre-landfall N = 68

Post-landfall N = 48

Pre-landfall 

Post-landfall 

Pre-landfall quantified 

Post-landfall quantified 

Post-landfall quantified 

Post-landfall censored 

CUMULATIVE FREQUENCY 

EXPLANATION

DATA

CUMULATIVE FREQUENCY, IN PERCENT

100

80

60

40

20

0

0 0.2 0.4 0.6 0.8 1.0

CONCENTRATION, IN MILLIGRAMS PER LITER

Pre-landfall 

Post-landfall 

Pre-landfall censored

Pre-landfall quantified 

Post-landfall censored 

CUMULATIVE FREQUENCY 

EXPLANATION

DATA

E Molybdenum Medium is surface water; parameter code is 01062

F Phosphorus as P Medium is surface water; parameter code is 00665

N is number of samples

N is number of samples

Figure 4.—Continued
54 Contaminants in Water and Sediment Sampled in Response to the Deepwater Horizon Oil Spill 

sac12-0452_Figure 04gh CUMULATIVE FREQUENCY, IN PERCENT

100

80

60

40

20

0

0 1 2 3 4

CONCENTRATION, IN MILLIGRAMS PER LITER AS NITROGEN

Pre-landfall N = 67

Post-landfall N = 48

Pre-landfall N = 61

Post-landfall N = 48

Pre-landfall 

Post-landfall 

Pre-landfall quantified 

Post-landfall quantified 

Post-landfall censored 

CUMULATIVE FREQUENCY 

EXPLANATION

DATA

CUMULATIVE FREQUENCY, IN PERCENT

100

80

60

40

20

0

0 200 400 600 800

CONCENTRATION, IN MILLIGRAMS PER LITER

Pre-landfall 

Post-landfall 

Pre-landfall quantified 

CUMULATIVE FREQUENCY 

EXPLANATION

DATA

G Ammonia plus organic nitrogen as N Medium is surface water; parameter code is 00625

H Potassium Medium is surface water; parameter code is 00937

N is number of samples

N is number of samples

Figure 4.—Continued
Results and Discussion 55

sac12-0452_Figure 04ij CUMULATIVE FREQUENCY, IN PERCENT

100

80

60

40

20

0

0 10 20 30 40

CONCENTRATION, IN PERCENT BY WEIGHT

Pre-landfall N = 70

Post-landfall N = 49

Pre-landfall N = 70

Post-landfall N = 49

Pre-landfall 

Post-landfall 

Pre-landfall quantified 

Post-landfall quantified 

Post-landfall quantified 

Post-landfall censored 

CUMULATIVE FREQUENCY 

EXPLANATION

DATA

CUMULATIVE FREQUENCY, IN PERCENT

100

80

60

40

20

0

0 10 20 30 40 50 60

CONCENTRATION, IN MILLIGRAMS PER KILOGRAM

Pre-landfall 

Post-landfall 

Pre-landfall censored

Pre-landfall quantified 

Post-landfall censored 

CUMULATIVE FREQUENCY 

EXPLANATION

DATA

Pre-landfall censored

I Calcium Medium is sediment; parameter code is 01476

J Lead Medium is sediment; parameter code is 01382

N is number of samples

N is number of samples

Figure 4.—Continued
56 Contaminants in Water and Sediment Sampled in Response to the Deepwater Horizon Oil Spill 

Comparison of Pre-Landfall to 

Post-Landfall Samples

Of the approximately 100 organic compounds that were 

determined in at least 100 water samples, only 11 compounds 

had enough quantified detections above the optimal censoring 

threshold to make a statistical comparison of pre-landfall 

to post-landfall samples. Of these, only toluene and organic 

carbon showed a significant difference between pre‐landfall 

and post-landfall samples in the PPW test. Toluene 

concentrations were significantly higher in post-landfall 

samples than in pre-landfall samples (p=0.0144; table 18). 

This statistical test result supports the previous observation 

that toluene in water had a higher detection frequency in 

post-landfall samples, at 13 percent, than in pre-landfall 

samples, where it was not detected, after data were censored 

to an optimal threshold of 0.7 μg/L (table 17). The difference 

in concentrations between post-landfall and pre-landfall 

samples (Cpost – Cpre) for toluene at each site along the GOM 

coast, from west to east, is shown in figure 5A. For each site 

in figure 5A, the difference in concentrations of toluene is a 

range, which indicates that one or both samples is censored, 

that is, a nondetection; this range is derived by using both 

zero and the reporting level as the censored value when 

calculating the difference. By using this method of calculation, 

all of the bars that are centered on zero are cases where both 

pre-landfall samples and post-landfall samples were censored 

(for example, most sites in fig. 5A); ranges that do not include 

zero are based on one censored value and one detection. 

For toluene (fig. 5A), the five bars with positive values 

indicate detections in post-landfall samples and censored 

data in the corresponding pre-landfall samples. If there is 

a single point instead of a range, then both samples were 

quantified detections. A single negative value results when the 

concentration is higher in the pre-landfall sample than in the 

post-landfall sample (as shown in fig. 5B for LA-22), and a 

single positive value indicates that the concentration is higher 

in the post-landfall sample than in the pre-landfall sample (as 

shown in fig. 5B for LA-26).

sac12-0452_Figure 04K CUMULATIVE FREQUENCY, IN PERCENT

100

80

60

40

20

0

0 200 400 600 800 1,000 1,200

CONCENTRATION, IN MILLIGRAMS PER KILOGRAM

Pre-landfall N = 70

Post-landfall N = 49

Pre-landfall 

Post-landfall 

Pre-landfall quantified 

Post-landfall censored 

CUMULATIVE FREQUENCY 

EXPLANATION

DATA

K Phosphorus Medium is sediment; parameter code is 01388

N is number of samples

Figure 4.—Continued
Results and Discussion 57

Table 18. Statistical comparisons of contaminant concentrations in pre-landfall samples to those in post-landfall samples from the 

Deepwater Horizon oil spill, Gulf of Mexico, 2010: organic contaminants in water.

[Significant p-values are shaded yellow (p<0.01) or orange (p<0.05). Abbreviations: A, no detections remained after censoring at optimal censoring threshold; 

B, no detections in paired dataset; C, no detections remain after blank censoring; mg/L, milligrams per liter; n, number of sample pairs; na, not applicable; nc, 

not censored at optimal censoring threshold because no detections remained after blank censoring; ns, not significant at 0.05 level in a 2-sided test; PPW, paired 

Prentice-Wilcoxon; μg/L, micrograms per liter; <, less than; ≤, less than or equal to; –, PPW test was not run]

Analyte Units

Optimal 

censoring 

threshold1

Paired Prentice–Wilcoxon test

2

n p-value

Sampling 

period with 

significantly higher 

concentration

Reason no PPW 

test was run

Acenaphthene μg/L 0.28 – – – A

Acenaphthylene μg/L 0.3 – – – A

Anthracene μg/L 0.39 – – – A

Benzene μg/L 0.34 44 0.0833 ns na

Benzo[a]anthracene μg/L 0.26 46.5 0.3173 ns na

Benzo[a]pyrene μg/L 0.33 46.5 0.3173 ns na 

Benzo[b]fluoranthene μg/L 0.3 46.5 0.3173 ns na 

Benzo[k]fluoranthene μg/L 0.4 – – – B

Bis(2-chloroethyl)ether μg/L 2.1 – – – B

Bis(2-ethylhexyl) phthalate μg/L 7.4 41.5 0.3173 ns na

Carbon, organic mg/L 3 40 0.0001 Post-landfall na

Carbon disulfide μg/L 0.5 41 0.3173 ns na

Chloromethane μg/L 0.53 – – – A

Chrysene μg/L 0.33 45 0.3173 ns na

Dibenzo[a,h]anthracene μg/L 0.42 – – – B

Dichloromethane μg/L nc – – – C

Diethyl phthalate μg/L 0.61 – – – A

Di-n-butyl phthalate μg/L 2 – – – A

Ethylbenzene μg/L nc – – – C

Fluoranthene μg/L 0.3 – – – A

Fluorene μg/L 0.33 – – – A

Indeno(1,2,3-cd)pyrene μg/L 0.38 – – – B

Isophorone μg/L 0.61 – – – A

Naphthalene μg/L nc – – – C

Pentachlorophenol μg/L 3.1 – – – A

Phenanthrene μg/L 0.32 – – – A

Phenol μg/L 1.5 – – – A

Pyrene μg/L 0.35 – – – A

Toluene μg/L 0.7 44 0.0144 Post-landfall na

Tribromomethane μg/L 0.58 – – – A

Trichloromethane μg/L 0.6 44 0.3173 ns na

Xylenes, total μg/L 1.6 44 0.3173 ns na

1

Lowest detection threshold that maximizes the number of quantifiable detections, minimizes the number of indeterminate samples, and has ≤5 to 8 percent 

indeterminate samples, depending on sample size.

2

Non-integer indicates data missing for one member of a sample pair.
58 Contaminants in Water and Sediment Sampled in Response to the Deepwater Horizon Oil Spill 

Toluene was not detected at greater than 0.7 μg/L in 

pre-landfall samples but was detected in six post-landfall 

samples, only five of which were in the paired data set and 

therefore appear in figure 5A. The significant PPW test result 

was influenced by the toluene detections in post-landfall 

samples from five sites: MS-37, FL-3, FL-4, FL-25, and 

FL-5 (fig. 5A). Additional BTEX compounds—benzene and 

xylenes—were detected in samples from two of these sites: 

MS-37 and FL-25. 

The detection of BTEX compounds in post-landfall 

beach-water samples does not necessarily indicate the 

presence of M-1 oil. Weathered M-1 oil, which was collected 

on April 27, 2010, contained no detectable BTEX compounds; 

of the aliphatic and cyclic hydrocarbons detected, the lowest 

molecular-weight compound detected was the alkane n-C14 

(State of Florida Oil Spill Academic Task Force, 2010), and 

BTEX compounds were not detected in surface-oil samples 

approaching the near shore environment (Atlas and Haven, 

2011). BTEX compounds are volatile and tend to be rapidly 

removed from seawater by evaporation, and to a lesser extent 

by sorption to particles and sediment, biodegradation, and 

photolysis (Neff, 2002). Other sources of BTEX compounds 

to the GOM include produced water (Neff, 2002; Neff and 

others, 2011), deposition of airborne hydrocarbons from 

combustion sources, and natural oil and gas seeps (Continental 

Shelf Associates, 1997). Nevertheless, high concentrations 

of BTEX compounds, including up to 30 μg/L toluene, were 

reported in a plume trending southwest from the M-1 well 

at about 1,100 m depth in June 2010 (Reddy and others, 

2012); it was concluded that although the ultimate fate of 

these compounds in the deep-water plume was unknown, the 

apportionments of hydrocarbon transfers to the water column 

and atmosphere appeared to be very different for a deepwater spill compared to a sea-surface oil spill. In the present 

study, water samples were collected at wadable depths near 

the shore, and toluene was detected in post-landfall water 

samples from six sites. Three of the six sites with toluene 

detections, MS-37, AL-7, and FL-3, were reported to have the 

M-1 oil fingerprint in corresponding post-landfall samples of 

sediment, tarballs, or both (Rosenbauer and others, 2010)—

thus providing direct evidence of M-1 oil landfall at those 

sites at the time of post-landfall sampling—but the other three 

sites with toluene detections, FL-4, FL-25, and FL-5, did not 

show evidence of M-1 oil. No evidence of M-1 oil was found 

in 69 pre-landfall sediment samples analyzed by Rosenbauer 

and others (2011), although a tarball from one site, FL-18, was 

similar to M-1 oil, as discussed later in the report. 

Comparison with Benchmarks for Human Health 

and Aquatic Life 

Benchmark comparisons were made for all field samples, 

including primary environmental samples and field replicates. 

Benchmark exceedances for organics in water by individual 

sample are listed in appendix table 3-1, and the results are 

summarized in table 19. For those organic compounds with 

benchmarks, 253 water samples were analyzed: 196 prelandfall samples from 70 sites and 57 post-landfall samples 

from 49 sites. Not every organic compound was analyzed in 

every sample, as indicated in appendix table 3-1. Of the 253 

water samples, 138 samples were analyzed for PAHs and 

BTEX compounds, 86 samples for BTEX compounds only, 

and 29 samples for PAHs only. 

Human-health benchmarks are available for 11 organic 

contaminants analyzed in water (table 5C). None of these 

benchmarks were exceeded by any water samples in this study. 

Aquatic-life benchmarks used in the present study 

include the USEPA’s toxic-unit benchmarks for mixtures 

of PAH and BTEX compounds (table 5A), as well as 

supplementary aquatic-life benchmarks for 72 individual 

organic contaminants (table 5B). One water sample exceeded 

the USEPA’s chronic toxic-unit benchmark for PAH and 

BTEX compound mixtures (table 19, appendix 3-1). As 

noted previously, this benchmark assumes additive toxicity 

for compounds with the same mechanism of action, and a 

∑TUi

 value greater than 1 indicates that chronic toxicity to 

aquatic life is likely. The single water sample exceeding this 

benchmark was the post-landfall sample from the Mississippi 

River at South Pass, Louisiana (site LA-35), for which the 

chronic ∑TUi value was 2.4. This is substantially higher 

than the corresponding chronic ∑TUi value of less than 10–4

for the pre-landfall sample collected at this site. Neither the 

post-landfall nor the pre-landfall sediment from site LA-35 

contained the M-1 oil fingerprint (Rosenbauer and others, 

2010 and 2011).

Of the 72 individual organic contaminants analyzed in 

this study that have aquatic-life benchmarks (table 5B), not all 

were analyzed in every water sample (see appendix table 3-1). 

However, none of the aquatic-life benchmarks for any 

individual organic contaminants were exceeded by any water 

samples in this study. 

Of individual organic contaminants with benchmarks, 

recovery in matrix spikes was less than 70 percent for 

six contaminants—4-nitrophenol, benzo[a]pyrene, 

hexachlorobutadiene, hexachlorocyclopentadiene, 

hexachloroethane, and N-nitrosodiphenylamine—indicating 

that the measured concentration could be biased low. 
Results and Discussion 59

, PRE MINUS C POST C

sac12-0452_Figure 5ab

IN MICROGRAMS PER KILOGRAM 

MAP NUMBER (WEST TO EAST)

TX-56

TX-55

TX-51

TX-53

TX-49

TX-47

LA-46

LA-25

LA-23

LA-28

LA-26

LA-24

LA-31

LA-36

LA-35

LA-32

LA-33

LA-29

LA-22

LA-30

LA-34

MS-43

MS-37

MS-38

MS-39

MS-44

MS-40

MS-41

MS-45

MS-42

AL-1

AL-2

AL-3

AL-4

AL-8

AL-5

AL-9

AL-10

AL-6

AL-7

FL-1

FL-2

FL-3

FL-4

FL-25

FL-5

FL-6

FL-7

–20–40

0

604020

, PRE MINUS C POST C

IN MICROGRAMS PER LITER 

MAP NUMBER (WEST TO EAST)

TX-56

TX-55

TX-51

TX-53

TX-49

TX-47

LA-46

LA-25

LA-23

LA-28

LA-26

LA-24

LA-31

LA-36

LA-35

LA-32

LA-33

LA-29

LA-22

LA-30

LA-34

MS-43

MS-37

MS-38

MS-39

MS-44

MS-40

MS-41

MS-45

MS-42

AL-1

AL-2

AL-3

AL-4

AL-8

AL-5

AL-9

AL-10

AL-6

AL-7

FL-1

FL-2

FL-3

FL-4

FL-25

FL-5

FL-6

FL-7

-1 

5 4 3 2 1 0 

Maximum Minimum 

Gray bar indicatesmissing dataor no sample

Maximum Minimum 

Gray bar indicatesmissing dataor no sample

A Toluene in water

CPOST minus CPRE > 0 (p = 0.014)

B Chrysene in sediment

CPOST minus CPRE > 0 (p = 0.0033)

Note: > is greater than

Figure 5. For selected analytes, difference between organic contaminant concentrations in samples collected during post-landfall and pre-landfall periods (Cpost

minus Cpre) by the USGS at Deepwater Horizon oil spill sampling sites along the Gulf of Mexico coast, 2010, from west to east, for (

A) toluene in water, (

B) chrysene 

in sediment, (

C) C1-alkylated chrysenes in sediment, (

D) C2-alkylated fluorenes in sediment, (

E) C3-alkylated dibenzothiophenes in sediment, (

F) C4-alkylated 

phenanthrenes/anthracenes in sediment, (

G) naphthalene in sediment, and (

H) oil and grease in sediment.
60 Contaminants in Water and Sediment Sampled in Response to the Deepwater Horizon Oil Spill 

sac12-0452_Figure 5cd

CPOST MINUS CPRE,

IN MICROGRAMS PER KILOGRAM 

MAP NUMBER (WEST TO EAST)

