Assessing Transformation of Trace Metals and Crude Oil in Mississippi and Louisiana 
Coastal Wetlands in Response to the Deepwater Horizon Oil Spill 
 
by 
 
Jeffrey Paul Keevan 
 
 
 
 
A thesis submitted to the Graduate Faculty of 
Auburn University 
in partial fulfillment of the 
requirements for the Degree of 
Master of Science 
 
Auburn, Alabama 
August 4, 2012 
 
 
 
 
 
Copyright 2012 by Jeffrey Paul Keevan 
 
 
Approved by 
 
Ming-Kuo Lee, Chair, Professor, Department of Geology and Geography 
 James A. Saunders, Professor, Department of Geology and Geography 
Charles E. Savrda, Professor, Department of Geology and Geography  
 
 
 
 
 
 
 
 
 
ii 
 
 
 
ABSTRACT 
 
On April 20, 2010, the drilling rig Deepwater Horizon exploded in the Gulf of Mexico, 
resulting in the release of about 5 million barrels of crude oil into the environment. Coastal 
wetlands are particularly susceptible to oil contamination because they are composed largely of 
fine-grained sediments, which have a high capacity to adsorb oil and associated metals. 
Microbial activities may be enhanced by an increase in amounts of organic matter and 
subsequently influence the biogeochemical cycling of trace metals. This research assesses the 
levels of oil and trace metals, along with associated biogeochemical changes, in six coastal 
marshes in Mississippi and Louisiana.  
Total digestion analysis of wetland sediments shows higher concentrations of certain 
trace metals (e.g., Ni, Cu, Pb, Zn, Co, V, Ba, Hg, As) in heavily-oiled Louisiana sites (e.g., Nay 
Jimmy and Bayou Dulac) compared to those at less-affected and pristine sites. Due to chemical 
complexation among organic compounds and metals, crude oils often contain elevated levels (up 
to hundreds of mg/kg) of trace metals. At the heavily-oiled Louisiana sites (e.g., Bay Jimmy and 
Bayou Dulac), elevated levels of metals and total organic carbon were found in sediments down 
to depths of about 30 cm. The contamination is not limited to shallow sediments; oil, along with 
various associated metals, may be invading into deeper (pre-industrial) portions of the marsh 
sediments. Pore waters extracted from contaminated sediments are characterized by very high 
levels of reduced sulfur (up to 80 mg/kg). Microbial analysis of oiled sediments indicates that the 
influx of oil into the wetlands might have provided the additional substrate and carbon source for 
stimulating sulfate-reducing bacteria. Moreover, pore-water pH values show a general increasing 
iii 
 
trend (ranging from 6.6 to 8.0) with depth, possibly reflecting the combined effects of bacterial 
sulfate reduction and saltwater intrusion at depth. Despite high levels of trace metals in bulk 
sediments, concentrations of trace metals dissolved in pore waters are generally low. Pyrite-like 
iron-sulfides with distinct framboidal form are found in oiled sediments. Laser-ablation 
inductively coupled plasma mass spectrometer (LA-ICP-MS) analyses show that sulfide solids 
contain various levels of trace metals, including As, Hg, Pb, Cu, Zn, V, and Zn. Sulfide solids 
likely serve as local sinks for chalcophile (?sulfur-loving?) trace metals under sulfate-reducing 
conditions. It appears that high organic matter content and bacterially-mediated sulfate reduction 
facilitate metal retention via sulfide formation in the oiled marsh sediments.  
In addition to metals retention in sulfide solids, geochemical analyses show that residual 
oils remain in these wetlands up to months or possibly longer. High TOC and DOC levels (up to 
about 29% and 330 mg/kg, respectively), and low ?13C values of affected sediments, confirm the 
persistence of oil in these salt marshes. Gas-chromatograph mass-spectrometer (GC-MS) 
analyses of extracted organic contaminants show that only lighter compounds of the Macondo-1 
crude oil are quickly degraded, while the heavier components tend to remain in the environment 
months after the spill. The long-term biogeochemical effects of the remnant oil in the wetlands 
remains unclear, as does the possibility of re-oxidation of wetland sediments and metal sulfides. 
A potential effect would be the disaggregation of the solid sulfides and subsequent mobilization 
of sorbed trace metals. This possibility warrants further monitoring of affected wetlands. 
 
 
 
 
iv 
 
 
ACKNOWLEDGMENTS 
 
 
This project would not have been possible without research grants provided by the  
National Science Foundation and British Petroleum. I would like to extend my sincerest gratitude 
to my thesis advisor, Dr. Ming-Kuo Lee, for his patience, guidance, and support, for which this 
project would not have been possible. In addition, I would also like to thank my committee 
members, Dr. James Saunders and Dr. Charles Savrda, as well as the rest of the Auburn 
University Department of Geology and Geography faculty for their support over the last two 
years.  
Many others contributed to various facets of research and analyses related to this study, 
and their efforts are greatly appreciated. They include Drs. Alison Keimowitz, Benedict Okeke, 
Randall Clark, Yonnie Wu, Michael Meadows, Ahjeong Son, Scott Phipps, Just Cebiran, 
Charlotte Brunner, Munir Humayan and Yang Wang. Field sampling and laboratory sample 
processing were made possible by contributions from various people, including Michael Shelton, 
Eric Sparks, Robin Governo, Ada Cotto, and Joel Abrahams. I am extremely appreciative to the 
Auburn University Department of Geology and Geography for granting me a full Teaching 
Assistantship and to Dr. Lee for a summer Research Assistantship. 
 I would like to thank my friends and family for their support and understanding for my 
numerous absences throughout the past two years. I also would like to extend my deepest 
gratitude to my research partner Mike Natter for the many long hours toiled in the field and 
laboratory. Finally, I dedicate this thesis to the memory of my father.  
 
 
v 
 
 
 
 
 
 
 