TX-56

TX-55

TX-51

TX-53

TX-49

TX-47

LA-46

LA-25

LA-23

LA-28

LA-26

LA-24

LA-31

LA-36

LA-35

LA-32

LA-33

LA-29

LA-22

LA-30

LA-34

MS-43

MS-37

MS-38

MS-39

MS-44

MS-40

MS-41

MS-45

MS-42

AL-1

AL-2

AL-3

AL-4

AL-8

AL-5

AL-9

AL-10

AL-6

AL-7

FL-1

FL-2

FL-3

FL-4

FL-25

FL-5

FL-6

FL-7

–1 –2 –3 –4 

4 3 2 1 0 

CPOST MINUS CPRE,

IN MICROGRAMS PER KILOGRAM

MAP NUMBER (WEST TO EAST)

TX-56

TX-55

TX-51

TX-53

TX-49

TX-47

LA-46

LA-25

LA-23

LA-28

LA-26

LA-24

LA-31

LA-36

LA-35

LA-32

LA-33

LA-29

LA-22

LA-30

LA-34

MS-43

MS-37

MS-38

MS-39

MS-44

MS-40

MS-41

MS-45

MS-42

AL-1

AL-2

AL-3

AL-4

AL-8

AL-5

AL-9

AL-10

AL-6

AL-7

FL-1

FL-2

FL-3

FL-4

FL-25

FL-5

FL-6

FL-7

–10–20

0

40302010

Maximum Minimum 

Gray bar indicatesmissing dataor no sample

C C1-alkylated chrysenes in sediment

CPOST minus CPRE > 0 (p = 0.0037)

D C2-alkylated fluorenes in sediment

CPOST minus CPRE > 0 (p = 0.0144)

Maximum Minimum 

Gray bar indicatesmissing dataor no sample

Note: > is greater than

Figure 5.—Continued
Results and Discussion 61 sac12-0452_Figure 5ef

, PRE MINUS C POST C

IN MICROGRAMS PER KILOGRAM 

MAP NUMBER (WEST TO EAST)

TX-56

TX-55

TX-51

TX-53

TX-49

TX-47

LA-46

LA-25

LA-23

LA-28

LA-26

LA-24

LA-31

LA-36

LA-35

LA-32

LA-33

LA-29

LA-22

LA-30

LA-34

MS-43

MS-37

MS-38

MS-39

MS-44

MS-40

MS-41

MS-45

MS-42

AL-1

AL-2

AL-3

AL-4

AL-8

AL-5

AL-9

AL-10

AL-6

AL-7

FL-1

FL-2

FL-3

FL-4

FL-25

FL-5

FL-6

FL-7

–5

50

201510

, PRE MINUS C POST C

IN MICROGRAMS PER KILOGRAM

MAP NUMBER (WEST TO EAST)

TX-56

TX-55

TX-51

TX-53

TX-49

TX-47

LA-46

LA-25

LA-23

LA-28

LA-26

LA-24

LA-31

LA-36

LA-35

LA-32

LA-33

LA-29

LA-22

LA-30

LA-34

MS-43

MS-37

MS-38

MS-39

MS-44

MS-40

MS-41

MS-45

MS-42

AL-1

AL-2

AL-3

AL-4

AL-8

AL-5

AL-9

AL-10

AL-6

AL-7

FL-1

FL-2

FL-3

FL-4

FL-25

FL-5

FL-6

FL-7

–2–4–6

86420

1210

E C3-alkylated dibenzothiophenes in sediment

CPOST minus CPRE > 0 (p = 0.0164)

F C4-alkylated phenanthrenes/anthracenes in sediment

CPOST minus CPRE > 0 (p = 0.0041)

Maximum Minimum 

Maximum Minimum 

Gray bar indicatesmissing dataor no sample

Gray bar indicatesmissing dataor no sample

Note: > is greater than

Figure 5.—Continued
62 Contaminants in Water and Sediment Sampled in Response to the Deepwater Horizon Oil Spill 

sac12-0452_Figure 5gh

, PRE MINUS C POST C

IN MILLIGRAMS PER KILOGRAM 

MAP NUMBER (WEST TO EAST)

TX-56

TX-55

TX-51

TX-53

TX-49

TX-47

LA-46

LA-25

LA-23

LA-28

LA-26

LA-24

LA-31

LA-36

LA-35

LA-32

LA-33

LA-29

LA-22

LA-30

LA-34

MS-43

MS-37

MS-38

MS-39

MS-44

MS-40

MS-41

MS-45

MS-42

AL-1

AL-2

AL-3

AL-4

AL-8

AL-5

AL-9

AL-10

AL-6

AL-7

FL-1

FL-2

FL-3

FL-4

FL-25

FL-5

FL-6

FL-7

–1,000–1,500–2,000–2,500

–500

0

500

1,000

, PRE MINUS C POST C

IN MICROGRAMS PER KILOGRAM

MAP NUMBER (WEST TO EAST)

TX-56

TX-55

TX-51

TX-53

TX-49

TX-47

LA-46

LA-25

LA-23

LA-28

LA-26

LA-24

LA-31

LA-36

LA-35

LA-32

LA-33

LA-29

LA-22

LA-30

LA-34

MS-43

MS-37

MS-38

MS-39

MS-44

MS-40

MS-41

MS-45

MS-42

AL-1

AL-2

AL-3

AL-4

AL-8

AL-5

AL-9

AL-10

AL-6

AL-7

FL-1

FL-2

FL-3

FL-4

FL-25

FL-5

FL-6

FL-7

–10–20–30

0

605040302010

G Naphthalene in sediment

CPOST minus CPRE < 0 (p = 0.0008)

H Oil and grease in sediment

CPOST minus CPRE < 0 (p = 0.0095)

Maximum Minimum 

Gray bar indicatesmissing dataor no sample

Maximum Minimum 

Gray bar indicatesmissing dataor no sample

Note: < is less than

Figure 5.—Continued
Results and Discussion 63

Table 19. Summary of benchmark exceedances for organic contaminants in water and sediment from the Deepwater Horizon oil spill, Gulf of Mexico, 2010.[Abbreviations: BTEX, benzene, toluene, ethylbenzene, xylene and related compounds; ESBTU, equilibrium-partitioning sediment benchmark toxic unit for PAH mixtures in sediment; MW, molecular weight; 

PAH, polycyclic aromatic hydrocarbon; post, post-landfall samples; pre, pre-landfall samples; SV, screening value; TU, toxic unit benchmark for PAH-BTEX mixtures in water; –, no benchmarks exceeded]

State

Water Sediment

Number 

of sites

Total 

number of 

samples1

Number of 

samples with 

exceedances2

Benchmarks 

exceeded2

Number of 

sites

 Number of samples

Upper SV and ESBTU 

benchmarks exceeded7 Total3

In minimal 

effect 

range4

In possible 

effect 

range5

In probable 

effect 

range6

 Pre-landfall sampling period

Texas 10 24 0 – 10 12 8 0 4 Total PAH, Low-MW PAH, chronic ESBTU

Louisiana 15 35 0 – 15 19 8 1 10 Total PAH, Low-MW PAH

Mississippi 9 25 0 – 9 11 11 0 0 –

Alabama 10 26 0 – 10 14 12 2 0 –

Florida 26 86 0 – 26 52 42 0 10 Total PAH, Low-MW PAH, High-MW PAH

Total pre-landfall 70 196 0 – 70 108 81 3 24

 Post-landfall sampling period

Texas 6 9 0 – 6 10 5 1 4 Total PAH, Low-MW PAH 

Louisiana 16 18 1 Chronic TU 15 17 5 0 12 Total PAH, Low-MW PAH, High-MW PAH

Mississippi 9 10 0 – 9 10 9 0 1 Total PAH

Alabama 10 11 0 – 10 11 8 0 3 Total PAH, Low-MW PAH, High-MW PAH 

Florida 8 9 0 – 8 9 8 0 1 Total PAH

Total post-landfall 49 57 1 48 57 35 1 21

Total (all samples) 119 253 1 118 165 116 4 45

1The total number of water samples includes field replicate samples, and counts separately samples sent to different laboratories for analysis. About 70 percent of water samples were analyzed for PAHs and 

BTEX compounds, and 30 percent were analyzed for BTEX compounds at a different laboratory. Samples typically were collected from a given site on the same date.

2Organic contaminants in water were compared to aquatic-life benchmarks in tables 5A and 5B, and human-health benchmarks in table 5C.3The total number of sediment samples includes field replicate samples. Samples were analyzed for PAHs, alkylated PAHs, and a few additional semivolatile organic compounds. Samples typically were 

collected from a given site on the same date.

4All constituent concentrations were below all applicable benchmarks (table 6C); there is no indication of adverse effects on benthic organisms within this range.5One or more constituents exceeded a lower SV benchmark, but no elements exceeded an upper SV benchmark; adverse biological effects occasionally occur within this range.6One or more constituents exceeded an upper SV benchmark; adverse biological effects frequently occur within this range.7Organic contaminants in sediment were compared to sediment-quality benchmarks in tables 5D and 5E.
64 Contaminants in Water and Sediment Sampled in Response to the Deepwater Horizon Oil Spill 

Benchmark results in appendix table 3-1 and summary 

statistics in table 17 are footnoted to indicate this. The single 

observed benchmark exceedance of the chronic TU benchmark 

for PAH and BTEX compounds by one post-landfall sample 

from site LA-35 must be considered in light of the QC data 

for organic contaminants in water. Of the compounds included 

in this benchmark, one BTEX compound (benzene) and one 

PAH compound (naphthalene) were detected in field or trip 

blanks associated with post-landfall samples; therefore, data 

for these two analytes were censored at five times the blank 

concentration to minimize the probability that incidental 

contamination contributed to the reported concentrations 

and any consequent benchmark exceedances. In the case of 

the LA-35 sample that exceeded the chronic TU benchmark, 

however, neither benzene nor naphthalene was detected in 

the sample; therefore, their concentrations were set to zero 

when computing the TU values for this sample, following 

the USEPA’s calculation procedure and examples, which 

assume that censored values are equivalent to zero (Mount, 

2010). Therefore, incidental contamination by benzene or 

naphthalene did not contribute to the chronic TU benchmark 

exceedance in the post-landfall sample at site LA-35.

Because there was only one benchmark exceedance, 

Fisher’s exact test was not performed for organic contaminants 

in water. When chronic ∑TUi

 values for all 47 pairs of 

pre-landfall and post-landfall samples were compared, there 

was no significant difference between the two sampling 

periods (sign test, p>0.05). In addition, acute ∑TUi values for 

PAH and BTEX compound mixtures were not greater than 1 

in any water samples, and there was no significant difference 

in acute ∑TUi values between pre-landfall and post-landfall 

samples (sign test, p>0.05). Again, these comparisons need to 

be qualified because reporting levels varied among analytes 

and between the two sampling periods, and concentrations 

were not censored to a single detection threshold prior to 

calculation of benchmark ∑TUi values, which were calculated 

following the standard USEPA procedure. Because reporting 

levels for many analytes were higher in post-landfall samples 

than in pre-landfall samples, setting nondetections equal to 

zero could underestimate benchmark exceedance rates in 

post-landfall samples relative to pre-landfall samples. Also, of 

the 47 sites with paired data, 6 pre-landfall sites were missing 

data for BTEX compounds, so the benchmark ∑TUi

 values for 

these pre-landfall samples were computed for PAHs only. 

Organic Contaminants in Sediment 

Most organic contaminants in sediment were determined 

by a single laboratory (TestAmerica Laboratory in Vermont) 

in samples from both sampling periods. These contaminants 

include parent PAHs and alkylated PAH groups, which are 

of potential concern from the oil spill (U.S. Environmental 

Protection Agency, 2011b). Fourteen additional organic 

contaminants, mostly individual alkylated PAH compounds, 

were analyzed only in pre-landfall samples by the USGS 

NWQL. Also, 44 miscellaneous SVOCs were analyzed in 

post-landfall but not pre-landfall samples; these include 

chlorinated phenols, nitroaromatic compounds, chlorinated 

alkanes and alkenes, nitroso compounds, and phthalate esters.

Reporting levels for organics in sediment varied 

somewhat for a given compound, but not as widely as for 

organics in water, and reporting levels were comparable for 

pre-landfall and post-landfall samples (appendix 2). 

Contaminant Occurrence

The detection frequencies and percentile concentrations 

of organic contaminants in sediment are shown in table 20. 

Of the 14 organic contaminants analyzed only in prelandfall samples, excluding TOC, 8 contaminants were 

detected in 1 to 4 samples each. Six of these were individual 

alkylated PAH compounds that also were included in 

determination of alkylated PAH groups (for example, 

1,2-dimethylnaphthalene would be included in the C-2 

naphthalenes group) by TestAmerica Laboratory in Vermont. 

The remaining two were 9,10-anthraquinone and the mixture 

of petroleum hydrocarbons. 

There were 52 organic contaminants, plus organic 

carbon, analyzed in both pre-landfall and post-landfall 

samples: 19 parent PAHs, 5 individual alkylated PAHs, 

22 alkylated PAH groups, 5 SVOCs, and oil and grease. Of 

the 52 analytes, 49 were detected in pre-landfall samples 

and 50 in post-landfall samples, with 47 analytes detected in 

samples from both sampling periods. Only two analytes were 

not detected in any samples: the SVOCs, hexachlorobenzene 

and diethyl phthalate. PAH detection frequencies above the 

optimal censoring threshold for each analyte ranged from 3 to 

64 percent for parent PAHs and 0 to 33 percent for alkylated 

PAH groups; because of variable reporting limits, there were 

some indeterminate samples (table 20). Figure 4C shows 

an example of the concentration distribution observed in 

sediment samples for the alkylated PAH group, C3-alkylated 

fluorenes. The reporting levels for C3-alkylated fluorene 

tend to be lower for post-landfall than pre-landfall samples, 

which means that uncensored detection frequencies will not 

provide a fair comparison of occurrence in the two sampling 

periods. After censoring at an optimal threshold of 1.8 μg/kg, 

the detection frequency for C3-alkylated fluorenes was higher 

in post-landfall samples at 15 percent than in pre-landfall 

samples, where it was 1 percent. 
Results and Discussion 65

Comparison of detection frequencies among 

contaminants with different reporting levels should be 

done at a common detection threshold (table 20). For 

example, the parent PAH, chrysene, was detected above its 

optimal censoring threshold of 0.23 μg/kg in 50 percent of 

post-landfall samples, compared to 33, 29, 21, and 13 percent 

of post-landfall samples for the C-1, C-2, C-3, and C-4 

alkylated chrysenes detected above their respective optimal 

censoring thresholds, which are 1.5, 1, 1, and 1.3 μg/kg. 

When a common detection threshold of 1.5 μg/kg was applied, 

the 29-percent detection frequency for chrysene was then 

comparable to detection frequencies for the C-1 and C-2 

alkylated chrysenes of 33 and 27 percent, respectively, and 

it was closer to those for C-3 and C-4 alkylated chrysenes, 

which were 19 percent and 10 percent, respectively. 

Thirteen PAHs—four parent and nine alkylated—were 

detected at or above concentrations of 1.5 μg/kg in more 

than 20 percent of post-landfall samples, whereas four parent 

PAHs were detected at or above the 1.5 μg/kg threshold 

in more than 20 percent of pre-landfall samples (table 20). 

Overall, PAH detection frequencies in sediment (table 20) 

tended to be higher than in water samples (table 17), which is 

expected because PAHs are hydrophobic and tend to sorb to 

organic material.

Comparison of Pre-Landfall to 

Post-Landfall Samples

Of 54 organic contaminants analyzed during both prelandfall and post-landfall sampling periods, and for at least 

80 whole-sediment samples, there were enough quantified 

detections above the optimal censoring threshold to make a 

statistical comparison of pre-landfall to post-landfall samples 

for 49 contaminants (table 21). Parent PAHs accounted for 

19 of these contaminants, and alkylated PAHs accounted for 

26 contaminants. Of these 49 contaminants, 22 showed a 

significant difference between pre-landfall and post-landfall 

samples in PPW tests (p<0.05; table 21). Concentrations 

were significantly higher in post-landfall samples for 

20 contaminants, which included 3 PAHs and 17 alkylated 

PAH groups, and in pre-landfall samples for two contaminants, 

naphthalene and oil and grease. The difference between 

concentrations in post-landfall and pre-landfall sediment 

samples (Cpost – Cpre) at individual sites along the GOM coast, 

from west to east, is shown in figures 5B to 5H for some 

example contaminants with significantly higher concentrations 

during one sampling period than the other. The examples 

in figures 5B–5F are PAHs that had significantly higher 

concentrations in post-landfall than pre-landfall samples; they 

represent various PAH ring structures and various degrees 

of alkylation. Figures 5G and 5H show naphthalene and 

oil and grease, respectively, for which concentrations were 

significantly higher in pre-landfall samples than post-landfall 

samples. For the three parent PAHs with significant PPW tests, 

chrysene, benzo[b]fluoranthene, and benzo[e]pyrene, there 

were high post-landfall sample concentrations at one site—

LA-26 (for example, see chrysene in fig. 5B). About 1.5 to 

2 times more sample pairs had a positive difference when 

subtracting pre-landfall samples from post-landfall samples 

than had a negative difference for these three PAHs, which is 

consistent with the significant test result. 

In contrast, the significant results for 15 of 17 alkylated 

PAHs reflected particularly high concentrations in postlandfall samples at seven sites: LA-28, LA-26, LA-31, MS-42, 

AL-8, AL-9, and AL-10 (for example, see figs. 5C–5F). Five 

of these sites showed post-landfall evidence of M-1 oil in 

sediment, tarballs, or both, on the basis of PAH fingerprinting 

by Rosenbauer and others (2010): Grand Isle Beach at State 

Park, Louisiana (LA-31); Petit Bois Island Beach, Mississippi 

(MS-42); and BLM-1 (AL-8), BLM-2 (AL-9), and Fort 

Morgan BLM-3 (AL-10) in Alabama. Notably, 16 of the 17 

alkylated PAHs with significantly higher concentrations in 

post-landfall samples were identified as relatively abundant 

components of weathered M-1 oil (State of Florida Oil 

Spill Academic Task Force, 2010). Chrysene and alkylated 

PAHs, however, are characteristic of petrogenic PAHs (those 

originating from petroleum and petroleum products) in general 

(Iqbal and others, 2008). 

For two sites, LA-28 and LA-26, with large 

positive differences in alkylated PAHs when pre-landfall 

concentrations were subtracted from post-landfall 

concentrations, there was no evidence of the M-1 oil 

fingerprint in the post-landfall sediment samples (Rosenbauer 

and others, 2010). The most abundant PAH compounds in 

these samples were consistent with pyrogenic sources, which 

result from combustion of organic matter and fossil fuels. In 

the LA-28 sample, the most abundant PAH compound was 

anthracene, which is produced during rapid, high temperature 

pyrosynthesis but does not persist during the slow diagenesis 

leading to the generation of fossil fuels (Iqbal and others, 

2008). In the LA-26 sample, the most abundant PAHs were 

fluoranthene and pyrene, and alkylated PAH concentrations 

were generally lower than the corresponding parent PAHs, 

which are characteristic of pyrogenic sources of PAHs. 

Table 20. Summary statistics for organic contaminants in sediment from the Deepwater Horizon oil spill, Gulf of Mexico, 2010.

This table is presented as a Microsoft© Excel spreadsheet. It can be accessed and downloaded at URL http://pubs.usgs.gov/

sir/2012/5228.
66 Contaminants in Water and Sediment Sampled in Response to the Deepwater Horizon Oil Spill Table 21. Statistical comparisons of contaminant concentrations in pre-landfall samples and post-landfall samples from the Deepwater Horizon oil spill, Gulf of Mexico, 2010: organic contaminants in sediment.—Continued [Significant p-values are shaded yellow (p<0.01) or orange (p<0.05). Abbreviations: g/kg, gram per kilogram; mg/kg, milligram per kilogram; n, number of pre-landfall and post-landfall sample pairs in PPW test; na, OC-normalization is not applicable; nd, optimal threshold not determined; ns, not significant at 0.05 level in a 2-sided test; OC, organic carbon; Post, post-landfall period; PPW, paired Prentice- Wilcoxon; Pre, pre-landfall period; μg/kg, microgram per kilogram; μg/g-oc, microgram per gram of sediment organic carbon; –, PPW test was not run; <, less than] Analyte Dry-weight concentrations OC-normalized concentrations3 Units Optimal censoring threshold1 Paired Prentice-Wilcoxon test Units Optimal censoring threshold1 Paired Prentice-Wilcoxon test

2

n p-value

Sampling period with 

significantly higher 

concentration

2

n p-value

Sampling period 

with significantly 

higher concentration

1-Methylnaphthalene μg/kg 0.4 44 0.6054 ns μg/g-oc 0.54 –4 – –

1-Methylphenanthrene μg/kg 0.38 45.5 0.0975 ns μg/g-oc 0.44 40 0.0696 ns26-Dimethylnaphthalene μg/kg 0.47 45.5 0.5378 ns μg/g-oc 0.56 43.5 0.1573 ns

2-Methylnaphthalene μg/kg 0.53 45 0.9755 ns μg/g-oc 0.64 –4 – –

Acenaphthene μg/kg 0.36 44.5 0.5983 ns μg/g-oc 0.48 45 0.9875 nsAcenaphthylene μg/kg 0.38 45.5 0.9505 ns μg/g-oc 0.46 45.5 0.1573 ns

Anthracene μg/kg 0.38 45.5 0.6515 ns μg/g-oc 0.46 45.5 0.581 ns

Benzo[a]anthracene μg/kg 0.25 42.5 0.7539 ns μg/g-oc 0.48 47 0.2561 nsBenzo[a]pyrene μg/kg 0.25 42.5 0.5311 ns μg/g-oc 0.48 47 0.111 ns

Benzo[b]fluoranthene μg/kg 0.23 47 0.0333 Post μg/g-oc 0.44 43 0.0512 nsBenzo[e]pyrene μg/kg 0.38 45 0.0219 Post μg/g-oc 0.72 41.5 0.0074 PostBenzo[ghi]perylene μg/kg 0.25 43.5 0.2264 ns μg/g-oc 0.5 45 0.1742 nsBenzo[k]fluoranthene μg/kg 0.4 45.5 0.3122 ns μg/g-oc 0.76 43 0.1257 nsBiphenyl μg/kg 0.47 45 0.3173 ns μg/g-oc 0.56 –4 – –

Bis(2-ethylhexyl) phthalate μg/kg 80 44 0.5816 ns μg/g-oc 110 44.5 0.3173 nsC1 Chrysene μg/kg 1.5 46 0.0037 Post μg/g-oc 1.7 45 0.0016 Post

C1 Dibenzothiophenes μg/kg 1 44.5 0.1727 ns μg/g-oc 1.7 45 0.1932 ns

C1 Fluoranthenes/pyrenes μg/kg 0.91 44 0.0187 Post μg/g-oc 1.7 45 0.0297 Post

C1 Fluorenes μg/kg 1.5 45.5 0.1573 ns μg/g-oc 1.7 –4 – –

C1 Naphthalenes μg/kg 1.3 44.5 0.1573 ns μg/g-oc 1.7 –4 – –C1 Phenanthrenes/anthracenes μg/kg 1.5 46 0.0224 Post μg/g-oc 1.7 45 0.0082 PostC2 Chrysenes μg/kg 1 44.5 0.0123 Post μg/g-oc 1.7 45 0.0027 Post

C2 Dibenzothiophenes μg/kg 1 44.5 0.0322 Post μg/g-oc 1.7 45 0.0191 Post

C2 Fluoranthenes/pyrenes μg/kg 1.3 45 0.0379 Post μg/g-oc 1.7 45 0.0101 PostC2 fluorenes μg/kg 1.3 44.5 0.0144 Post μg/g-oc 1.7 45 0.0254 Post

C2 naphthalenes μg/kg 0.91 44.5 0.6312 ns μg/g-oc 1.7 45 0.9875 nsC2 Phenanthrenes/anthracenes μg/kg 1 44.5 0.0091 Post μg/g-oc 1.7 45 0.0027 Post

C3 Chrysenes μg/kg 1 44.5 0.0136 Post μg/g-oc 1.7 45 0.0144 PostC3 Dibenzothiophenes μg/kg 1 44.5 0.0164 Post μg/g-oc 1.7 45 0.0176 Post

C3 Fluoranthenes/Pyrenes μg/kg 1.5 46 0.0358 Post μg/g-oc 1.7 45 0.0144 PostC3 Fluorenes μg/kg 1.8 46 0.0144 Post μg/g-oc 1.7 45 0.0254 PostC3 Naphthalenes μg/kg 0.91 44.5 0.6595 ns μg/g-oc 1.7 45 0.9875 nsC3 Phenanthrenes/anthracenes μg/kg 1 44.5 0.0024 Post μg/g-oc 1.7 45 0.0027 Post

Table 21. Statistical comparisons of contaminant concentrations in pre-landfall samples and post-landfall samples from the Deepwater Horizon oil spill, Gulf of Mexico, 2010: organic contaminants in sediment.
Results and Discussion 67

Table 21. Statistical comparisons of contaminant concentrations in pre-landfall samples and post-landfall samples from the Deepwater Horizon oil spill, Gulf of Mexico, 2010: organic contaminants in sediment.—Continued[Significant p-values are shaded yellow (p<0.01) or orange (p<0.05). Abbreviations: g/kg, gram per kilogram; mg/kg, milligram per kilogram; n, number of pre-landfall and post-landfall sample pairs in PPW test; na, OC-normalization is not applicable; nd, optimal threshold not determined; ns, not significant at 0.05 level in a 2-sided test; OC, organic carbon; Post, post-landfall period; PPW, paired PrenticeWilcoxon; Pre, pre-landfall period; μg/kg, microgram per kilogram; μg/g-oc, microgram per gram of sediment organic carbon; –, PPW test was not run; <, less than]

Analyte

Dry-weight concentrations OC-normalized concentrations3

Units

Optimal 

censoring 

threshold1

Paired Prentice-Wilcoxon test

Units

Optimal 

censoring 

threshold1

Paired Prentice-Wilcoxon test

2n p-value

Sampling period with 

significantly higher 

concentration

2n p-value

Sampling period 

with significantly 

higher concentration

C4 Chrysenes μg/kg 1.3 44.5 0.0144 Post μg/g-oc 1.7 45 0.0254 PostC4 Dibenzothiophenes μg/kg 1.8 46 0.0047 Post μg/g-oc 1.7 45 0.0082 PostC4 Naphthalenes μg/kg 1.2 44.5 0.0253 Post μg/g-oc 1.7 45 0.0254 PostC4 Phenanthrenes/anthracenes μg/kg 1.3 45 0.0041 Post μg/g-oc 1.7 45 0.0047 PostChrysene μg/kg 0.23 47 0.0033 Post μg/g-oc 0.44 43 0.0049 PostDibenzo[ah]anthracene μg/kg 0.38 45 0.7296 ns μg/g-oc 0.46 45 0.9875 nsDibenzothiophene μg/kg 0.38 45.5 0.1491 ns μg/g-oc 0.46 45.5 0.3173 nsFluoranthene μg/kg 0.26 47 0.649 ns μg/g-oc 0.5 45 0.7769 nsFluorene μg/kg 0.44 45 1 ns μg/g-oc 0.54 45 0.3173 ns

Indeno[123cd]pyrene μg/kg 0.23 45.5 0.5065 ns μg/g-oc 0.46 47 0.3389 nsNaphthalene μg/kg 0.29 40 0.0008 Pre μg/g-oc 0.56 45.5 0.0044 PreOil and grease mg/kg 110 45.5 0.0095 Pre μg/g-oc nd5 –5 – –

Organic carbon percent 0.1 44 0.2478 ns μg/g-oc na – – –

Perylene μg/kg 0.22 41.5 0.6748 ns μg/g-oc 0.44 43 0.9221 ns

Phenanthrene μg/kg 0.23 44 0.3913 ns μg/g-oc 0.44 43.5 0.9247 nsPyrene μg/kg 0.24 45.5 0.1712 ns μg/g-oc 0.48 47 0.2265 ns

1Lowest detection threshold at which the percentage of indeterminate samples is less than or equal to 5 percent. 2Non-integer indicates data missing for one member of a sample pair.3Normalized contaminant concentrations (in μg/g-oc) were calculated by dividing the censored contaminant concentration (μg/kg) by the sediment organic-carbon concentration (g/kg).4No detections remained after censoring at optimal censoring threshold.5Organic-carbon data is not available for a sufficient number of pre-landfall samples to determine an optimal censoring threshold or run PPW test on organic carbon-normalized data for this constituent.
68 Contaminants in Water and Sediment Sampled in Response to the Deepwater Horizon Oil Spill 

Naphthalene and oil and grease concentrations were 

significantly higher in pre-landfall sediment samples than 

post-landfall samples (table 21). Twenty-seven sample 

pairs have negative difference values when pre-landfall 

concentrations were subtracted from post-landfall 

concentrations, compared to only 5 pairs with positive 

difference values. Moreover, one site, LA-32, has a very large 

naphthalene difference value (fig. 5G). Similarly, oil and 

grease concentrations at 26 sites along the GOM coast had 

negative difference values when pre-landfall concentrations 

were subtracted from post-landfall concentrations, compared 

to 5 sites with positive difference values; concentrations 

in pre-landfill samples were substantially higher for sites 

LA-29, LA-22, LA-34, and AL-6 (fig. 5H). Oil and grease are 

operationally defined as hexane-extractable material, which 

includes relatively nonvolatile hydrocarbons, vegetable oils, 

animal fats, waxes, soaps, and greases (U.S. Environmental 

Protection Agency, 1998).

Because hydrophobic contaminants such as PAHs 

tend to be associated with organic carbon, it is possible that 

differences in the amount of organic carbon in pre-landfall 

and post-landfall samples could have caused or contributed 

to the significant differences in PAH concentrations. 

Therefore, the PPW tests were repeated after normalizing 

organic contaminant concentrations to the sediment-TOC 

content (table 21). Of the 20 PAHs with significantly higher 

concentrations in post-landfall samples, 19 continued to show 

a significant difference after organic-carbon normalization; 

the 20th had a p-value of 0.051, which is only slightly greater 

than the significance criterion of p<0.05. Sediment-TOC data 

were insufficient to normalize oil and grease concentrations; 

however, naphthalene concentrations were significantly 

higher in pre-landfall than in post-landfall samples even 

after organic-carbon normalization. Moreover, there was 

no significant difference in sediment-TOC content between 

the two sampling periods (table 21). These PPW test results 

indicate that the significant differences are not likely due to 

differing amounts of sediment-TOC in samples from prelandfall and post-landfall periods. 

The results of the present study, combined with direct 

evidence from the oil fingerprinting study by Rosenbauer and 

others (2010), indicate that M-1 oil could have contributed 

to the higher alkylated PAH concentrations measured at five 

sites, LA-31, MS-42, AL-8, AL-9, and AL-10, sampled in 

October 2010, relative to pre-landfall concentrations; however, 

other PAH sources, including other sources of oil, cannot 

be excluded. There are many possible sources of oil-related 

contaminants in the GOM, including natural oil seepage, 

which is estimated at about one million barrels of petroleum 

hydrocarbons each year; various oil spills from production 

operations, which contribute approximately 74,000 barrels 

each year; transportation accidents; and unburned engine fuel 

(Operational Science Advisory Team, 2010). A previous study 

of PAH sources along the Louisiana coast (Iqbal and others, 

2008) reported that approximately 50 percent of PAHs were 

from petrogenic sources; 36 percent were from pyrogenic 

sources; and 14 percent were from diagenetic sources, that 

is, the chemical or biological transformation of natural 

organic matter. 

Comparison with Benchmarks for Aquatic Life

The USEPA ESBTU benchmarks address the additive 

toxicity of PAH and BTEX compound mixtures in sediment 

(table 5D). As noted previously, ΣESBTUi

 values were 

calculated only for PAHs because BTEX compounds were 

not determined in sediment. One sediment sample exceeded 

the chronic ESBTU benchmark for PAH mixtures: the 

pre-landfall sample from Trinity Bay near Beach City, Texas 

(site TX-52). This site was outside the area of expected oil 

landfall and was not sampled during the post-landfall period. 

Notably, sediment-TOC concentrations in the present study 

were very low, having a median of 0.1 percent, which could 

affect bioavailability and potential toxicity. As previously 

noted, equilibrium-partitioning theory predicts PAH toxicity 

in sediments that have a TOC content of 0.2 percent or above 

(U.S. Environmental Protection Agency, 2002). 

Empirical screening values (table 5E) for 20 individual 

PAHs, 3 PAH mixtures, and 24 other SVOCs in sediment 

were used to classify sites into one of three categories: the 

minimal-effect, possible-effect, and probable-effect ranges. 