TABLE OF CONTENTS 
 
 
Abstract ......................................................................................................................................... ii 
Acknowledgments ....................................................................................................................... iv 
List of Tables .............................................................................................................................. vii 
List of Figures ............................................................................................................................ viii 
Chapter 1. Introduction ................................................................................................................. 1 
Chapter 2. Background and Geologic Setting .............................................................................. 5 
            Wetlands  .......................................................................................................................... 5 
            Sample Sites  ..................................................................................................................... 6 
            Geologic Setting ............................................................................................................... 7 
            Geology and Biogeochemical Systems  .......................................................................... 20 
            Bacterial Processes in Geological Environments  .......................................................... 21 
            Organic Carbon ............................................................................................................... 24 
            Sedimentary/Framboidal Pyrite  ..................................................................................... 27 
            Trace Metals ................................................................................................................... 29 
Chapter 3. Methodology  ............................................................................................................ 30 
            Field Methods  ................................................................................................................ 30 
            Laboratory Methods  ....................................................................................................... 31 
Chapter 4. Results and Discussion   ............................................................................................ 40 
            Surface Water ................................................................................................................. 40 
vi 
 
            Pore-water Geochemistry ............................................................................................... 41 
            Sediment Characteristics (Grain Size and Mineralogy).................................................. 48 
            Sediment Geochemistry .................................................................................................. 56 
            Metal Enrichment in Wetland Sediments  ...................................................................... 68 
            Total Organic Carbon in Sediments  ............................................................................... 70 
            Petrographic, SEM, and LA-ICP-MS Analyses of Sulfide Solids ................................. 73 
            Microbial Communities in Affected Wetlands  .............................................................. 87 
            GC-MS Analysis of Bulk Oil and Petroleum Biomarkers  ............................................. 89 
            Carbon Isotopic Compositions  ....................................................................................... 98 
Chapter 5. Conclusions  ............................................................................................................ 103 
References   ............................................................................................................................... 107 
Appendix 1: DOC, Reduced Fe, and Sulfide Contents of Pore Waters .................................... 114 
Appendix 2: Distribution of Phi Size by Weight Percent in Sediments ................................... 117 
 
Appendix 3: Bulk Major Ion Compositions of Coastal Wetland Sediments. ........................... 119 
Appendix 4: Trace Metal Compositions of Coastal Wetland Sediments ................................. 122 
Appendix 5: TOC of Sediments, Carbon Isotopic Compositions of Bulk Sediments,               
Marsh Plants, Oil Sample Scrapped off the Oiled Plants, and BP MC-252 Oil. ...................... 128 
Appendix 6: Summary of Number of Positive Tubes in the SRB MPN Cultures .................... 131 
Appendix 7: Summary of Number of Positive Tubes in the IRB MPN Cultures  .................... 134 
 
 
 
 
vii 
 
 
 
 
LIST OF TABLES 
 
 
Table 1. Sample location information for Gulf marshes .............................................................. 6 
Table 2. Geochemical analyses performed on pore-water and sediment samples  ..................... 32 
Table 3. Surface water data collected via in-situ meters of TROLL 9000   ............................... 41 
Table 4. Grain size distribution in 0-3 cm sediments  ................................................................ 50 
Table 5. Grain size distribution in 12-15 cm sediments  ............................................................ 51 
Table 6. Grain size distribution in 27-30 cm sediments  ............................................................ 52 
Table 7. Average mineral composition of sediment samples from 0-3 cm interval ................... 55 
Table 8. Average mineral composition of sediment samples from 12-15 cm interval  .............. 55 
Table 9. Average mineral composition of sediment samples from 27-30 cm interval  .............. 55 
Table 10. Calculated average normalized enrichment factor (ANEF) of selected elements at 
various salt marsh sites  .............................................................................................................. 70 
 
Table 11. Elemental composition by percentage of SEM w/ EDAX analyses  .......................... 79 
Table 12. Average elemental concentrations of LA-ICP/MS analysis of pyrites from BD  ...... 86 
Table 13. Average elemental concentrations of LA-ICP/MS analysis of pyrites from BD  ...... 86 
Table 14. Average elemental concentrations of LA-ICP/MS analysis of pyrites from BJN  ..... 87 
Table 15. Biomarker ratios calculated from peaks of GC-MS spectra  ...................................... 98 
 
 
 
viii 
 
 
 
 
LIST OF FIGURES 
 
 
Figure 1. Gulf Coast marsh site location map .............................................................................. 4 
Figure 2. Photograph of sediment coring at Bayou Heron  .......................................................... 8 
Figure 3. Sampling location map of Bayou Heron  ...................................................................... 9 
Figure 4. Photograph of sediment coring at Point Aux Chenes Bay  ......................................... 10 
Figure 5. Sampling location map of Point Aux Chenes Bay  ..................................................... 11 
Figure 6. Photograph of sediment coring at Rigolets  ................................................................ 12 
Figure 7. Sampling location map of Rigolets  ............................................................................ 13 
Figure 8. Photograph of bulk sediment sampling at Bayou Dulac  ............................................ 14 
Figure 9. Sampling location map of Bayou Dulac  ..................................................................... 15 
Figure 10. Photograph of oiled marsh grass at Bay Batiste  ....................................................... 16 
Figure 11. Sampling location map of Bay Batiste  ..................................................................... 17 
Figure 12. Photograph of oiled marsh grass at Bay Jimmy North .............................................. 18 
Figure 13. Sampling location map of Bay Jimmy North ............................................................ 19 
Figure 14. Box plot of reduced iron in pore-waters  ................................................................... 42 
Figure 15. Box plot of reduced sulfur in pore-waters  ................................................................ 43 
Figure 16. Plot of reduced sulfur concentration with depth in Louisiana sites .......................... 44 
Figure 17. Plot of increased pH with depth in Louisiana sites  .................................................. 45 
Figure 18. Box plot and depth profile of Dissolved Organic Carbon in pore waters  ................ 47 
Figure 19. 0-3 cm sediment classification diagram  ................................................................... 50 
ix 
 