Of 165 sediment samples analyzed for organic contaminants 

that have benchmarks, 116 samples (70 percent) had no lower 

or upper screening values exceeded by any of the organic 

contaminants determined in the sample, so these were in 

the minimal-effect range where no adverse effects would 

be expected; 45 samples (27 percent) exceeded one or more 

upper screening values and so were in the probable-effect 

range, where there is a high probability of adverse effects 

on aquatic life; and only 4 samples (2 percent) were in 

the possible-effect range (table 19; appendix table 3-2). 
Results and Discussion 69

Twenty one out of 57 post-landfall samples (37 percent) 

exceeded one or more upper screening values compared to 

24 out of 108 pre-landfall samples (22 percent). The reverse 

pattern holds for samples where no screening values were 

exceeded, so that no adverse effects are expected, which 

applied to 81 of 108 of pre-landfall samples (75 percent) 

and 35 of 57 post-landfall samples (61 percent). The only 

upper screening-value benchmarks exceeded were for PAH 

mixtures. Lower screening values were exceeded by PAH 

mixtures, a few individual PAHs, and occasionally by bis(2-

ethylhexyl)phthalate. Although three PAH compounds 

(benzo[g,h,i]perylene, indeno[1,2,3-cd]pyrene, and perylene) 

were detected in laboratory reagent blanks associated with 

two post-landfall samples, it is unlikely that any incidental 

contamination contributed to benchmark exceedances for 

these two samples. Neither of these two samples exceeded the 

ESBTU for total PAHs, and only one empirical benchmark—a 

lower screening value for perylene—was exceeded by one of 

these samples. On the other hand, four organic contaminants 

with benchmarks had less than 50 percent recovery from 

matrix spikes, so their concentrations and contribution to 

benchmark exceedance could be biased low. These were 

acenaphthylene and naphthalene, which are PAH compounds 

included in the ESBTU; 1,2,4-trichlorobenzene, which had no 

benchmark exceedances; and N-nitrosodiphenylamine, which 

was not evaluated because the benchmark was below the 

reporting level. 

For the five sites identified as having possible 

contributions to alkylated PAH concentrations from M-1 oil—

LA-31, MS-42, AL-8, AL-9, and AL-10—PAH concentrations 

did not exceed ESBTU benchmarks. Chronic ∑ESBTUi values 

in post-landfall samples from these sites ranged from 0.17 to 

0.29 and so were below the hazard index of 1; this indicates 

that PAH levels in these post-landfall samples were not high 

enough to cause toxicity to benthic organisms according to 

these criteria. On the other hand, these samples did exceed 

empirical upper screening-value benchmarks for total PAHs, 

indicating a high probability of toxicity to benthic organisms 

at these sites as indicated by other field studies (MacDonald 

and others, 2000; Ingersoll and others, 2001).

Because of differences in how various benchmarks are 

derived, it is not surprising that empirical benchmarks were 

exceeded more often than the ESBTU benchmarks. The 

empirical, upper screening values are probabilistic—they 

are associated with frequent occurrence of toxicity in field 

sediments, which often contain mixtures of contaminants. 

Exceedance of an empirical benchmark is an indicator 

that toxicity is likely; it does not guarantee toxicity, and 

concentrations above the benchmark do not necessarily cause 

toxicity. In contrast, the ESBTU benchmark is causally based 

and designates concentrations expected to result in PAHinduced toxicity to benthic organisms. 

Direct comparison between benchmark-exceedance 

frequencies for pre-landfall and post-landfall sampling 

periods must be qualified because, as noted previously, data 

from the two sampling periods do not represent exactly the 

same sites: 22 pre-landfall sites in Florida and Texas and 

1 post-landfall site in Louisiana were only sampled during 

one sampling period (table 1). Also, 20 of the 71 total sites 

were sampled more than once during one or both sampling 

periods. Differences in benchmark exceedances, however, 

were evaluated for the paired-sample dataset, which 

excludes exceedance data for field replicate samples and 

for sites sampled during only one period. Fisher’s exact 

test indicated there was no significant difference in the 

benchmark-exceedance frequency between pre-landfall and 

post-landfall samples in this dataset (p>0.05). This was true 

for exceedance of both upper and lower screening-value 

benchmarks. When chronic ∑ESBTUi values for paired prelandfall and post-landfall samples were compared, there was 

no significant difference between the two sampling periods 

(sign test, p>0.05). 

Trace and Major Elements and Nutrients 

in Water 

For trace and major elements and nutrients in water, 

the USGS NWQL analyzed pre-landfall samples, and 

TestAmerica Laboratory in Florida analyzed post-landfall 

samples. For some trace elements and nutrients, the method 

used to analyze pre-landfall samples by the USGS NWQL was 

more sensitive than the method used for post-landfall samples 

by TestAmerica Laboratory in Florida. 

Constituent Occurrence

The detection frequencies and percentile concentrations 

for trace and major elements and nutrients in beach water 

samples are shown in table 22. Detection frequencies are 

provided for a series of detection thresholds because a 

common detection threshold must be applied when comparing 

detection frequencies between pre-landfall and post-landfall 

samples or for two different constituents. Reporting levels 

for trace elements in water were highly variable because 

77 percent of water samples were diluted prior to trace 

element analysis, at least in part because of high specific 

conductance values. 

Table 22. Summary statistics for trace and major elements and nutrients in water from the Deepwater Horizon oil spill, Gulf of Mexico, 

2010.

This table is presented as a Microsoft© Excel spreadsheet. It can be accessed and downloaded at URL http://pubs.usgs.gov/

sir/2012/5228.
70 Contaminants in Water and Sediment Sampled in Response to the Deepwater Horizon Oil Spill 

Several patterns of trace-element occurrence were 

observed. Uncensored detection frequencies for many 

constituents tended to be higher in pre-landfall samples than 

in post-landfall samples. For some constituents, however, 

this simply reflects the lower reporting levels used to analyze 

these constituents in pre-landfall samples. When data were 

censored to a common reporting level, detection frequencies 

and concentrations were similar (table 22). For example, 

zinc concentrations detected in pre-landfall water samples 

(filled circles in fig. 4D) were generally below the laboratory 

reporting levels for post-landfall samples (unfilled squares in 

fig. 4D). However, after censoring at the optimal censoring 

threshold of 80 μg/L, the detection frequencies for zinc in 

water samples from the two sampling periods were the same 

at about 2 percent (table 22). Additional examples of this 

pattern were found with lead, which was detected above a 

threshold of 20 μg/L in 2 to 3 percent of samples from both 

sampling periods, and iron, which was detected above a 

threshold of 500 μg/L in 41 to 42 percent of samples from 

both periods. Molybdenum in water (fig. 4E) showed a 

different pattern, in which uncensored detection frequencies 

were higher in pre-landfall samples than post-landfall samples, 

but the concentration distribution was higher in post-landfall 

samples. After censoring to the optimal threshold of 20 μg/L, 

the molybdenum detection frequency was actually higher 

in post-landfall samples, at 8 percent, than in pre-landfall 

samples, where it was 0 percent. Aluminum and manganese 

also showed greater detection frequencies above their 

respective optimal censoring thresholds in post-landfall 

than pre-landfall samples. The nutrients, phosphorus and 

ammonia, were more frequently detected in pre-landfall than 

post-landfall samples, even after censoring to a common 

detection threshold. Phosphorus concentrations (fig. 4F) in 

post-landfall water samples had to be blank-censored first 

to minimize the possibility that the detected concentrations 

were the result of incidental contamination. Because the 

blank-censoring procedure is intentionally conservative, 

this could have overestimated the extent of incidental 

contamination and thus lowered the post-landfall sample 

detection frequency. Similarly, ammonia plus organic nitrogen 

(fig. 4G) was blank-censored in post-landfall water samples 

because of detection in each of four field blanks for the postlandfall sampling period. The conservative blank-censoring 

procedure resulted in censored data with high reporting levels 

for all post-landfall samples. When detection frequencies were 

computed at the optimal censoring threshold of 2.4 mg/L as 

nitrogen (N), the ammonia detection frequencies were zero 

in both sampling periods. Barium, calcium, magnesium, 

potassium, and sodium were detected in 100 percent of both 

pre-landfall and post-landfall water samples, although some 

concentrations in post-landfall samples were higher than 

in pre-landfall samples (for example, potassium in fig. 4H; 

appendix 2–3). 

Comparison of Pre-Landfall to 

Post-Landfall Samples

Statistical comparisons of trace and major element and 

nutrient concentrations in water were made for 17 of the 

26 constituents determined in water during both study periods 

(table 23). The other nine constituents had no detections 

remaining after censoring, so no comparisons were made. 

The PPW test indicated significant differences between 

concentrations in pre-landfall and post-landfall water samples 

for nine constituents: six trace or major elements had higher 

concentrations in post-landfall samples, and three nutrients 

had higher concentrations in pre-landfall samples (table 23). 

Concentrations were higher in post-landfall samples for 

barium, calcium, magnesium, molybdenum, potassium and 

sodium. These are all elements in seawater (Turekian, 1968), 

and barium sulfate is a standard additive in drilling mud 

(Argonne National Laboratory and others, 2012). By using 

molybdenum as an example, figure 6A shows the difference 

in molybdenum concentrations in water between post-landfall 

and pre-landfall samples at individual sites along the GOM 

coast from west to east. Many sites had censored data for one 

or both samples; these are represented by bars that touch or 

cross the x-axis, that is, where y equals zero. Eighteen sites 

showed a positive difference when pre-landfall samples were 

subtracted from post-landfall samples, indicating higher postlandfall sample concentrations than pre-landfall, and six sites 

showed a negative difference, indicating the opposite. 

Three nutrients, ammonia as N, ammonia as NH4, and 

phosphorus, showed statistically significant differences 

(table 23), having higher detection frequencies (table 22) 

and higher concentrations in pre-landfall samples than postlandfall samples (for example, fig. 6B). Data were insufficient 

to assess ammonia plus organic nitrogen. Statistical 

comparisons were not significant for organic nitrogen and 

dissolved nitrogen (table 23).
Results and Discussion 71

Table 23. Statistical comparisons of contaminant concentrations in pre-landfall samples to those in post-landfall samples from the 

Deepwater Horizon oil spill, Gulf of Mexico, 2010: trace and major elements and nutrients in water.

[Significant p-values are shaded yellow (p<0.01) or orange (p<0.05). Abbreviations: A, No quantified detections remain above censoring threshold; B, no 

quantified detections remain after blank censoring; mg/L, milligram per liter; n, number of sample pairs; na, not applicable; nc, not censored because constituent 

was detected in all samples; nd, no quantified detections remained after blank censoring; NH4, ammonium cation; ns, not significant at 0.05 level in 2-sided test; 

PPW, paired Prentice-Wilcoxon; μg/L, microgram per liter; –, PPW test was not run; <, less than; ≤, less than or equal to]

Constituent Symbol or 

abbreviation Units

Optimal 

censoring 

threshold1

Paired Prentice-Wilcoxon test

Reason no 

PPW test 

was run 2

n p-value

Sampling period with 

significantly higher 

concentration

Aluminum Al μg/L 400 41.5 0.6963 ns na

Ammonia as N N (ammonia) mg/L as N 0.04 44.5 <0.0001 Pre-landfall na

Ammonia as NH4 N (ammonium) mg/L as NH4 0.0515 43 <0.0001 Pre-landfall na

Ammonia plus organic N N (Kjeldahl) mg/L 2.4 – – – A

Arsenic As μg/L 40 – – – A

Barium Ba μg/L nc 40 0.0001 Post-landfall na

Beryllium Be μg/L 10 – – – A

Cadmium Cd μg/L 10 – – – A

Calcium Ca mg/L nc 42 0.0122 Post-landfall na

Chromium Cr μg/L 20 40 0.3173 ns na

Cobalt Co μg/L 30 – – – A

Copper Cu μg/L 38 – – – A

Iron Fe μg/L 500 40 0.0692 ns na

Lead Pb μg/L 20 40 0.5834 ns na

Magnesium Mg mg/L nc 42 0.0024 Post-landfall na

Manganese Mn μg/L 10 40 0.073 ns na

Molybdenum Mo μg/L 20 40 0.0317 Post-landfall na

Nickel Ni μg/L 75 – – – A

Nitrogen, organic N (organic) mg/L 2.4 41.5 0.3173 ns na

Nitrogen, dissolved N (total) mg/L nc 41 0.8752 ns na

Phosphorus P mg/L as P 0.18 42 0.0046 Pre-landfall na

Potassium K mg/L nc 42 <0.0001 Post-landfall na

Selenium Se μg/L 40 – – – A

Silver Ag μg/L nd – – – B

Sodium Na mg/L nc 42 0.0007 Post-landfall na

Zinc Zn μg/L 80 40 0.9859 ns na

1

Lowest detection threshold that maximizes the number of quantifiable detections, minimizes the number of indeterminate samples, and has ≤7-percent 

indeterminate samples.

2

Non-integer indicates data missing for member of one sample pair.
72 Contaminants in Water and Sediment Sampled in Response to the Deepwater Horizon Oil Spill 

sac12-0452_Figure 6ab

CPOST MINUS CPRE,

IN MILLIGRAMS PER LITER AS N 

MAP NUMBER (WEST TO EAST)

TX-56

TX-55

TX-51

TX-53

TX-49

TX-47

LA-46

LA-25

LA-23

LA-28

LA-26

LA-24

LA-31

LA-36

LA-35

LA-32

LA-33

LA-29

LA-22

LA-30

LA-34

MS-43

MS-37

MS-38

MS-39

MS-44

MS-40

MS-41

MS-45

MS-42

AL-1

AL-2

AL-3

AL-4

AL-8

AL-5

AL-9

AL-10

AL-6

AL-7

FL-1

FL-2

FL-3

FL-4

FL-25

FL-5

FL-6

FL-7

–0.25

–0.2

–0.15

–0.1

–0.05

0

0.05

0.1

CPOST MINUS CPRE,

IN MICROGRAMS PER LITER 

MAP NUMBER (WEST TO EAST)

TX-56

TX-55

TX-51

TX-53

TX-49

TX-47

LA-46

LA-25

LA-23

LA-28

LA-26

LA-24

LA-31

LA-36

LA-35

LA-32

LA-33

LA-29

LA-22

LA-30

LA-34

MS-43

MS-37

MS-38

MS-39

MS-44

MS-40

MS-41

MS-45

MS-42

AL-1

AL-2

AL-3

AL-4

AL-8

AL-5

AL-9

AL-10

AL-6

AL-7

FL-1

FL-2

FL-3

FL-4

FL-25

FL-5

FL-6

FL-7

–10–15

–5

50

25201510

Maximum Minimum 

Gray bar indicatesmissing dataor no sample

Maximum Minimum 

Gray bar indicatesmissing dataor no sample

A Molybdenum in water

CPOST minus CPRE > 0 (p = 0.0317)

B Ammonia (as N) in water

CPOST minus CPRE < 0 (p = 0.0001)

Note: < is less than; > is greater than 

Figure 6. For selected analytes, difference between trace and major element and nutrient concentrations in samples collected during post-landfall and pre-landfall 

periods (Cpost minus Cpre) by the USGS at Deepwater Horizon oil spill sampling sites along the Gulf of Mexico coast, 2010, from west to east: (

A) molybdenum in water, 

(B) ammonia as N in water, (

C) lead in whole sediment, and (

D) lead in the less than 63-micrometer (<63-μm) sediment fraction.
Results and Discussion 73 sac12-0452_Figure 6cd

CPOST MINUS CPRE,

IN MILLIGRAMS PER KILOGRAM 

MAP NUMBER (WEST TO EAST)

TX-56

TX-55

TX-51

TX-53

TX-49

TX-47

LA-46

LA-25

LA-23

LA-28

LA-26

LA-24

LA-31

LA-36

LA-35

LA-32

LA-33

LA-29

LA-22

LA-30

LA-34

MS-43

MS-37

MS-38

MS-39

MS-44

MS-40

MS-41

MS-45

MS-42

AL-1

AL-2

AL-3

AL-4

AL-8

AL-5

AL-9

AL-10

AL-6

AL-7

FL-1

FL-2

FL-3

FL-4

FL-25

FL-5

FL-6

FL-7

–20–40–60–80

0

80604020

CPOST MINUS CPRE,

IN MILLIGRAMS PER KILOGRAM 

MAP NUMBER (WEST TO EAST)

TX-56

TX-55

TX-51

TX-53

TX-49

TX-47

LA-46

LA-25

LA-23

LA-28

LA-26

LA-24

LA-31

LA-36

LA-35

LA-32

LA-33

LA-29

LA-22

LA-30

LA-34

MS-43

MS-37

MS-38

MS-39

MS-44

MS-40

MS-41

MS-45

MS-42

AL-1

AL-2

AL-3

AL-4

AL-8

AL-5

AL-9

AL-10

AL-6

AL-7

FL-1

FL-2

FL-3

FL-4

FL-25

FL-5

FL-6

FL-7

–10–20–30–40–50

0

2010

Maximum Minimum 

Gray bar indicatesmissing dataor no sample

Maximum Minimum 

C Lead in whole sediment

CPOST minus CPRE < 0 (two-sided p = 0.0471)

D Lead in less than 63-micrometer sediment fraction

CPOST minus CPRE is not significantly different from 0 (p = 0.8291)

Note: < is less than

Figure 6.—Continued
74 Contaminants in Water and Sediment Sampled in Response to the Deepwater Horizon Oil Spill 

Comparison with Benchmarks for Human Health 

and Aquatic Life

U.S. Environmental Protection Agency (2010) 

recommended that concentrations of nickel and vanadium 

in water be compared to human-health benchmarks for 

recreational exposure. Neither was exceeded in any water 

samples collected in the present study, and recreational 

exposure-based human-health benchmarks were not available 

for other trace elements.

Aquatic-life benchmarks were available for 18 trace 

elements in water (table 6A). Benchmarks were identified 

from a number of sources, including USEPA and NOAA, 

and included both acute and chronic marine benchmarks. 

As noted previously, trace-element concentrations were 

converted from total to dissolved concentrations by the use 

of marine conversion factors from the U.S. Environmental 

Protection Agency (2011d). Acute aquatic-life benchmarks 

for one or more trace elements were exceeded in 23 of 

158 water samples (table 24A, appendix table 3-3), of which 

22 samples were from the post-landfall period and 1 was 

from the pre-landfall period; these samples with observed 

acute benchmark exceedances represent 39 percent of 

post-landfall samples and 1 percent of pre-landfall samples. 

The elements responsible for acute benchmark exceedances 

were copper in all 23 samples, and zinc in 2 samples. The one 

pre-landfall sample with exceedances was from Louisiana, 

whereas post-landfall samples with exceedances were found 

in all five states sampled. In addition, chronic aquatic-life 

benchmarks were exceeded by concentrations of one or 

more trace elements in 74 of 158 samples, including 22 of 

102 pre-landfall samples and 52 of 56 post-landfall samples; 

the samples with observed chronic benchmark exceedances 

represent 22 percent of total pre-landfall samples and 93 

percent of total post-landfall samples. Overall, boron exceeded 

the chronic benchmarks in 50 water samples, manganese in 

30, copper in 24, cobalt in 19, nickel in 7, lead in 6, barium 

in 3, zinc in 2, and vanadium in 1 water sample. The postlandfall sample from site LA-25, Rockefeller Refuge Beach, 

Louisiana, exceeded chronic benchmarks for eight trace 

elements, including nickel and vanadium; excluding this 

sample, the other post-landfall chronic benchmarks exceeded 

were for boron in 47 water samples, copper in 21, manganese 

in 11, and barium in 1 water sample. 

For trace elements in water, statistical comparison of 

the proportion of samples exceeding aquatic-life benchmarks 

between the pre-landfall and post-landfall sampling periods 

was precluded because of the highly variable reporting levels 

and the large number of censored values that had reporting 

levels greater than the applicable benchmarks. For example, 

of 40 post-landfall samples in the paired-sample dataset, 

1 sample exceeded the 8.1 μg/L aquatic-life benchmark 

for lead, 3 samples were less than this benchmark value, 

16 samples were reported as censored values of less than 

10 μg/L, and 20 samples were reported as censored values of 

less than 20 μg/L. The lead concentration could exceed the 

benchmark in none, some, or all of the 36 samples reported 

as having less than 10 or less than 20 μg/L of lead. The single 

benchmark exceedance observed for lead in post-landfall 

samples in the paired-sample dataset, therefore, represents 

the minimum number of exceedances of this benchmark 

for the 40 post-landfall samples, and the actual number of 

post-landfall samples with lead concentrations higher than 

8.1 μg/L in this dataset could be substantially greater—

theoretically, as few as 1 sample and as many as 37 of the 

40 post-landfall water samples could exceed the benchmark 

for lead. In this sense, the uncensored benchmark-exceedance 

frequencies presented in this report are essentially minimum 

exceedance frequencies; if the analytical methods used for 

post-landfall samples were more sensitive, it is possible that a 

greater number of benchmark exceedances would have been 

identified. For antimony, boron, and vanadium, comparisons 

to benchmarks were limited because these elements were 

analyzed largely during only one sampling period. For arsenic, 

cadmium, cobalt, copper, lead, nickel, and silver, benchmark 

exceedance could not be ascertained for between 35 and 

100 percent of samples during one or both sampling periods 

because concentrations were censored values at reporting 

levels that were higher than the applicable benchmarks. For 

the following analytes and sampling periods, therefore, the 

exceedance frequencies presented in this report could be 

substantially underestimated: antimony, boron, and vanadium 

in the pre-landfall period; arsenic, cadmium, cobalt, lead, 

nickel, and silver in the post-landfall period; and copper in 

both sampling periods. This is illustrated in figure 7, which 

shows the number of aquatic-life benchmark exceedances, 

by element and sampling period, for the 40 sample pairs in 

the paired-sample data set. The blue and red bars in figure 7A

represent the number of observed benchmark exceedances 

for a given element in pre-landfall and post-landfall 

periods, respectively. The height of each bar in figure 7A

represents the minimum number of exceedances for that 

element and sampling period because some samples had 

missing data or were censored at reporting levels too high 

to ascertain whether or not the benchmark was exceeded. 

In figure 7B, samples that are missing data (antimony, 

boron, and vanadium), or are censored values with reporting 

levels higher than the applicable benchmark, are assumed 

to be possible benchmark exceedances and are shown as a 

lighter colored segment in the stacked bar (lighter blue for 

pre-landfall samples and lighter red for post-landfall samples); 

the total height of the stacked bar represents the maximum 

number of exceedances possible for that element and sampling 

period. It is clear that several trace elements have reporting 

levels above the applicable benchmarks in a large number of 

samples, or were not analyzed in a large number of samples. 
Results and Discussion 75

Table 24A. Summary of benchmark and baseline exceedances for trace and major elements from the Deepwater Horizon oil spill, Gulf of Mexico, 2010: benchmark exceedances in water. [Abbreviations: B, boron; Ba, barium; Co, cobalt; Cu, copper; Mn, manganese; Ni, nickel; Pb, lead; V, vanadium; Zn, zinc; <, less than; –, no benchmarks exceeded]

State Number of sites Total number of samples1 Number of samples with benchmark exceedances Elements that exceeded benchmarks (number of samples) Human health Aquatic life: acute Aquatic life: chronic Aquatic life: acute Aquatic life: chronic

Pre-landfall sampling period

Texas 10 12 0 0 9 – Co (9), Pb (2), Mn (9), Ni (2)

Louisiana 15 19 0 1 9 Cu (1), Zn (1) Ba (1), Co (9), Cu (2), Pb (3), Mn (7), Ni (4), Zn (1)

Mississippi 3 3 0 0 1 – Co (1), Mn (1)

Alabama 9 13 0 0 3 – B (2), Mn (1)

Florida 26 55 0 0 0 – –

Total pre-landfall 63 102 0 1 22

Post-landfall sampling period

Texas 6 8 0 4 8 Cu (4) B (8), Cu (4), Mn (2)

Louisiana 16 18 0 7 14 Cu (7), Zn (1) Ba (2), B (10), Cu (7), Pb (1), Mn (7), Ni (1), V (1), Zn (1)

Mississippi 9 10 0 6 10 Cu (6) B (10), Cu (6), Mn (2)

Alabama 10 11 0 3 11 Cu (3) B (11), Cu (3), Mn (1)

Florida 8 9 0 2 9 Cu (2) B (9), Cu (2)

Total post-landfall 49 56 0 22 52

Total (all samples) 112 158 0 23 74

1The total number of samples includes field replicate samples, which typically were collected from a given site on the same date.
76 Contaminants in Water and Sediment Sampled in Response to the Deepwater Horizon Oil Spill Table 24B. Summary of benchmark and baseline exceedances for trace and major elements from the Deepwater Horizon oil spill, Gulf of Mexico, 2010: benchmark exceedances in whole sediment and national baseline exceedances in the less than 63-micrometer (μm) sediment fraction.

[Abbreviations: Al, aluminum; As, Arsenic; Ba, barium; Co, cobalt; Cr, chromium; Mn, manganese; SV, screening value; V, vanadium; –, no elements exceeded both upper SV benchmarks and national baselines; <, less than]

State Number of sites Total number of samples1

Number of whole-sediment samples in each range Upper SV benchmarks and national baselines exceeded for the same element5

Minimal 

effect 

range2

Possible 

effect 

range3

Probable 

effect 

range4

Number of samples 

exceeding both 

for any element 

Elements exceeding both 

(number of samples per element)

Pre-landfall sampling period

Texas 10 12 0 0 12 3 As (1), Ba (2), Co (1), Mn (1)

Louisiana 15 18 0 0 18 6 As (1), Ba (3), Mn (1), V (2)

Mississippi 9 11 8 1 2 0 –Alabama 10 10 9 1 0 0 –

Florida 26 32 25 6 1 0 –

Total pre-landfall 70 83 42 8 33 9

Post-landfall sampling period

Texas 6 9 0 0 9 0

Louisiana 16 24 0 0 24 10 Al (3), Ba (9), Cr (2), Mn (1), V (3)

Mississippi 9 9 8 0 1 0 –

Alabama 10 10 10 0 0 0 –

Florida 8 8 8 0 0 0 –

Total post-landfall 49 60 26 0 34 10

Total (all samples) 119 143 68 8 67 19

1The total number of samples includes field replicate samples. 2All constituent concentrations were below all applicable benchmarks; there is no indication of adverse effects on benthic organisms within this range.3One or more constituents exceeded a lower SV benchmark, but no elements exceeded an upper SV benchmark; adverse biological effects occasionally occur within this range.4One or more constituents exceeded an upper SV benchmark; adverse biological effects frequently occur within this range.5The listed elements exceeded one or more of their respective upper SV benchmarks in whole sediment, and also were enriched relative to national baseline concentrations from Horowitz and Stephens 

(2008).
Results and Discussion 77

PRE, Observed PRE, Maximum possible POST, Observed POST, Maximum possible 

0

5

10

15

20

25

30

35

40

Silver

Arsenic

Boron

Barium

Cadmium

Cobalt

Copper

Manganese

Nickel

Lead

Antimony

Vanadium

Zinc

Any TE 

Exclude B,V

NUMBER OF SAMPLES EXCEEDING BENCHMARKS 

PRE, Observed POST, Observed 

A

0

5

10

15

20

25

30

35

40

Silver

Arsenic

Boron

Barium

Cadmium

Cobalt

Copper

Manganese

Nickel

Lead

Antimony

Vanadium

Zinc

Any TE 

Exclude B,V

NUMBER OF SAMPLES EXCEEDING BENCHMARKS 

B

sac12-0452_Figure 07ab

Figure 7. Number of benchmark exceedances for trace elements in water in paired pre-landfall and post-landfall samples 

(N= 40) from the Deepwater Horizon oil spill, Gulf of Mexico, 2010: (A) observed number of exceedances, which ignores 

censored data and represents the minimum number of exceedances; (B) maximum number of benchmark exceedances 

possible, which assumes that all samples with censored reporting levels greater than the applicable benchmark are possible 

exceedances. B, boron; N, number of sample pairs in the dataset; POST, post-landfall samples; PRE, pre-landfall samples; TE, 

trace element; V, vanadium.
78 Contaminants in Water and Sediment Sampled in Response to the Deepwater Horizon Oil Spill 

Therefore, the number of benchmarks exceeded could 

be substantially higher than what was observed, so the 

benchmark exceedances observed in 47 percent of water 

samples represent the minimum number of exceedances for 

the samples collected in the present study. Furthermore, there 

is too much uncertainty to do statistical comparisons between 

sampling periods of benchmark exceedances for antimony, 

boron, vanadium, cobalt, copper, lead, nickel, arsenic, 

cadmium, and silver. For barium, manganese, and zinc, 

which were the only elements with sufficient data to make 

statistical comparisons, there were no significant differences 

in benchmark exceedances between paired pre-landfall and 

post-landfall samples (sign test, p>0.05).

Two of the elements with benchmark exceedances, 

boron and copper, were detected in one of four field blanks 

for the study, so their concentrations were blank-censored 

prior to comparison to benchmarks. The maximum boron 

concentration of 10 μg/L detected in blanks was less than 

1 percent of the benchmark value of 1,200 μg/L, indicating 

there is reasonable certainty that measured concentrations 

above the benchmark were not affected by incidental 

contamination. For copper, however, the maximum 

concentration of 2.2 μg/L detected in blanks was close 

to the chronic and acute aquatic-life benchmarks of 3.1 

and 4.8 μg/L, respectively. Therefore, measured copper 

concentrations were considered to be benchmark exceedances 

only when they exceeded 11 μg/L, or five times the maximum 

blank concentration. 

A total of seven samples exceeded chronic aquaticlife benchmarks for nickel, vanadium, or both, which were 

specifically identified by U.S. Environmental Protection 

Agency (2011a) as relevant to the Deepwater Horizon oil 

spill in the GOM. Of these seven samples, six were from 

the pre-landfall period and exceeded the chronic benchmark 

for nickel, and one sample from the post-landfall period 

exceeded chronic benchmarks for both nickel and vanadium 

(appendix table 3-3). Nickel benchmark exceedance could 

be substantially underestimated during the post-landfall 

period because the reporting level of 15 to 75 μg/L was too 

high to ascertain whether the chronic aquatic-life benchmark 

of 8.2 μg/L was exceeded. Vanadium was analyzed in all 

post-landfall samples but in only two pre-landfall samples.

The frequency at which aquatic-life benchmarks for 

one or more trace elements were exceeded—47 percent—in 

GOM water samples indicates there is potential for toxicity to 

aquatic life. Because of high and variable analytical reporting 

levels for trace elements in water, it was not possible to do 

a rigorous statistical comparison of benchmark exceedances 

between the pre-landfall and post-landfall sampling periods. 

Trace and Major Elements and Nutrients 

in Sediment 

Trace and major elements and the nutrients phosphorus 

and total nitrogen were analyzed in both whole sediment and 

the less than 63-μm sediment fraction, by the USGS SCL for 

both pre-landfall and post-landfall samples. Concentrations in 

whole sediment were used to assess contaminant occurrence 

and for comparison to sediment-quality benchmarks. 

Concentrations in the less than 63-μm fraction of sediment 

were compared to national baseline concentrations in 

bed sediments of rivers and streams from Horowitz and 

Stephens (2008). 

Constituent Occurrence

The detection frequencies and percentile concentrations 

for trace and major elements and nutrients in sediment are 

shown in table 25 for whole sediment and table 26 for the 

less than 63-μm sediment fraction. Because sediment samples 

were subjected to strong-acid digestion, which destroys the 

sediment matrix, the analyses yielded total trace-element 

concentrations (Horowitz and Stephens, 2008).

Detection frequencies for these constituents in whole 

sediment ranged from zero for thallium and uranium to over 

90 percent for barium, manganese, phosphorus, sodium, 

strontium, and sulfur in one or both sampling periods at a 

common detection threshold of 0.1 mg/kg (table 25). For 

almost all constituents, detection frequencies in pre-landfall 

and post-landfall samples were separated by about 10 percent 

or less at their optimal censoring thresholds (table 25). As 

examples, the concentration distributions in pre-landfall and 

post-landfall whole-sediment samples are shown for calcium 

and lead in figures 4I and 4J. Although calcium detection 

frequencies above the optimum censoring threshold were 

similar for pre-landfall and post-landfall samples, at 67 to 

68 percent, respectively, calcium concentrations appeared 

to be higher in post-landfall samples (fig. 4I). The opposite 

was true for lead, which had similar detection frequencies in 

Table 25. Summary statistics for trace and major elements and nutrients in whole sediment from the Deepwater Horizon oil spill, Gulf 

of Mexico, 2010.

Table 26. Summary statistics for trace and major elements and nutrients in the less than 63-micrometer sediment fraction from the 

Deepwater Horizon oil spill, Gulf of Mexico, 2010.

These tables are presented as Microsoft© Excel spreadsheets. They can be accessed and downloaded at URL http://pubs.

usgs.gov/sir/2012/5228.
Results and Discussion 79

both sampling periods but higher concentrations during the 

pre-landfall period (fig. 4J). Because whole-sediment samples 

were collected from the swash zone and analyzed without 

pre-treatment, dried sea salt could have contributed to the 

sodium, potassium, calcium, and magnesium concentrations 

measured in whole-sediment samples. 

Of nutrients, phosphorus was detected above 0.1 mg/kg 

in all pre-landfall and post-landfall whole-sediment samples 

(table 25), and the highest concentrations were in two prelandfall samples (fig. 4K). Total nitrogen was detected above 

its optimum threshold of 0.1 percent in 10 to 11 percent of 

both pre-landfall and post-landfall whole-sediment samples. 