Figure 20. 12-15 cm sediment classification diagram  ............................................................... 51 
Figure 21. 27-30 cm sediment classification diagram  ............................................................... 52 
Figure 22. Box plot and depth profile of iron in sampled sediments  ......................................... 58 
Figure 23. Box plot and depth profile of sulfur in sampled sediments  ...................................... 59 
Figure 24. Box plot and depth profile of copper in sampled sediments  .................................... 59 
Figure 25. Box plot and depth profile of lead in sampled sediments  ........................................ 60 
Figure 26. Box plot and depth profile of zinc in sampled sediments  ........................................ 60 
Figure 27. Box plot and depth profile of nickel in sampled sediments  ..................................... 61 
Figure 28. Box plot and depth profile of cobalt in sampled sediments  ..................................... 61 
Figure 29. Box plot and depth profile of manganese in sampled sediments  ............................. 62 
Figure 30. Box plot and depth profile of arsenic in sampled sediments  .................................... 62 
Figure 31. Box plot and depth profile of thorium in sampled sediments  .................................. 63 
Figure 32. Box plot and depth profile of strontium in sampled sediments  ................................ 63 
Figure 33. Box plot and depth profile of vanadium in sampled sediments  ............................... 64 
Figure 34. Box plot and depth profile of phosphorous in sampled sediments  ........................... 64 
Figure 35. Box plot and depth profile of barium in sampled sediments  .................................... 65 
Figure 36. Box plot and depth profile of aluminum in sampled sediments  ............................... 65 
Figure 37. Box plot and depth profile of mercury in sampled sediments  .................................. 66 
Figure 38. Box plot and depth profile of calcium in sampled sediments  .................................. 66 
Figure 39. Box plot and depth profile of magnesium in sampled sediments  ............................. 67 
Figure 40. Box plot and depth profile of sodium in sampled sediments  ................................... 67 
Figure 41. Finer grain size / higher metal concentration correlation graph  ............................... 68 
Figure 42. Box plot and depth profile of Total Organic Carbon in sampled sediments  ............ 72 
x 
 
Figure 43. Higher TOC / higher metal concentration correlation graph .................................... 73 
Figure 44. Microphotographs of framboidal pyrites from Louisiana marsh sediments  ............ 75 
Figure 45. SEM/EDAX spectrum of framboidal pyrite from Bayou Dulac  .............................. 76 
Figure 46. SEM/EDAX spectrum of framboidal pyrite from Bayou Dulac  .............................. 77 
Figure 47. SEM/EDAX spectrum of framboidal pyrite from Bay Jimmy North  ...................... 78 
Figure 48. LA-ICP/MS results of framboidal pyrite analysis from Bayou Dulac  ..................... 82 
Figure 49. LA-ICP/MS results of framboidal pyrite analysis from Bayou Dulac  ..................... 83 
Figure 50. LA-ICP/MS results of framboidal pyrite analysis from Bayou Dulac  ..................... 84 
Figure 51. LA-ICP/MS results of framboidal pyrite analysis from Bay Jimmy North  ............. 85 
Figure 52. Gas chromatogram of BP Macondo-1 crude oil ........................................................ 93 
Figure 53. Fragmentograms of BP oil and degraded oil from Bay Jimmy plants ...................... 94 
Figure 54. Fragmentograms of oil from surface sediments in Bay Jimmy  ................................ 95 
Figure 55. Gas chromatogram of surface sediments in Bay Jimmy South ................................. 96 
Figure 56. Fragmentograms of oil from 12-15 cm deep sediments in BJS and BD ................... 97 
Figure 57. Isotopic histogram of oil, plant, and sediment samples .......................................... 101 
Figure 58. Box plot of ???C signatures in the sampling sites  .................................................... 102 
 
 
 
 
 
 
 
1 
 
 
 
INTRODUCTION 
 
 On April 20, 2010, an explosion engulfed the oil rig Deepwater Horizon in the Gulf of 
Mexico, leading to an unprecedented environmental oil spill of approximately 5 million barrels 
(Cleveland et al., 2010; Crone and Tolstoy, 2010). The Macondo-1 oil spill is regarded as the 
worst marine oil spill in the history of petroleum exploration. This spilled oil inundated many 
Gulf coastal wetlands, and its presence has had detrimental effects on the aquatic zones and 
ecosystems of coastal marsh areas. This situation is particularly dire along the Gulf coastal 
wetlands because they are ecologically and economically important. Wetlands are well-known 
natural filters of debris and pollutants derived from rivers, streams, and the atmosphere. Many 
trace metals (such as arsenic and mercury) transported by the river systems are deposited and 
trapped in the wetlands, reducing their potential to enter the water column and food chain. 
Arsenic and mercury are of particular concern, because in excess they are extremely toxic to 
wildlife and humans (Guo et al., 1997; Wright and Welbourn, 2002). 
Massive influxes of oil can increase microbial activity and enhance the mobilization and 
biotransformation of heavy metals such as arsenic and mercury. Arsenic can become mobilized 
through bacterial iron reduction (Islam et al., 2004; Saunders et al., 2008) of oxides, while 
bacterial sulfate reduction can cause methylation of mercury (Compeau and Bartha, 1984; 
Delaune et al., 2004). Methyl mercury (MeHg) and arsenic are bioaccumulated, and the risks 
associated with biotic accumulation underscore the necessity to understand their fate and 
transformation in coastal wetland sediments. The fate and transportation of toxic metals may 
2 
 
have an effect on aquatic and coastal ecosystems for many years, so a baseline assessment of 
metal concentrations is an important aspect of this study. 
Also of concern is the long-term persistence of oil in the wetland environment after the 
arrival of spilled oil from the BP Macondo-1 well. Crude oils and associated compounds change 
in chemical composition after their release in natural environments due to microbial degradation 
and various physiochemical processes (i.e., evaporation, dispersion, oxidation, and mineral 
adsorption). Oudot and Chaillan (2010) showed that heavy fractions of oil remained in the 
wetland environment decades after the Amoco-Cadiz oil spill. Generally, natural microbes will 
quickly digest the lighter compounds of oil, leaving heavier components (e.g., asphaltenes, 
resins, and polycyclic aromatics) in contaminated sediments. Total organic carbon (TOC) 
content in sediments and dissolved organic carbon (DOC) content in sediment pore waters tend 
to increase as a result of massive oil spills. DOC and TOC contents may be measured as a non-
specific indicator for the level of oil contamination and degradation.  
To assess and quantify the impact of the Deepwater Horizon oil spill on wetland 
sediments, field sampling was conducted in ten different Gulf Coast wetlands (Figure 1). The ten 
sites selected are located up to three states apart and ranged in their degree of contamination 
from pristine to heavily-oiled. The varying degrees of contaminated wetlands allowed for a broad 
assessment of the impact of the oil both geographically and according to the amount od 
inundation. Sediment cores, near-surface sediments, surface water, and vegetation were collected 
from each site in order to assess changes induced by oil contamination. This study focuses on 
samples collected from 6 of the 10 sampling sites: Bayou Heron (BH); Point Aux Chenes Bay 
(PACB); Rigolets (RG); Bayou Dulac (BD); Bay Batiste (BB); and Bay Jimmy North (BJN). 
These sites are located along the coasts of Mississippi and Louisiana.  
3 
 