Comparison of Pre-Landfall to 

Post-Landfall Samples

Statistical comparison of trace- and major-element and 

nutrient concentrations in whole sediment was performed for 

33 constituents, including total carbon and organic carbon. 

Six constituents showed a significant difference between 

pre-landfall and post-landfall samples in PPW tests (p<0.05) 

after censoring each element to its specific optimal censoring 

threshold (table 27). Concentrations were higher in postlandfall samples for calcium (fig. 4I), total carbon, sodium, 

and strontium, and in pre-landfall samples for lead (fig. 4J) 

and mercury. Using lead in whole sediment as an example, 

figure 6C shows the difference in concentrations when prelandfall concentrations were subtracted from post-landfall 

ones (Cpost – Cpre) at each sampling site along the GOM coast 

from west to east. Statistically higher lead concentrations 

in pre-landfall whole-sediment samples appeared to be 

influenced in part by a negative difference value, showing 

higher pre-landfall concentrations, at three sites in Louisiana, 

one extreme site in Mississippi, and two sites in Florida 

(fig. 6C). When pre-landfall concentrations were subtracted 

from post-landfall ones, 50 percent of sites had difference 

values that were negative; 23 percent had positive difference 

values; and 27 percent had difference values that equaled or, if 

the difference value was a range, included zero, so they could 

not be classified as definitively positive or negative. 

Because trace elements tend to be concentrated in the 

less than 63-μm fraction of sediment, it is possible that 

substantially different amounts of fine material in pre‐landfall 

and post-landfall samples could have contributed to the 

few significant differences in trace- and major-element 

concentrations that were observed. Therefore, the PPW 

tests were also performed on trace- and major-element and 

nutrient concentrations measured in the less than 63-μm 

fraction of sediment (table 27). Of the six elements that 

showed significant differences between sampling periods in 

whole sediment, none were significant in the less than 63-μm 

sediment fraction. Several factors could contribute to the lack 

of significant relationships in the less than 63-μm sediment 

data. First, the sample size was much smaller for this fraction, 

which had 15 to 16 sample pairs for nutrients and 21 to 35 for 

other elements, compared to 35 sample pairs for nutrients and 

44 to 48 for other elements in whole sediment; this reduced 

the power of the test for the less than 63-μm sediment fraction. 

Also, any dried sea salt present on whole-sediment samples 

would not remain in the less than 63-μm sediment fraction 

because the sediment samples were rinsed with deionized 

water during the sieving process. This would affect salts of 

major ions, such as calcium, sodium, and strontium. Finally, 

it is possible that significant differences in the constituent 

concentrations between post-landfall and pre-landfall samples 

actually were influenced by differences in the amount of fine 

material in these samples. 

Again, by using lead as an example, the difference in 

post-landfall and pre-landfall concentrations (Cpost – Cpre) at 

individual sampling sites for the less than 63-μm sediment 

fraction (fig. 6D) can be compared to the difference for whole 

sediment (fig. 6C). First, the most extreme difference value 

for lead in whole sediment (MS-44; fig. 6C) was no longer 

extreme in the less than 63-μm sediment fraction (fig. 6D). 

Both datasets had 50 percent of sites with a negative difference 

value when pre-landfall concentrations were subtracted from 

post-landfall ones; however, the less than 63-μm sediment 

fraction had a positive difference value at 37 percent of sites 

compared to 23 percent of sites for whole sediment, and 

difference values were indistinguishable from zero for 13 and 

27 percent of sites for the less than 63-μm fraction and whole 

sediment, respectively. The smaller sample size for the less 

than 63-μm fraction is illustrated in figures 6C and 6D also. 

Fine sediment data were missing for several sites, especially in 

Florida and Alabama (fig. 6D), because the sediment samples 

collected at these sites had insufficient mass in the less than 

63-μm fraction to run the trace-element analysis.

Overall, there was no significant difference in the percent 

of fine material contained in pre-landfall and post-landfall 

samples (table 27). To test whether site-specific differences 

in the percent of fine material contributed to differences in 

contaminant concentrations, the differences in contaminant 

concentrations in whole sediment between sampling periods 

(Cpost – Cpre) were regressed against the differences in the 

percentage of sediment that was less than 63 μm (LT63) 

between sampling periods (LT63post – LT63pre), in both 

cases subtracting pre-landfall values from post-landfall 

values. For lead and mercury, which had significantly higher 

concentrations in whole sediment pre-landfall samples 

than in post-landfall samples, the difference in constituent 

concentrations was significantly (p<0.05) related to the 

difference in fine material between the samples. Although 

not conclusive, this supports the hypothesis that site-specific 

differences in the amount of fine material in sediment 

samples could have contributed to the significantly higher 

concentrations of lead and mercury in pre-landfall compared 

to post-landfall whole-sediment samples. 
80 Contaminants in Water and Sediment Sampled in Response to the Deepwater Horizon Oil Spill Table 27. Statistical comparisons of contaminant concentrations in pre-landfall samples to those in post-landfall samples from the Deepwater Horizon oil spill, Gulf of Mexico, 2010: trace and major elements and nutrients in whole sediment and in the less than 63-micrometer (μm) sediment fraction.—Continued [Significant p-values are shaded bright yellow (p<0.01) or orange (p<0.05). Abbreviations: A, not detected in any samples; B, not detected at the optimal censoring threshold in any samples; md, data were missing for a large number of samples; n, number of pre-landfall and post-landfall sample pairs; mg/kg, milligram per kilogram; na, not applicable; nc, detected in every sample, so no censoring was necessary; nd, not detected in any samples; ns, not significant at 0.05 level in two-sided test; PLT63, percent of sediment sample that passes through a 63-μm sieve; post, post-landfall period; PPW, paired Prentice- Wilcoxon; pre, pre-landfall period; <, less than; –, PPW test was not run] Constituent or parameter Symbol or abbreviation Units Whole sediment Fine (<63-micrometer) sediment Optimal censoring threshold1 Paired Prentice-Wilcoxon test Reason no PPW test was run Optimal censoring threshold1 Paired Prentice-Wilcoxon test Reason no PPW test was run 2

n p-value

Sampling 

period with 

significantly 

higher 

concentration

2

n p-value

Sampling 

period with 

significantly 

higher 

concentration

Aluminum Al Percent 0.1 47 0.6710 ns na 0.3 34.5 0.5305 ns na

Antimony Sb mg/kg 0.1 47 0.4194 ns na 0.4 32.5 0.8818 ns naArsenic As mg/kg nc 48 0.3870 ns na nc 35 0.5516 ns na

Barium Ba mg/kg 1 47 0.3431 ns na nc 35 0.3144 ns naBeryllium Be mg/kg 0.1 47 0.9432 ns na 0.9 31 0.9940 ns naCadmium Cd mg/kg 0.1 46.5 0.6156 ns na 1.3 32.5 0.3173 ns naCalcium Ca Percent 0.1 47 0.0131 Post na 0.2 34.5 0.9697 ns na

Carbon, total C (total) Percent 0.1 48 0.0010 Post na nc 16 0.6384 ns naCarbon, organic C (organic) Percent 0.1 44 0.2478 ns na nc 15 0.8023 ns naChromium Cr mg/kg 2 48 0.9243 ns na 5 33.5 0.2190 ns naCobalt Co mg/kg 1 47 0.7000 ns na 10 32 0.9853 ns naCopper Cu mg/kg 1 47 0.4051 ns na nc 35 0.9420 ns naIron Fe Percent 0.1 47 0.3493 ns na 0.2 34.5 0.9574 ns na

Lead Pb mg/kg 1 48 0.0471 Pre na 3 30 0.8291 ns naLithium Li mg/kg 1 47 0.8672 ns na 7 34.5 0.9516 ns naMagnesium Mg Percent 0.1 47 0.8385 ns na nc 35 0.0349 Post naManganese Mn mg/kg 1 48 0.4877 ns na nc 35 0.0274 Pre na

Mercury Hg mg/kg 0.01 48 0.0450 Pre na 0.01 21.5 0.7717 ns naMolybdenum Mo mg/kg 1 46.5 0.5787 ns na 13 – – – B

Nickel Ni mg/kg 1 47 0.6200 ns na 2 34.5 0.6101 ns naNitrogen, total N (total) Percent 0.1 35 0.5415 ns na nc 16 0.5893 ns naPhosphorus

P mg/kg nc 35 0.1783 ns na 1 35 0.0624 ns na

Potassium

K Percent 0.1 47 0.6918 ns na 0.6 33 0.2753 ns na

Selenium Se mg/kg 0.1 46.5 0.5803 ns na 1.2 32.5 0.2998 ns na

Table 27. Statistical comparisons of contaminant concentrations in pre-landfall samples to those in post-landfall samples from the Deepwater Horizon oil spill, Gulf of Mexico, 2010: trace and major elements and nutrients in whole sediment and in the less than 63-micrometer sediment fraction.
Results and Discussion 81

Table 27. Statistical comparisons of contaminant concentrations in pre-landfall samples to those in post-landfall samples from the Deepwater Horizon oil spill, Gulf of Mexico, 2010: trace and major elements and nutrients in whole sediment and in the less than 63-micrometer (μm) sediment fraction.—Continued[Significant p-values are shaded bright yellow (p<0.01) or orange (p<0.05). Abbreviations: A, not detected in any samples; B, not detected at the optimal censoring threshold in any samples; md, data were missing for a large number of samples; n, number of pre-landfall and post-landfall sample pairs; mg/kg, milligram per kilogram; na, not applicable; nc, detected in every sample, so no censoring was necessary; nd, not detected in any samples; ns, not significant at 0.05 level in two-sided test; PLT63, percent of sediment sample that passes through a 63-μm sieve; post, post-landfall period; PPW, paired PrenticeWilcoxon; pre, pre-landfall period; <, less than; –, PPW test was not run]

Constituent or 

parameter

Symbol or 

abbreviation Units

Whole sediment Fine (<63-micrometer) sediment

Optimal 

censoring 

threshold1

Paired Prentice-Wilcoxon test

Reason no 

PPW test 

was run

Optimal 

censoring 

threshold1

Paired Prentice-Wilcoxon test

Reason no 

PPW test 

was run

2n p-value

Sampling 

period with 

significantly 

higher 

concentration

2n p-value

Sampling 

period with 

significantly 

higher 

concentration

Silver Ag mg/kg 0.5 46.5 0.3173 ns na nd – – – A

Sodium Na Percent 0.1 48 0.0006 Post na 0.5 33 0.3934 ns na

Strontium Sr mg/kg 1 48 0.0346 Post na nc 35 0.3713 ns naSulfur S Percent 0.01 48 0.3202 ns na nc 35 0.4003 ns na

Tin Sn mg/kg 1 47 0.2875 ns na 13 – – – B

Titanium Ti Percent 0.01 47.5 0.9421 ns na 0.03 31 0.7273 ns na

Uranium U mg/kg md – – – A 600 – – – B

Vanadium V mg/kg 1 47 0.6394 ns na nc 35 0.5479 ns naZinc Zn mg/kg 1 47 0.116 ns na nc 35 0.3091 ns naPercent of sediment <63-μm PLT63 Percent 1 46.5 0.8166 ns na na na na na na
82 Contaminants in Water and Sediment Sampled in Response to the Deepwater Horizon Oil Spill 

Comparison with Sediment-Quality Benchmarks 

and National Baseline Concentrations 

About 18 trace elements have one or more empirical 

sediment-quality benchmarks for protection of benthic 

organisms in whole sediment. Of 143 whole sediment 

samples, 67 samples (table 24B) from 28 sites exceeded one 

or more upper screening values for trace elements, placing 

these samples in the probable effect range; therefore, these 

samples have a high probability of adverse effects on benthic 

organisms. These samples included 33 of 83 pre-landfall 

samples and 34 of 60 post-landfall samples. Eight pre-landfall 

samples exceeded one or more lower screening values for 

trace elements, but no upper screening values, so were in 

the possible-effect range. The remaining 68 samples were 

in the minimal-effect range, indicating no adverse effects on 

benthic organisms would be expected. These results could be 

conservatively high estimates of potential toxicity because the 

present study measured total trace-element concentrations in 

sediment, rather than the bioavailable concentrations. 

The trace elements with one or more upper screeninglevel benchmark exceedances in whole-sediment samples 

were barium in 66 samples, aluminum in 34, manganese in 

24, vanadium in 17, cobalt in 7, arsenic in 2, and chromium 

in 2 samples. Trace-element concentrations exceeded 

one or more upper screening values in 40 percent of prelandfall samples and 57 percent of post-landfall samples. 

Fisher’s exact test indicated no significant difference in 

benchmark-exceedance frequencies between pre-landfall and 

post-landfall sampling periods for whole-sediment samples 

in the paired dataset. This was true for both upper and lower 

screening-value benchmarks. 

There were no blank or matrix spike QC data available 

for trace elements in sediment. However, the QC replicate 

data indicate high variability in the concentrations of four 

elements: magnesium, mercury, sodium, and tin. Summary 

statistics in table 25 and benchmark comparisons in table 23

are footnoted accordingly. 

Appendix table 3-4 also lists trace and major elements for 

which enrichment was found in the less than 63-μm sediment 

fraction, relative to national maximum baseline conditions. 

As noted previously, elements were considered to be enriched 

if their maximum baseline quotients exceeded 2 for samples 

with less than 1 percent material in the less than 63-μm 

sediment fraction, or 1 for all other samples. About 20 samples 

with less than 1 percent material in the less than 63-μm 

sediment fraction had insufficient material to do trace-element 

determinations. Of 124 samples analyzed for trace elements 

in the less than 63-μm sediment fraction, 81 had less than 

1 percent material in the less than 63-μm fraction and were 

compared to the quotient threshold of 2. All but one of these 

samples were enriched in at least one element. 

The use of national baselines to assess anthropogenic 

enrichment is based on the observation by Horowitz and 

Stephens (2008) that the upstream or underlying rock type had 

a minimal effect on trace- and major-element concentrations 

in streambed sediment nationally compared to the effects of 

land use or population density. There are regional differences 

in soil composition, however, that likely affect trace- and 

major-element concentrations in the less than 63-μm sediment 

fraction in the present study. Gustavsson and others (2001) 

reported total concentrations of trace and major elements in 

fine soil, defined as the less than 75-μm fraction of soil, across 

the U.S. These authors observed much lower concentrations 

in the less than 75-μm soil fraction for many elements in 

the Gulf Atlantic–Coastal Flats, which includes the Florida 

sites from the present study, than in many other parts of the 

country; this was attributed to an abundance of quartz sand 

in surficial soil, combined with the wet climate, which causes 

leaching of many elements from the upper soil horizons. 

These elements include arsenic, chromium, copper, lead, 

manganese, nickel, vanadium, and zinc. On the basis of the 

soil distributions observed by Gustavsson and others (2001), 

we would expect concentrations of these elements to be lower 

at Florida sites and some Alabama and Mississippi sites in 

the present study compared to sites in Texas and Louisiana. 

In fact, the concentrations of these elements reported by 

Gustavsson and others (2001) for most coastal soils in Florida, 

Alabama, and Mississippi were below the minimum baseline 

concentrations (that is, below the range of natural geochemical 

variation) in U.S. river sediment from Horowitz and Stephens 

(2008). In contrast, Gustavsson and others (2001) reported 

that soils in the Mississippi River Alluvial Plain contained 

the same elements at concentrations within their national 

baseline ranges from Horowitz and Stephens (2008); this area 

corresponds to the Louisiana and Texas sites in the present 

study. This indicates that comparison with maximum baseline 

concentrations will underestimate the degree of enrichment 

for our study sites in Florida and parts of Alabama and 

Mississippi, but is generally appropriate for sites in Louisiana 

and Texas. 

The baseline exceedance results can be considered, 

together with upper screening-value benchmark exceedances, 

to identify samples that combine enrichment above baseline 

with potential for toxicity (table 24B and appendix table 3-4). 

There were 122 sediment samples with trace-element data 

for both whole sediment and the less than 63-μm sediment 

fraction. Of these, 19 samples (16 percent) exceeded upper 

screening-value benchmarks for, and were enriched in, one or 

more of these elements: barium in 14 samples, vanadium in 

5, aluminum in 3, manganese in 3, arsenic in 2, chromium in 

2, and cobalt in 1 sample. These samples were evenly divided 

between sampling periods, with 9 pre-landfall samples and 

10 post-landfall samples, and were collected from 8 sites in 

Louisiana and 3 sites in Texas. 
Results and Discussion 83

Contaminant Concentrations at Sites with 

Macondo-1 Well Oil Fingerprint Evidence 

As noted previously, sediment and tarballs sampled 

by the USGS at 49 post-landfall sites and 69 pre-landfall 

sites were analyzed for diagnostic geochemical biomarkers 

by Rosenbauer and others (2010, 2011). In the Rosenbauer 

study, extracts from tarballs and from subsamples of the same 

composite sediment samples analyzed in the present study 

were compared to the chemical “fingerprint” of BP M-1 oil. 