This study seeks to test two major hypotheses: 1) high inputs of spilled oil leads to 
increased bacterial activity and biotransformation of heavy metals; and 2) natural microbes 
digest lighter oils quickly (within months) while the heavy and less degradable oil persists longer 
in the environment. In order to test these hypotheses, geological, geochemical, and microbial 
analyses were performed to characterize the sediments and pore waters collected from sampling 
sites. The main objectives of this research are to (1) analyze mineralogy and grain-size 
distribution of wetland sediments, (2) compare organic carbon contents in sediments and pore 
waters extracted from oiled and unaffected marsh sites, (3) assess geochemical profiles of 
sediments and pore waters and changes in microbial communities with depth, and (4) conduct 
geochemical biomarker and stable carbon isotope analyses to correlate organic matter recovered 
from oiled marshes to their initial sources.   
Since the sampling took place relatively soon (6 to 9 months) after the onset of the oil 
contamination, the results can provide baseline data for these sensitive wetlands that will be 
useful for developing long-term remediation and restoration strategies. The results of this study 
also will be of interest to communities that are located within the affected areas, as many of them 
could be directly affected by metal mobilization and oil incursion induced by the Deepwater 
Horizon explosion. 
 
 
 
 
 
 
4 
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 1. Sample location map showing ten wetland sampling sites along the coasts of Alabama, 
Mississippi, and Louisiana. White indicates no oil contamination, orange indicates moderate oil 
contamination, and red indicates heavy oil contamination. 
(http://www.tovima.gr/oldPhotos/Article%20Photos/20100528/334342.jpg) 
5 
 
BACKGROUND AND GEOLOGIC SETTING 
 
The explosion of the oil rig Deepwater Horizon on April 20, 2010 led to an 
unprecedented environmental disaster in the Gulf of Mexico. Approximately 5 million barrels of 
oil were released into the Gulf waters (Cleveland et al., 2010; Crone and Tolstoy, 2010; 
Rosenbauer et al., 2010). Many coastal wetlands were inundated and contaminated with this oil. 
Of special interest is whether the influx of oil and organic matter may enhance the mobilization 
and biotransformation of heavy metals such as arsenic and mercury. This alteration may have a 
lasting effect on aquatic and coastal ecosystems (Kiemowitz et al., 2010). To determine whether 
coastal oil inundation has caused any localized detrimental effects, several coastal wetlands, 
representing affected and unaffected sites, were sampled and analyzed for geochemical and 
microbial changes. 
 
Wetlands 
The six sites sampled for this study (Bayou Heron, Point Aux Chenes Bay, Rigolets, Bay 
Batiste, Bayou Dulac, Bay Jimmy North) are typical coastal salt marsh wetlands located along 
the Gulf Coast (Figure 1). Wetland environments are well-documented as sinks for metals 
derived from natural and anthropogenic sources (Guo, 1997; Wright and Welbourn, 2002). 
Because their physical makeup is primarily organic-rich fine-grained sediments, wetlands have 
the ability to retain high concentrations of metals. When these estuarine environments undergo 
geochemical changes, such as oxidation or reduction events, metals can be transformed or 
mobilized, leading to potential toxicity hazards for wildlife, and potentially, humans. 
 
6 
 
Sample Sites 
In all, ten marsh sites located along coastal wetlands of Alabama, Mississippi, and 
Louisiana were sampled for two separate theses research projects. The names and abbreviations 
of the sites, as well as their locations and sampling dates, are listed in Table 1. The sites range in 
their degree of contamination from pristine to completely oil immersed. Two sites from 
Mississippi (Bayou Heron and Point Aux Chenes Bay) and four sites from Louisiana (Rigolets, 
Bayou Dulac, Bay Batiste, and Bay Jimmy North) were ultimately chosen for this study to 
investigate biogeochemical changes within these distinct geographic areas. A parallel thesis 
project (Natter, 2012) focused on other coastal wetland sampling sites in Alabama and 
Louisiana. The sites chosen in this study represent some of the worst affected areas in 
Mississippi and Louisiana.  
 
 
Table 1.  Sample location information for Gulf marshes. 
 
Sampling  
Sites 
Sample 
ID 
Latitude 
(degree) 
Longitude 
(degree) 
Date  
Sampled 
Water Temp ?C 
      
Weeks Bay WB 30.413 87.831 10/19/10 22.8 
Longs Bayou LB 30.308 87.623 10/20/10 22.6 
Walker Island WI 30.288 87.541 10/20/10 23.0 
Bayou Heron BH 30.396 88.401 10/22/10 21.6 
Point Aux Chenes Bay PACB 30.335 88.451 10/22/10 23.1 
Rigolets RG 30.172 89.690 01/10/11 8.8 
Bayou Dulac BD 29.456 89.808 01/11/11 11.5 
Bay Batiste BB 29.472 89.831 01/11/11 10.4 
Bay Jimmy North BJN 29.454 89.885 01/13/11 6.6 
Bay Jimmy South BJS 29.445 89.891 01/13/11 7.2 
 
 
 
7 
 
Geologic Setting 
Grand Bay is located in the eastern portion of the Mississippi Sound. It receives its 
sediment inputs from nearby Mobile Bay. The drainage basin in this area is composed of small 
floodplains, swamps, and marshes (Greene et al., 2007). The geologic units surrounding Grand 
Bay are of Quaternary age and generally are made of loam, sand, gravel, and clay (Bicker, 1969). 
Barataria Bay is located along the southeastern Louisiana shore and is part of the 
Mississippi River delta. The basin is characterized by four primary sedimentary facies of 
Quaternary age: (1) a proximal ebb-tidal delta facies, (2) a distal ebb-tidal delta facies, (3) a near-
shore facies, and (4) an inner-shelf facies. Sediments deposited within these environments grade 
from sand to silt to silty clay. Sediments typically become finer upward and seaward. All of the 
facies include some mud (Fitzgerald et al., 2004). The presence of mud, or clay, is important, as 
heavy metals and organic matter tend to concentrate in fine-grained sediments that have high-
surface areas, which are conducive to metal sorption. With higher levels of organic matter, 
potential for mercury methylation (Hammerschmidt et al., 2004) and arsenic mobilization 
increases (Burnol et al., 2010). 
 
 
 
 
 
 
 
 
 
8 
 
Bayou Heron (BH) 
Bayou Heron (BH) is part of the larger Grand Bay area, located in eastern Mississippi. It 
is a part of the Mississippi Sound, which receives its sedimentation from nearby Mobile Bay. 
This site was sampled on October 22, 2010, at 20-cm water depth (Figure 2). The sampling site 
was located at latitude N 30? 23.732? and longitude W 88? 24.077? (Figure 3). Using a Google 
Earth layer which tracks all reports of locations of oil sightings post-Deepwater Horizon, Bayou 
Heron was determined to not have been affected by the oil spill and, on that basis, it stands as a 
control site for investigating the geochemical impacts in the Grand Bay area. Figure 3 shows the 
approximate geographic location of the sediment core/water sampling site. 
 
 
 
 
Figure 2. Photograph of sediment coring and surface-water sampling at Bayou Heron (BH), 
Mississippi. 
9 
 
 
 
Figure 3. Map of sediment-coring and water-sampling site for Bayou 
Heron (BH). 
10 
 
Point Aux Chenes Bay (PACB) 
   Like Bayou Heron, Point Aux Chenes Bay (PACB) is located within Grand Bay, which 
is ultimately part of the Mississippi Sound. Sediment cores and surface-water samples were 
collected from PACB (Figure 4) on October 22, 2010 at latitude N 30? 20.08? and longitude W 
88? 27.033? (Figure 5) at a water depth of 25 cm. In contrast to BH, PACB is open to the Gulf of 
Mexico. With no barriers protecting it, PACB was slightly contaminated with oil as tides carried 
oil toward shore. No visible oil was detected on the surface water at the time of sampling. 
 
 
 Figure 4. Photograph of sediment coring and surface-water sampling at Point Aux Chenes Bay (PACB), Mississippi. 
11 
 
 
 
Figure 5. Map of sediment-coring and water-sampling site at Point Aux Chenes Bay 
(PACB). 
12 
 
Rigolets (RG) 
 Rigolets (RG) is located in southeastern Louisiana, just outside (to the northeast) of the 
Barataria Bay Basin, where other Louisiana sampling was conducted. Rigolets is a narrow 
waterway situated between Lake Pontchartrain and the Gulf of Mexico. Its sediments consist 
largely of silt and clay, though some locations near barrier shorelines and deltaic progradations 
do host coarse-grained sediments (Flocks et al., 2009). The current natural sediment source for 
this area is derived from incoming rivers and shoreline erosion (Flocks et al., 2009). Sediment 
cores and surface-water samples were collected from RG (Figure 6) at latitude N 30? 10.346? and 
longitude W 89? 41.396? (Figure 7) at a water depth of 20 cm. This site was sampled on January 
10, 2011. Geochemical analyses (see sections below) indicate that this site was only mildly 
contaminated with oil. As the results show that other Barataria Bay sites were heavily affected, 
RG serves as a control site for comparison.  
 
Figure 6. Photograph of sediment coring and surface-water sampling at Rigolets (RG), 
Louisiana. 
13 
 
 
 
Figure 7. Map of sediment-coring and water-sampling site at Rigolets 
(RG). 
14 
 
Bayou Dulac (BD) 
Bayou Dulac (BD) is situated within the Barataria Bay Basin near where a stream meets 
with tidal water from a larger water body of Bay Batiste. As part of the Mississippi River delta, 
Bayou Dulac receives its sediment loads from the Mississippi River. Sediment cores and surface-
water samples were collected from BD (Figure 8) at latitude of N 29? 27.392? and longitude W 
89? 48.469? (Figure 9) on January 11, 2011. Water depth at this location was 10 cm. Bayou 
Dulac was reported as one of the worst contaminated salt marsh sites in Louisiana. Visibly oiled 
marsh grass was present at the site at the time of sampling. Bulk surface sediments collected at 
this site had a strong, almost overpowering, odor of hydrogen sulfide during the collection 
process, indicating prevailing sulfate-reducing conditions. Since BD is part of a narrow water 
inlet from Bay Batiste, it is probable that any oil that washed up in this area would have been 
trapped, as this narrow inlet is a more stagnant water body than Bay Batiste and experiences 
limited seawater flushing. 
 
Figure 8. Photograph of bulk sediment sampling in Bayou Dulac (BD), 
Louisiana. Slightly-oiled marsh grass can be seen in the background. 
15 
 
 
 
Figure 9. Map of sediment-coring and water-sampling site for Bayou Dulac 
(BD). 
16 
 
Bay Batiste (BB) 
Bay Batiste (BB) is situated within the Barataria Bay Basin, just west of Bayou Dulac. As 
part of the Mississippi River delta, Bay Batiste receives its sediment load from the Mississippi 
River. BB is protected from the open Gulf by the larger Barataria Bay, but it is still open enough 
to experience considerable seawater flushing, which could aid in removing oil. Sediment cores 
and surface-water samples were collected from BB at latitude N 29? 28.340? and longitude W 
89? 49.874? (Figure 11) on January 11, 2011. The samples were collected at 10-cm water depth. 
Though BB was reported as being heavily inundated with oil, only slight visible oil over dead 
marsh grass was seen at the time of sampling (Figure 10).  
 
  
Figure 10. Photograph of light accumulations of oil covering dead marsh grass at Bay Batiste (BB), 
Louisiana. All grass that had been removed in the foreground is presumed to have been inundated 
with oil. 
17 
 
 
  
Figure 11. Map of sediment-coring and water-sampling site for Bay Batiste 
(BB), Louisiana. 
18 
 
Bay Jimmy North (BJN) 
Bay Jimmy North (BJN) is located within the Barataria Bay Basin to the west of Bay 
Batiste and receives its sedimentation from the nearby Mississippi River. Sediment cores and 
surface water samples, in addition to bulk sediments and live and dead plants, were collected 
from BJN on January 13, 2011 at latitude N 29? 27.236? and longitude W 89? 53.512? (Figure 
13). Samples were collected at a water depth of 10 cm. BJN was reported as having received a 
significant amount of oil from the BP oil spill ? over 32,000 gallons of oil were removed during 
a 10-day period of cleaning (USA Today, 2010). Though BJN is open to Barataria Bay, a small 
island (BJS) bounds it to the south. Since oil was visibly present on the day of sampling (Figure 
12), covering dead plants along the shoreline, it is probable that accumulations of oil in BJN are 
not as easily flushed. Or, perhaps there was enough oil inundation that flushing by ocean waves 
was not complete at time of sampling.  
 