The identification of M-1 well oil in the extracts was based on 

a combination of the interpretation of compounds identified 

in the mass spectra of sample extracts and a multivariate 

statistical analysis of the biomarker ratios by using hierarchal 

cluster analyses and principal component analyses. 

At pre-landfall sites, residues of oil—any oil—were 

found in sediment from 45 of 69 sites (65 percent of sites). 

None of these sediment samples correlated with the M-1 

oil, although a tarball collected from site FL-18 at Coco 

Plum Beach near Marathon, Florida, was similar to M-1 

oil (Rosenbauer and others, 2011). This pre-landfall tarball 

sample from site FL-18 was collected on May 24, which was 

6 days after NOAA reported on May 18 that a small tendril 

of M-1 well oil was in close proximity to the loop current 

(Lubchenco, 2010). 

In post-landfall samples, Rosenbauer and others 

(2010) found at least a trace amount of oil at 44 of 49 sites 

(90 percent), with evidence of M-1 oil in sediment, tarballs, 

or both, from 19 of the 49 sampled sites (39 percent). Of 

20 tarballs collected from 19 sites, all but 2 contained M-1 

oil. Five of the post-landfall sites likely contained a mixture 

of M-1 oil plus one or more other oils. These results indicate 

a high incidence of oil contamination at the post-landfall sites, 

with direct evidence of M-1 oil in sediment, tarballs, or both, 

at 19 sites. These 19 sites are identified in table 1 and figure 1. 

When PPW tests were run for all contaminants on the 

“fingerprint-sample” dataset, which was composed of prelandfall and post-landfall samples from only those 19 sites 

that had M-1 oil fingerprint evidence during the post-landfall 

period, the results were very similar to results for the pairedsample dataset. A few analytes with significant differences 

when using the paired-sample dataset were no longer 

significant when the fingerprint-sample data subset was used. 

Specifically, toluene, calcium, and molybdenum in water, and 

calcium in sediment, were no longer significantly higher in 

post-landfall samples when the smaller fingerprint-sample 

dataset was used. Similarly, lead had significantly higher 

concentrations in sediment during the pre-landfall period 

when using the paired-sample dataset, but not when using 

the fingerprint-sample dataset. The loss of significance for 

some analytes could be a result of the much smaller sample 

size in the fingerprint-sample dataset, which typically had 

14 to 18 sample pairs, compared to the entire dataset, which 

typically had 40 to 48 sample pairs. Although the 19 sites 

with direct evidence of M-1 oil landfall could be expected 

to show significantly higher contaminant concentrations 

in post-landfall samples for more analytes than in the full 

paired-sample dataset, this was not the case; again, the small 

sample size of the fingerprint-sample dataset limits the 

power of the test. There were three analytes for which the 

post-landfall concentrations were significantly higher than 

pre-landfall concentrations in the fingerprint-sample dataset 

but not in the full paired-sample dataset: two alkylated PAHs 

(1-methylphenanthrene and C1-alkylated dibenzothiophenes) 

and sulfur in sediment. In terms of potential toxicity, the most 

important difference between the two datasets is that toluene 

was no longer significant in the subset of 19 sites in the 

fingerprint-sample dataset. The principal conclusion from the 

PPW analysis, however, remains unchanged—concentrations 

of 20 PAHs, especially alkylated PAHs, were higher overall in 

post-landfall samples than pre-landfall sediment samples. Of 

the 19 post-landfall sites with M-1 oil, 5 sites had the largest 

difference in post-landfall minus pre-landfall concentrations 

for several PAHs. These sites are Grand Isle Beach at State 

Park, Louisiana (LA-31); Petit Bois Island Beach, Mississippi 

(MS-42); and BLM-1 (AL-8), BLM-2 (AL-9), and Fort 

Morgan BLM-3 (AL-10) in Alabama. 

Data Issues, Data Censoring, and Quality Control 

Because of the nature of this project—especially the 

emergency timing and the involvement of multiple agencies 

and organizations—there were a number of data issues that 

had to be resolved in order to do a technically sound analysis 

of the resulting data. This occurred because the pre-landfall 

sampling had to be done soon after the oil spill, before oil 

made landfall, and there were not yet recommendations in 

place concerning what analytes should be targeted and what 

methods should be used. Later, between the pre-landfall and 

post-landfall sampling periods, changes were made to the 

target analyte list and the chemical analysis methods used 

(Operational Science Advisory Team, 2010, appendix F), 

and these changes improved the number of oil-related 

contaminants with data for the post-landfall period. Data 

issues faced during the data analysis required for this report 

included large amounts of censored data, highly variable 

reporting levels for a given contaminant and sampling 

medium, duplicate analyses of the same sample that were 

either verifications by the same laboratory or re-analysis by 

a different laboratory, systematic differences in reporting 

levels between pre-landfall and post-landfall sampling 

periods, and differences between the two sampling periods 

in the contaminants that were analyzed. The complexity of 

data types and sources also created difficulties for database 

management that had to be resolved before data analysis 

could proceed; for example, there was incomplete information 

on parameters, methods, and data precision from contract 

laboratories. The importance of database management cannot 

be overemphasized, and the expertise and efforts of the USGS 

database managers were essential to compiling a dataset of 

optimized and documented data quality. All of the data issues 
84 Contaminants in Water and Sediment Sampled in Response to the Deepwater Horizon Oil Spill 

affecting this report were resolved, and are detailed in the 

sections on data analysis and data censoring. 

One primary tool for dealing with many of these issues 

was strategic data censoring, which was necessary so that the 

data coming from different sources and representing different 

sampling periods, sites, or laboratories were comparable 

and could be evaluated on equal grounds. Unfortunately, 

post-laboratory data censoring resulted in loss of information 

for some samples. 

Consistency of methods. The fact that, for some 

contaminants, different laboratories were used to analyze 

different samples contributed to a number of data issues. 

Different laboratories can use different methods and 

often have different reporting levels for the same analyte. 

The latter was especially problematic when there were 

systematic differences in reporting levels between the two 

sampling periods, as occurred in this study for both organic 

contaminants and trace elements in water. To compare results 

from pre-landfall and post-landfall sampling periods, data 

had to be censored at a common threshold, which resulted in 

loss of information from the sampling period with the more 

sensitive method. Different laboratories also had different 

analyte lists, and all contaminants that were determined in 

only one of the sampling periods had to be dropped from the 

comparison between sampling periods. 

Sample dilution. For trace elements in water, 77 percent 

of samples were diluted prior to analysis because the water 

samples exceeded the specific conductance or total dissolved 

solids thresholds for analysis by ICP-OES or ICP-MS. The 

dilution factor used for each sample depended on the degree 

to which the specific conductance or total dissolved solids 

threshold was exceeded. Because the reporting level increased 

proportionally with the sample-specific dilution factor, the 

sample dilution process resulted in high and variable reporting 

levels for trace elements in water in this study. This precluded 

statistical comparison between pre-landfall and post-landfall 

samples, and in many cases censored values were higher 

than the applicable aquatic-life benchmarks, which made it 

impossible to ascertain whether benchmarks were exceeded. 

The use of sample dilution could have been minimized, 

although not eliminated altogether, by better communication 

with the analyzing laboratories so that operating protocols 

were optimized for analysis of seawater. 

Quality control. Blank censoring was used to ensure 

that reported contaminant concentrations in environmental 

water samples were not affected by incidental contamination 

during sample collection, processing, or analysis. Because 

a limited number of blanks were collected during this study, 

a conservative approach had to be taken when censoring 

environmental-sample results on the basis of contamination 

in blanks. Detection of an analyte in any field or trip blank 

resulted in censoring of concentrations of that analyte in all 

environmental samples collected during the same sampling 

period. For some analytes, such as ammonia plus organic 

nitrogen and benzene in water, this resulted in the censoring 

of all quantified detections from the post-landfall sampling 

period. If more blank samples had been collected, perhaps 

the potential for incidental contamination in an individual 

environmental sample could have been represented by the 

concentration in a single corresponding blank, and fewer 

samples would have been subject to blank censoring. 

Target analytes. To obtain the most complete information 

on contaminant benchmark exceedances, water and sediment 

samples should be analyzed for trace elements and organic 

compounds, including PAHs, alkylated PAHs, and BTEX 

compounds. USEPA benchmarks for total PAH mixtures 

in water and sediment were designed to assess cumulative 

potential toxicity of 41 oil-related contaminants: 18 parent 

PAHs, 16 alkylated PAH groups, and 7 BTEX compounds 

(U.S. Environmental Protection Agency, 2011a and 2011b). To 

obtain the most complete estimate of potential PAH toxicity, 

all 41 target analytes that go into this benchmark should 

be determined. In the present study, alkylated PAHs were 

not analyzed in water samples or, initially, in pre-landfall 

sediment samples. Although alkylated PAHs can be estimated 

from parent PAH concentrations by using multipliers 

(Mount, 2010), this method can underestimate the total PAH 

benchmark toxic-unit value (∑ESBTU or ∑TU) when parent 

PAHs are not detected. The Operational Science Advisory 

Team (2010; appendix table C-3) tested the efficacy of the 

multiplier-based estimation method by calculating toxic-unit 

benchmarks in two different ways for samples with a full suite 

of analytes measured: they compared the results obtained by 

using data for 16 parent PAHs plus multipliers to the results 

obtained by using data for all 41 analytes. Although the toxicunit benchmarks obtained these two ways were correlated 

positively to each other, the relationship was not statistically 

significant (p>0.05). In the present study, this means that 

∑TU benchmarks for total PAH mixtures in water could be 

underestimated. For organic compounds in sediment, this 

omission was corrected by reanalyzing pre-landfall sediment 

samples for all 34 parent and alkylated PAHs. A second target 

analyte omission in the present study is that BTEX compounds 

included in the ∑ESBTU benchmark were not analyzed in 

sediment; therefore, ∑ESBTU values for sediment could be 

underestimated to some extent. At least for weathered oil, this 

low bias is likely to be minimal because the BTEX compounds 

are volatile and were not detected in a sample of weathered 

M-1 crude oil (State of Florida Oil Spill Academic Task Force, 

2010) or in surface oil samples approaching the near shore 

environment after the spill (Atlas and Haven 2011). 

These factors—use of different laboratories for prelandfall and post-landfall sampling periods, high and variable 

reporting levels, missing data for analytes that should be 

included in benchmark calculations, and collection of only a 

limited number of blanks—led to difficulties in data analysis 

and interpretation. These are lessons learned that can be the 

basis for improvements in the agency response to future oil 

spills or similar environmental emergencies. 
Summary and Conclusions 85

Summary and Conclusions

In response to the British Petroleum (BP) Deepwater 

Horizon Macondo-1 (M-1) oil spill on April 20, 2010, the 

U.S. Geological Survey (USGS) sampled beach water and 

sediment at 70 sites along the Gulf of Mexico (GOM) coast 

from May 7 to July 7, 2010, in order to establish baseline 

contaminant levels in potentially vulnerable locations before 

the oil made landfall. After the oil made landfall, a subset 

of 48 sites was resampled from October 4 to 14, 2010, and 

one new site was sampled on August 23, 2010, to assess the 

existence of actionable levels of M-1 oil contamination after 

the extensive clean-up efforts of coastal areas by BP (Wilde 

and Skrobialowski, 2011). This report characterizes the water 

and sediment chemistry in pre-landfall and post-landfall 

samples, evaluates whether there were significant differences 

between the two sampling periods, and compares measured 

concentrations to applicable benchmarks for human health and 

aquatic life.

Organics in Water

For organic contaminants in water, detection frequencies 

and concentrations were generally low and were similar in 

pre-landfall and post-landfall samples. Of the 11 compounds 

with enough quantified detections to statistically compare 

pre-landfall and post-landfall samples, concentrations were 

significantly higher for only one organic contaminant—

toluene—primarily as a result of detections in four postlandfall samples from Florida and one from Mississippi. 

No samples exceeded any human-health benchmarks for 

organic contaminants in water, which were available for 

11 compounds. Aquatic-life benchmarks, which were 

available for 73 compounds or mixtures of related compounds, 

were exceeded in only one water sample. The aquatic-life 

benchmarks for polycyclic aromatic hydrocarbons (PAHs) and 

benzene, toluene, ethylbenzene, xylene and related volatile 

(BTEX) compounds were exceeded in the post-landfall sample 

from the Mississippi River at South Pass, Louisiana (site 

LA-35); no exceedance was observed in the corresponding 

pre-landfall sample for this site.

Organics in Sediment

Most PAHs and alkylated PAHs, and a few additional 

semivolatile organic compounds (SVOCs), were detected 

in one or more samples during both pre-landfall and postlandfall periods. Nine alkylated PAHs and five parent PAHs 

were detected at concentrations greater than or equal to 

1.5 microgram per kilogram (μg/kg) in sediment at over 20 

percent of sites during one or both sampling periods, despite 

very low organic carbon content (for example, a median of 

0.1 percent) in the sampled sediments. 

Concentrations were significantly higher (p<0.05) in 

post-landfall sediment samples than pre-landfall samples for 

20 of the 49 organic contaminants with enough quantified 

detections to make statistical comparisons, consisting 

of 3 PAHs and 17 alkylated PAH groups. Two analytes, 

naphthalene and oil and grease, had higher concentrations 

in pre-landfall than post-landfall samples. The same results 

were obtained when PAH concentrations were normalized 

by sediment total organic carbon (TOC), indicating that the 

significant differences observed were not caused simply by 

differences in the sediment-TOC content between the two 

sampling periods. 

Only one sediment sample exceeded the chronic 

equilibrium-partitioning sediment benchmark toxic-unit 

concentration (ESBTU) for PAH mixtures—a pre-landfall 

sample from Trinity Bay near Beach City, Texas (site TX-52). 

This indicates that aggregate PAH concentrations were 

potentially toxic to benthic organisms at this site at the time 

of sampling. Because no post-landfall sample was collected 

at this site, no comparison can be made between sampling 

periods. Empirical benchmarks—upper screening values—

for PAHs were exceeded in 27 percent of sediment samples 

overall, indicating a high probability of toxicity to benthic 

organisms at the time of sampling, although not necessarily 

due to PAHs. These empirical benchmarks are based on 

past field studies in which similar PAH concentrations in 

sediments were associated with toxicity (MacDonald and 

others, 2000); because field sediments typically contain 

mixtures of contaminants, however, toxicity in these studies 

was not necessarily due to PAHs. The percentage of sediment 

samples that exceeded upper screening-value benchmarks 

was 37 percent for post-landfall samples and 22 percent for 

pre-landfall samples; there was no significant difference, 

however, in the proportion of sediment samples that exceeded 

one or more benchmarks for organic contaminants in sediment 

between paired pre-landfall and post-landfall samples. About 

70 percent of all sediment samples were below all empirical 

sediment-quality benchmarks for organic contaminants, 

indicating that no adverse effects on benthic organisms would 

be expected. Sediment sampled in this study typically had low 

organic carbon content, which could affect bioavailability and 

potential toxicity. 

For 15 of the 17 alkylated PAHs with statistically higher 

concentrations in post-landfall samples, 7 sites stood out as 

having the largest concentration differences. For five of these 

seven sites, M-1 oil was identified in post-landfall sediments, 

tarballs, or both, on the basis of diagnostic geochemical 

biomarkers (Rosenbauer and others, 2010): Grand Isle Beach 

at State Park, Louisiana (LA-31); Petit Bois Island Beach, 

Mississippi (MS-42); and BLM-1, BLM-2, and Fort Morgan 

BLM-3 in Alabama (AL-8, AL-9, and AL-10). These results 

indicate that M-1 oil could have contributed to the higher 

PAH concentrations measured in post-landfall samples at 

these five sites. For the seven post-landfall sediment samples 
86 Contaminants in Water and Sediment Sampled in Response to the Deepwater Horizon Oil Spill 

collected at these five sites, the chronic ∑ESBTU values 

calculated for PAH mixtures ranged from 0.2 to 0.3, and 

six samples, including at least one from each site, exceeded 

multiple upper screening-level benchmarks for total PAHs. 

In contrast, the nine pre-landfall sediment samples that were 

collected from these five sites had chronic ∑ESBTU values of 

less than 0.005, and no empirical screening-value benchmarks 

were exceeded.