Figure 12. Photograph of heavily-oiled marsh grass and dead plants at Bay 
Jimmy North (BJN), Louisiana, extending several meters from the shoreline. 
19 
 
 
 
Figure 13. Map of sediment-coring and water-sampling site for Bay Jimmy North 
(BJN). 
20 
 
Geology and Biogeochemical Systems 
 The United States Gulf Coast region between Alabama to Louisiana is a unique area 
composed of Quaternary-aged alluvium deposited by numerous rivers distributing their sediment 
loads as they empty into the Gulf of Mexico. As these rivers aid in leveling much of the interior 
of the continent, they transform the coast into an area of natural complexity by transporting 
sediments, organic matter, and dissolved particles to the coastline. These sediments and 
dissolved loads interact with the environment to form unique and complex geologic, biologic, 
and geochemical systems. Many Gulf estuaries and coastal watersheds are highly susceptible to 
contamination by heavy metals, such as arsenic and mercury, that are extremely toxic to wildlife 
and humans (Guo, 1997; Wright and Welbourn, 2002). With increasing influx of organic matter 
from the oil spill, the complexities are amplified. Influx of high organic matter (OM) resulting 
from the oil spill may increase microbial activity, promote more strongly reducing conditions, 
and thereby affect the mobility and biogeochemical cycling of heavy metals in coastal wetlands 
(Keimowitz et al., 2005; Lee et al., 2005, 2007, 2010).  
Knowledge of hydrogeology, geochemistry, and geobiology is essential to understand 
key reactions that result in geochemical changes of sediments and pore waters. It has been shown 
in previous studies that mobilization and biological transformation of arsenic and mercury occur 
in strongly reducing environments via bacterial iron- and sulfate-reduction (Keimowitz et al., 
2005; Saunders et al., 2008; Merritt et al., 2009). The addition of oil can enhance these 
biogeochemical processes by providing organic carbon, which is the main energy source for 
bacteria.  
Moreover, nutrients and bio-stimulants used to decompose oils in mitigation also may 
stimulate microbial activities that impact mobility and natural cycling of metals in Gulf waters.  
21 
 
Although most light compounds of oil are considered biodegradable, saturated heavy oils, which 
represent about 60% of initial crude, can persist in contaminated wetlands for decades (Oudot 
and Chiallan, 2010). Thus, it is important to monitor the evolution of oil and its impact on the 
concentration, speciation, and mobilization of metals in impacted wetlands. When living 
organisms are exposed to Hg and As in aqueous environments, these elements are taken up by 
the organisms and then transformed/accumulated throughout the food chain. The impacts of the 
current oil spill on Gulf coastal watersheds could last for many years, even after the degradable 
oil on the surface is cleaned up.  
 
 
Bacterial Processes in Geological Environments 
  
 Bacterial activities can control the mobility and biogeochemical cycles of metals in 
various geological environments. Bacteria are unicellular organisms that are mostly invisible to 
the naked human eye. These microorganisms tend to form colonies referred to as microbial 
communities. These communities are found nearly everywhere in natural environments. They 
can be aerobic (require oxygen for respiration) or anaerobic (require substances other than 
oxygen for respiration). Bacteria aid greatly in the oxidation-reduction cycle by stripping 
electrons from an electron donor (oxidation) to derive energy for either substrate removal or cell 
synthesis. The redox cycle is completed by the free electron being paired up with an electron 
acceptor, resulting in that particular molecule being reduced.  This process can be either 
assimilatory or dissimilatory; assimilatory microorganisms incorporate the metal for use in 
enzymes and cellular components, whereas dissimilatory microorganisms oxidize organic 
compounds and funnel the electrons to metals that are located outside of the organism (Liermann 
et al., 2007). Bacteria can utilize multiple other elements (e.g., Fe, Mn, S, etc) aside from oxygen 
22 
 
as their terminal electron acceptor for respiration under various redox conditions. In wetlands, 
bacteria can be found in both terrestrial and aqueous environments, and they play an important 
role in the biogeochemical cycles of carbon and metals. Two primary types of bacteria of interest 
for this study are dissimilatory iron-reducing bacteria (FeRB) and sulfate-reducing bacteria 
(SRB). Dissimilatory bacteria oxidize organic compounds and pass the electrons through the 
electron-transport chain to metals that are located outside of the organism (Liermann et al., 
2007). 
 Iron-reducing bacteria are found in a multitude of environments, although in sulfate-rich 
marine environments they are outcompeted by sulfate-reducing bacteria (Madigan et al., 1997; 
Straub et al., 2000). One way they work is by oxidizing the electron donor (acetate or other 
short-chain fatty acids) to carbon dioxide, while utilizing ferric iron as the terminal electron 
acceptor (Champine and Goodwin, 1991; Lonergan et al., 1996). In this system, ferric iron 
(Fe(III)) is reduced to ferrous iron (Fe(II)) when iron accepts the electron. Since iron is the fourth 
most abundant element in the Earth?s crust (around 5.1%), this process is widespread in natural 
settings. In fact, ferric iron is one of the most important electron acceptors in non-marine 
sediments (Straub et al., 2000). Ferric iron is found in many different forms in the environment; 
common mineral forms are amorphous iron oxides, ferric oxyhydroxides, and hydrous ferric 
oxides, together referred to as iron oxyhydroxides (Straub et al., 2000). As they age, iron 
oxyhydroxides transform and re-organize to hematite, limonite, and goethite with better-defined 
atomic structures. 
 A chief adverse effect of FeRB is that, through dissimilatory processes, oxidation of 
organic compounds can lead to the mobilization of certain adsorbed trace metals during iron 
reduction. As dissimilatory processes are occurring, electrons are funneled by FeRB from a 
23 
 
carbon source to ferric iron. Other elements near their terminal electron acceptor (i.e., elements 
sorbed into iron oxyhydroxides) will occasionally receive electrons, causing them to become 
reduced. Arsenic is a prominent metal involved in this cycle. Arsenic is introduced to the 
hydrosphere and atmosphere by natural weathering or human activities (e.g., burning of coal) 
and ultimately is transported by streams and rivers in suspended sediment loads (Drever, 1997; 
Saunders et al., 2008). Eventually, streams and rivers will empty their sediment loads into 
estuaries and bays, concentrating arsenic in wetland settings. In oxidizing conditions, arsenic is 
primarily immobilized by being co-precipitated and adsorbed onto iron or manganese oxy-
hydroxides. During reduction, iron in these minerals is converted from Fe(III) (ferric iron) to 
Fe(II) (ferrous iron). This reduction has the tendency to disaggregate iron oxy-hydroxide 
minerals, thereby remobilizing arsenic. In addition to its release, arsenic is reduced from arsenate 
to arsenite when it receives electrons. Arsenite is the more adsorption-resistant and toxic form of 
arsenic. 
Sulfate-reducing bacteria (SRB) are bacteria that respire by oxidizing organic compounds 
while utilizing sulfate as their terminal electron acceptor in a process known as anaerobic 
respiration. Important bacteria in subsurface, SRB are known to exist in a variety of terrestrial 
and aquatic environments. They tend to outcompete many other microbes in environments that 
are carbon-rich and oxygen-deficient (Chapelle, 1993). SRB are also considered to be one of the 
important microbes in driving carbon and sulfur cycles. Sulfur is found in three common 
oxidation states: -2 for monosulfides (-1 for disulfides), 0 for elemental sulfur, and +4 for 
sulfates. The sulfur cycle is very dependent on SRB for redistributing sulfur among the three 
oxidation states (Chapelle, 1993).  SRB also utilize carbon produced by fermenters as a carbon 
source for their metabolism, thus playing a major role in carbon cycling.  
24 
 
If a carbon source is plentiful, SRB also tend to flourish in marine environments due to 
the abundance of sulfate in seawater. FeRB and SRB may, on occasion, also cohabitate in the 
same environment (Lovley and Chapelle, 1995). Like FeRB, many SRB species have the ability 
to utilize metals other than sulfate as their terminal electron acceptor (Lloyd et al., 2011). One 
adverse effect of SRB is their connection with mercury methylation. Methyl mercury is the most 
toxic and mobile form of mercury (Merritt et al., 2009; Acha? et al., 2011). Mercury methylation 
tends to occur in anoxic environments where SRB reside, and SRB are likely responsible for the 
methylation of mercury under favorable (i.e., acidic, warm, and low-salinity) geochemical 
conditions (Mason et al., 2005; Monreal, 2007).  Under highly reducing conditions, SRB may 
reduce dissolved loads of many toxic metals by sequestering them in Fe-sulfides (Huerta-Diaz 
and Morse, 1992; Lee et al., 2005; Saunders et al., 2008). 
 
Organic Carbon 
Organic carbon in wetlands and salt marshes is introduced from both allochthonous and 
autochthonous sources (Bianchi et al., 2010). Organic carbon can be derived from terrigenous 
sources, such as the decaying of organic matter in soil and also from biological activity of 
organisms living in the water. Organic carbon is an important part of the carbon cycle, which is 
the process responsible for recycling and redistributing carbon throughout the biosphere.  
By utilizing oxygen through the formation of carbon dioxide, bacterial degradation of 
organic carbon contributes to the development of anoxia in wetlands. Reducing bacteria, such as 
SRB, can further enhance this process through reduction of organic materials such as fulvic and 
humic acids. In low-temperature sedimentary environments, microbial processes are known to be 
25 
 
the primary oxidizers of organic material, resulting in the formation of carbon dioxide and 
reducing geochemical environments (Freeze and Cherry, 1979; Lovley and Chapelle, 1995).    
Petroleum, or crude oil, is comprised of many components, including various 
hydrocarbons such as paraffins (alkanes), naphthenes (cycloalkanes), asphaltics (asphaltenes), 
and aromatics, trace metals and various other compounds. The mixture of these compounds 
defines the characteristics of crude oil. Aromatic hydrocarbons, which have alternating single 
and double carbon atom bonds, have been known to be both carcinogenic and mutagenic. 
The chemical fingerprinting of oil is a relatively new procedure that has shown great 
promise in hydrocarbon exploration and also linking oil spills with their source. The primary 
factors controlling the individual geochemical characteristics of oil are: 1) the state of the source 
strata; 2) the thermal history of the source strata; 3) any chemical changes (e.g., degradation) 
resulting from the oil?s migration from the source strata to its reservoir; and 4) the weathering of 
the oil after release into the environment (Wang and Stout, 2007). Weathering of the oil will 
continuously degrade it, although typically it affects just the lighter compounds. Primary 
degradation of oil occurs through evaporation, dissolution, emulsification, photo-oxidation, 
biodegradation, and sedimentation/oil-mineral aggregation.  
Although weathering does result in a chemical change in the oil, certain compounds 
within the oil are resistant to degradation, even in severe weathering cases (Overton et al., 2004; 
Morrison and Murphy, 2006). These compounds, called biological markers (or biomarkers), are 
compounds that really have not changed much (if at all) from their original structure in living 
organisms (Wang and Stout, 2007). In fact, these compounds actually become concentrated 
(relative to degraded portions) during the weathering process due to their resistant nature (Wang 
and Fingas, 2003). Due to the lack of degradation of biomarkers and the geologic uniqueness of 
26 
 
reservoirs, spilled oil can be linked to its petrographic source on the basis of its biomarkers 
(Overton et al., 2004; Morrison and Murphy, 2006; Wang and Stout, 2007). It should be 
mentioned, however, that in certain climate conditions over long periods of time, even the 
usually degradation-resistant biomarkers can experience alteration (Wang et al., 2001). 
Biomarkers also can help characterize a particular oil?s thermal history and depositional 
environment, as well as the type of organic matter in the source rock (Wang and Stout, 2007; 
Ventura et al., 2010). 
Oil fingerprinting traditionally has been difficult, as crude oils consist of a wide range of 
organic compounds with different molecular weights and properties, though advancements in 
technology and analytical methods has made the practice more reliable and accessible (Wang 
and Fingas, 2003). Although biomarkers? concentrations are often low in oil (Wang and Stout, 
2007), biomarkers are still easily detectable, given the sensitivity of modern analytical 
instruments. According to Wang and Stout (2007), gas-chromatograph mass spectrometer (GC-
MS) is generally the best instrument to use for biomarker detection and quantification. The GC-
MS can be run in full scan mode, which will analyze up to hundreds of ions at a lower 
sensitivity. A selected ion mode (SIM) also can be run; under this mode, a few diagnostic ions 
are analyzed under a narrow scan under much higher sensitivity. Steranes, terpanes, and hopanes 
are most often used in fingerprinting because of their resistance to degradation (Barakat et al., 
2002). The GC-MS analysis measures the mass-to-charge (m/z) ratio, which is unique for each 
ion. For example, terpanes have an m/z ratio of 191. 
 