Trace and Major Elements and Nutrients 

in Water 

Detection frequencies ranged from 0 to 100 percent, 

depending on the element or nutrient. It was essential 

to censor data to a common detection threshold prior to 

comparing concentrations and detection frequencies for 

different constituents or sampling periods because reporting 

levels varied by constituent and by laboratory. Of the 

17 trace and major elements with enough quantified values 

to make statistical comparisons, concentrations in water 

were significantly higher (p<0.05) in post-landfall samples 

for barium, calcium, magnesium, molybdenum, potassium, 

and sodium. These are all elements in seawater, and barium 

sulfate is a standard additive in drilling mud. Ammonia and 

phosphorus concentrations were significantly higher (p<0.05) 

in pre-landfall samples. 

Aquatic-life benchmarks were available for 18 trace 

elements in water. Acute and chronic benchmarks were 

exceeded in 1 percent and 29 percent, respectively, of 

pre-landfall water samples. Post-landfall water samples 

exceeded acute and chronic benchmarks in 21 percent and 

93 percent of samples, respectively. The elements that 

exceeded acute benchmarks in one or more water samples 

from either sampling period were copper in 23 samples 

and zinc in 2 samples. The elements that exceeded chronic 

benchmarks were boron in 50 water samples, manganese in 

30, copper in 24, cobalt in 19, nickel in 7, lead in 6, barium 

in 3, zinc in 2, and vanadium in 1 water sample. One or more 

exceedances occurred in every state except Florida during 

the pre-landfall period, and in all five states during the postlandfall period. Of the 56 post-landfall samples, 52 exceeded 

one or more chronic aquatic-life benchmarks for trace 

elements in water, with exceedances for boron in 48 postlandfall samples, copper in 22, manganese in 12, barium in 

2, and lead, nickel, vanadium, and zinc in 1 post-landfall 

water sample each. Because of high and variable analytical 

reporting levels for several trace elements in water, it was 

not possible to rigorously compare benchmark exceedances 

between the pre-landfall and post-landfall sampling periods. 

Overall, the frequency at which aquatic-life benchmarks for 

trace elements were exceeded in GOM water samples was 

47 percent, which indicates there is potential for toxicity to 

aquatic life. Moreover, exceedance frequencies for several 

trace elements could be substantially underestimated because 

either the element was analyzed during only one sampling 

period or exceedance could not be ascertained for samples 

that were censored at reporting levels higher than the 

applicable benchmark. Aquatic-life benchmark exceedance 

could not be ascertained for at least 35 percent of samples 

within a sampling period for boron and vanadium in the 

pre-landfall period; for arsenic, cadmium, cobalt, lead, 

nickel, and silver in the post-landfall period; and for copper 

in both sampling periods. Nickel and vanadium, which were 

specifically identified by U.S. Environmental Protection 

Agency (2011a) as relevant to the oil spill, were responsible 

for exceedances in only 1 of the 52 post-landfall samples 

with exceedances, although the results for nickel could be 

underestimated because of high reporting levels during the 

post-landfall period. 

Trace and Major Elements and Nutrients 

in Sediment 

Detection frequencies for trace and major elements 

and nutrients in whole sediment ranged from 0 to 

100 percent, depending on the constituent, and they were 

similar for pre-landfall and post-landfall samples. Because 

sediment samples were subjected to strong acid digestion, 

concentrations represent total concentrations in sediment, 

which are defined as greater than or equal to 95 percent of the 

amount present.

 A few trace and major elements had significant 

differences in concentration in whole sediment between 

post-landfall and pre-landfall samples; however, these 

differences were not significant when tests were run on the 

less than 63-micrometer (μm) sediment fraction. This is likely 

due, at least in part, to the smaller sample size of the less than 

63-μm sediment-sample dataset, although other factors also 

could have contributed to the lack of significance in tests on 

the less than 63-μm fraction. Sediment samples were rinsed 

with water during the 63-μm sieving process, which could 

have removed dried sea salt present in the whole-sediment 

samples; if so, this would decrease concentrations of calcium, 

sodium, and strontium. For lead and mercury, which were 

significantly higher in pre-landfall than post-landfall samples 

for whole sediment, but not for the 63-μm sediment fraction, 

a larger proportion of fine material (that is, less than 63 μm) 

in pre-landfall sediment samples compared to post-landfall 

samples at some sites could have contributed to the significant 

difference observed for whole-sediment samples. 
Acknowledgements 87

Empirical sediment-quality benchmarks were available 

for 18 trace elements in sediment. Overall, 47 percent of 

whole, unsieved sediment samples exceeded one or more 

upper screening values for trace elements (table 24B), 

putting these samples in the probable effect range. These 

samples included 33 of 83 pre-landfall samples and 

34 of 60 post-landfall samples . These results could be 

conservatively high estimates of benchmark exceedance 

because they are based on measurements of total traceelement concentrations in sediment. For trace elements in 

whole sediment, there was no significant difference in the 

proportion of samples exceeding one or more aquatic-life 

benchmarks between the pre-landfall and post-landfall 

sampling periods. For the less than 63-μm sediment fraction, 

all but 1 of 124 samples were anthropogenically enriched 

in one or more trace or major elements, relative to national 

baseline values for U.S. streams (Horowitz and Stephens, 

2008). Sixteen percent of sediment samples exceeded upper 

screening-value benchmarks for, and were enriched in, one 

or more of these elements: barium in 14 samples, vanadium 

in 5, aluminum in 3, manganese in 3, arsenic in 2, chromium 

in 2, and cobalt in 1 sample. These samples were divided 

evenly between the pre-landfall and post-landfall periods, 

and they were collected from 8 sites in Louisiana and 3 sites 

in Texas. However, because many trace elements have lower 

concentrations in soils from Florida, Alabama, and Mississippi 

than in soils from Louisiana and Texas (Gustavsson and 

others, 2001), the baseline comparison analysis probably 

underestimates the degree of enrichment at Florida, Alabama, 

and Mississippi sites.

Comparison of Pre-Landfall to 

Post-Landfall Samples 

Considering all the information evaluated in this report, 

there were significant differences between post-landfall and 

pre-landfall samples for PAH concentrations in sediment. 

With a few exceptions, pre-landfall and post-landfall 

samples did not differ significantly in concentrations or 

benchmark exceedances for most organics in water or trace 

elements in sediment. The one exception is toluene, which 

had significantly higher concentrations in post-landfall than 

pre-landfall water samples, although this difference was not 

necessarily related to landfall M-1 oil. Toluene is volatile 

and was not detected in weathered M-1 crude oil (State of 

Florida Oil Spill Academic Task Force, 2010) or in surface-oil 

samples approaching the near shore environment after the spill 

(Atlas and Haven, 2011). For trace elements in water, aquaticlife benchmarks were exceeded in 47 percent of samples 

overall, but the high and variable analytical reporting levels 

precluded statistical comparison of benchmark exceedances 

between sampling periods. Of the organic contaminants in 

sediment, 3 parent PAHs and 17 alkylated PAH groups had 

significantly higher concentrations in post-landfall samples 

than in pre-landfall samples. Concentrations above the 

upper screening-value benchmarks put 37 percent of postlandfall samples and 22 percent of pre-landfall samples in the 

probable-effect range. However, the proportion of samples 

exceeding empirical upper screening-value benchmarks for 

PAHs in sediment were not significantly different in paired 

post-landfall and pre-landfall samples. 

For 15 of the 17 alkylated PAHs with statistically 

higher concentrations in post-landfall samples, the greatest 

concentration differences were observed at seven sites. 

These results corroborate the results of Rosenbauer and 

others (2010), who found diagnostic geochemical evidence 

of Deepwater Horizon M-1 oil in post-landfall sediment and 

tarballs from five of these seven sites. The five sites are Grand 

Isle Beach at State Park, Louisiana (LA-31); Petit Bois Island 

Beach, Mississippi (MS-42); and BLM-1, BLM-2, and Fort 

Morgan BLM-3 in Alabama (AL-8, AL-9, and AL-10). 

Acknowledgements

The USGS initiated the pre-landfall sampling and 

analytical study, and additional funding was later provided 

by the U.S. Coast Guard for both the pre-landfall and postlandfall work. We gratefully acknowledge the efforts of 

the staffs of the USGS Water Science Centers in Alabama, 

Florida, Georgia, Louisiana, Mississippi, and Texas in sample 

collection and processing. We thank Marge Davenport, 

Charles Demas, Yvonne Stoker, Donna Myers, and Terry 

Schertz for their coordination efforts; Franceska Wilde 

and Stan Skrobialowski for development of the sampling 

protocol and other assistance; and Gary Cottrell for his 

efforts in coordinating the laboratory contracts. We thank 

Arthur Horowitz, Geoffrey Plumlee, and Ruth Wolf for data 

and technical assistance. We also thank Robert Burgess, 

Christopher Ingersoll, Donald MacDonald, and David Mount 

for technical guidance on benchmarks. We are grateful to four 

anonymous reviewers for their thoughtful reviews of an earlier 

version of the manuscript that greatly improved this report. We 

thank David Strong and Gregory Wetherbee for their work on 

the map in this report, and Wes Stone for technical assistance. 

We also thank the USGS Tacoma Publishing Service Center, 

and Carol Sanchez, Robin Miller, Larry Schneider, and Susan 

Davis of the USGS Sacramento Publishing Service Center, for 

their support in the publication of this report. 
88 Contaminants in Water and Sediment Sampled in Response to the Deepwater Horizon Oil Spill 

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Censored data A set of one or more 

censored values.

Censored value An analytical result 

determined to be below a specified threshold 

concentration and reported as a less-than 

value (for example, less than 3 when 3 is the 

threshold; see Censoring).

Censoring Application of a threshold to data 

such that concentrations above that threshold 

are quantified values and concentrations 

below that threshold are reported as less-than 

values (for example, less than 3, when 3 is 

the threshold). Censoring may be done at 

two stages of chemical data analysis: (1) by 

the laboratory because of high uncertainty 

in quantifying concentrations near the 

method detection limit, in which case the 

threshold is a reporting level, although for 

some methods, values that are below the 

reporting level but above the detection level 

could be quantified, but coded as estimates; 

(2) during data analysis because of blank 

contamination, in order to avoid interpreting 

incidental contamination in a sample as 

environmental contamination or to eliminate 

bias when comparing data, such as bias due to 

different method sensitivities, in which cases 

the threshold is a censoring level. This report 

describes three kinds of censoring levels: 

raised censoring levels, which are applied 

to contaminants detected in quality control 

blank samples; optimum censoring thresholds, 

which are applied for comparison of prelandfall and post-landfall sample groups; 

and common detection thresholds, which are 

applied for comparison among contaminants 

with different laboratory reporting levels.

Censoring level A concentration threshold 

that is applied to data such that concentrations 

above that threshold are quantified values 

and concentrations below that threshold are 

reported as less-than values (for example, less 

than 3).

Common detection threshold A censoring 

level applied to a group of analytes for 

the purpose of comparing among the 

analytes. This eliminated bias due to 

differences in method sensitivities for 

different contaminants.

Detection level A generic term for the 

lowest concentration that can be reliably 

quantified by a certain method at a 

certain laboratory.

Indeterminate sample A sample with an 

indeterminate value for a specified analyte.

Indeterminate value A censored value, that 

is, a result reported as less than a specified 

reporting level, where the reporting level is 

higher than the applied censoring threshold, 

so the value cannot be classified as either a 

detection or nondetection at that threshold. 

For example, an analyte concentration 

reported as less than 1 would be indeterminate 

at a censoring threshold of 0.2 because it is 

unknown whether the analyte is present at 

levels above 0.2.

Method detection limit (MDL) The 

minimum concentration of a substance that 

can be measured and reported with 99-percent 

confidence that the value is greater than zero 

(40 CFR Part 136).

Optimal censoring threshold The lowest 

censoring level that converts no more 

than 5 percent of results from censored to 

indeterminate values, maximizes the number 

of quantifiable detections and, if possible, 

also minimizes the number of indeterminate 

values. This was applied to concentrations 

of a given contaminant for the purpose of 

comparing pre-landfall and post-landfall 

sample groups.

Quantified value An analytical result 

measured above the reporting level and 

reported as a specific concentration. For 

some methods, such as those in which there 

is corroborative evidence of analyte presence 

in a mass spectrogram, an analytical result 

measured below the reporting level but above 

the detection level would be quantified, but 

coded as an estimate.

Parameter code Code for parameters 

in the USGS National Water Information 

System database (http://nwis.waterdata.usgs.

gov/usa/nwis/pmcodes); also called USGS 

parameter code. 

Glossary
Raised censoring level For contaminants 

detected in quality-control blanks, a censoring 

level higher than the reporting level that is 

applied to censor data in those environmental 

samples associated with the contaminated 

blanks, which minimizes the likelihood 

that detections of those contaminants in 

environmental samples are the result of 

incidental contamination. Typically, the 

raised censoring level is set at five times the 

maximum concentration determined in the 

applicable blanks or, for common laboratory 

contaminants, 10 times.

Reporting level The concentration, set by 

a laboratory, used for reporting analytical 

results that are determined to be less than the 

detection level. This could be higher than 

the detection level because analytical results 

at or near the detection level can have high 

uncertainty. The reporting level can vary 

because of factors such as matrix interference, 

low sample mass, or sample dilution.

94 Contaminants in Water and Sediment Sampled in Response to the Deepwater Horizon Oil Spill
Appendix 1. Methods, Reporting Levels, and Laboratories

Used for Chemical Analysis for the Deepwater Horizon Oil Spill, 

Gulf of Mexico, 2010

 Appendix tables and references are available for download in PDF format at http://pubs.usgs.gov/sir/2012/5228/.

Table 1-1. Methods, reporting levels, and laboratories used for chemical analysis for the Deepwater Horizon oil spill, Gulf of Mexico, 

2010: organic contaminants in water

Table 1-2. Methods, reporting levels, and laboratories used for chemical analysis for the Deepwater Horizon oil spill, Gulf of Mexico, 

2010: organic contaminants in whole sediment

Table 1-3. Methods, reporting levels, and laboratories used for chemical analysis for the Deepwater Horizon oil spill, Gulf of Mexico, 

2010: trace and major elements and nutrients in water

Table 1-4. Methods, reporting levels, and laboratories used for chemical analysis for the Deepwater Horizon oil spill, Gulf of Mexico, 

2010: trace and major elements and nutrients in whole sediment

Table 1-5. Methods, reporting levels, and laboratories used for chemical analysis for the Deepwater Horizon oil spill, Gulf of Mexico, 

2010: trace and major elements and nutrients in the less than 63-micrometer sediment fraction

Table 1-6. Methods used for chemical analysis in the Deepwater Horizon oil spill, Gulf of Mexico, 2010, study

Appendix 1. References Cited

Appendix 2. Data Distributions for Contaminants in Water and 

Sediment Sampled in Response to the Deepwater Horizon Oil 

Spill, 2010

 Appendix figures are available for download in PDF format at http://pubs.usgs.gov/sir/2012/5228/.

Appendix 2.1. Graphs showing data distributions for organic contaminants in water sampled in response to the Deepwater Horizon oil 

spill, 2010

Appendix 2.2 Graphs showing data distributions for organic contaminants in whole sediment sampled in response to the Deepwater 

Horizon oil spill, 2010

Appendix 2.3. Graphs showing data distributions for trace and major elements, nutrients, and specific conductance in water sampled 

in response to the Deepwater Horizon oil spill, 2010

Appendix 2.4. Graphs showing data distributions for trace and major elements in whole sediment sampled in response to the 

Deepwater Horizon oil spill, 2010

Appendix 2.5. Graphs showing data distributions for trace and major elements in the less than 63-micrometer fraction of sediment 

sampled in response to the Deepwater Horizon oil spill, 2010
96 Contaminants in Water and Sediment Sampled in Response to the Deepwater Horizon Oil Spill

Appendix 3. Benchmark Exceedances for Contaminants in

Water and Sediment Sampled in Response to the Deepwater 

Horizon Oil Spill, 2010

Appendix tables are presented as Microsoft© Excel spreadsheets. They can be accessed and downloaded at http://pubs.

usgs.gov/sir/2012/5228/.

Appendix 3.1. Benchmark exceedances for organic contaminants in water, by sample, from the Deepwater Horizon oil spill, Gulf of 

Mexico, 2010

Appendix 3.2 Benchmark exceedances for organic contaminants in sediment, by sample, from the Deepwater Horizon oil spill, Gulf of 

Mexico, 2010

Appendix 3.3. Benchmark exceedances for trace elements in water, by sample, from the Deepwater Horizon oil spill, Gulf of Mexico, 

2010

Appendix 3.4. Benchmark exceedances for trace elements in whole sediment and national baseline comparisons for trace and major 

elements and nutrients in the less than the 63-micrometer sediment fraction, by sample, from the Deepwater Horizon oil spill, Gulf of 

Mexico, 2010
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For more information concerning the research in this report, contact the

 Director, California Water Science Center

U.S. Geological Survey

6000 J Street, Placer Hall

Sacramento, California 95819

http://ca.water.usgs.gov
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