 
 
27 
 
Sedimentary/Framboidal Pyrite 
Sedimentary, or biogenic, pyrite can form in wetland environments due to the reduction 
of ferric iron and sulfate by dissimilatory FeRB and SRB, and it is a prevalent authigenic 
component of sediments and sedimentary rocks (Berner, 1970). The free products of the 
reduction, ferrous iron and sulfide, can bind together and produce pyrite-like solids. The main 
limiting factors that limit the amount of sedimentary pyrite formed are the amounts of organic 
material, sulfate, and reactive iron in the system (Berner, 1970; Canfield et al., 1992; Morse, 
1999). In marine systems, the amount of iron is often the limiting factor for these reactions 
(Canfield et al., 1992; Morse, 1999). There also must be enough reactive organic material to 
initiate and sustain the bacterial sulfate-reduction process (Berner, 1983). The formation of 
sedimentary pyrite tends to occur within muds, as coarser-grained sediments do not normally 
contain the requisite amount of reactive iron or organic matter necessary for pyrite formation 
(Morse, 1999). However, poorly sorted, coarser-grained sediments may contain sufficient 
amounts of fines to accommodate pyrite formation. 
Pyrite is thought to initially form in sediments as iron monsulfides, and possibly 
disordered mackinawite and greigite, but then in early stages of sedimentary diagenesis converts 
to iron bisulfide, or pyrite (Berner, 1970; Morse, 1998). The initial monosulfide phase can lead 
to another form of pyrite called framboidal pyrite (Wilkin and Barnes, 1996). Framboidal pyrite 
has a raspberry-like appearance and, in fact, takes its name from the French word for raspberry 
(framboid). The formation of framboidal pyrite is not wholly understood; it is thought by some to 
be an authigenic process (Berner, 1970; Wilkin and Barnes, 1996; Wilkin et al., 1996) and by 
others a biogenic process (Donald and Southam, 1999; Folk, 2005). Wilkins and Barnes (1996) 
propose that a likely scenario for framboidal pyrite formation is that the initial sulfide formed is 
28 
 
actually greigite (Fe3S4). Greigite has shown ferrimagnetic tendencies, so a possible model 
would be that greigite grains attach to each other through magnetic attraction, form spheroidal 
textures. Because greigite has been shown to be thermodynamically unstable in marine 
environments, it would likely be replaced by pyrite (Wilkin and Barnes, 1996; Wilkin et al., 
1996). Berner (1969) describes a process by which synthetic framboidal pyrite was formed in a 
laboratory setting, indicating that microorganisms were not necessary for the process. 
Conversely, Folk (2005) cites several studies where framboidal pyrite was found in conjunction 
with decaying organic matter, and, in his own study, he found that the spherical components that 
make up the framboids are actually nannobacterial cells. The typical model for pyrite formation 
in aqueous solutions, described by Rickard and Luther (2006), is as follows: 
 
FeS + H2S           FeS2 + H2 
 
   It seems plausible that both authigenic and biogenic processes result in the formation of 
framboidal pyrite. Donald and Southam (1999) performed laboratory experiments in which iron 
monosulfides was produced. In the setup with no bacteria, excess H2S in the system was a 
catalyst in converting the product into pyrite, while in the biogenic system bacteria were able to 
catalyze the iron-monsulfide conversion to pyrite. Although the exact mechanism for the 
formation of sedimentary pyrite is not well understood, the ability of pyrite to co-precipitate with 
and adsorb trace metals is well documented (Huerta-Diaz and Morse, 1992; Lee et al., 2005; 
Saunders et al., 2008). 
 
 
29 
 
Trace Metals 
Trace metals are found in minute quantities in the cells and tissues of organisms. The 
metals are an integral part of proper nutrition for plants and animals, but can be toxic when 
accumulated in high levels. Wetlands are important because they have been recognized as both 
sinks and sources of trace metals, depending on climate variability and geochemical conditions. 
Inland wetlands at times may be sinks for trace metals. However, with seasonal and geochemical 
changes, metals in these settings may become mobilized (Olivie-Lauquet et al., 2000). Coastal 
wetlands are the final terrestrial sink for metals. Any metals mobilized within this realm may be 
released into the water column and ingested by organisms. 
Trace metals in wetlands have been known to concentrate in both authigenic (Huerta-
Diaz and Morse, 1992) and biogenic (Orberger et al., 2003) pyrite through co-precipitation and 
adsorption. Trace metals/metalloids typically associated with sedimentary pyrite include As, Cd, 
Co, Cr, Cu, Hg, Mn, Mo, Ni, Pb, and Zn (Huerta-Diaz and Morse, 1992). In addition to the trace 
metals already captured naturally by wetlands, additional trace metals may be added during 
organic incursions such as those associated with oil spills (Karchmer and Gunn, 1952; Ball et al., 
1960; Barwise, 1990).  Metals found in varying concentrations in oil include Ni, V, Fe, Ba, Al, 
Cr, Cu, and U (Karchmer and Gunn, 1952; Ball et al., 1960; Barwise, 1990; Kennicutt et al., 
1991).  
 
 
 
 
 
30 
 
 
METHODOLOGY 
Field Methods 
In order to understand the biogeochemical effects of the Gulf oil spill on coastal salt 
marshes, field sampling was conducted at both pristine and contaminated sites, with various 
laboratory analyses being conducted afterwards. Surface-water, sediments, and pore-water 
samples collected at these sites were subjected to a variety of analyses in order to characterize 
their geological, geochemical, and microbiologic profiles.  
Field sampling for this study was conducted in six coastal marshes in Mississippi and 
Louisiana, two of the states most affected by the oil spill. The sites were selected based on the 
degree of inundation with oil (sites range from pristine to heavily inundated), and their 
sedimentologic characteristics, mainly sediment texture. Finer-grained sediments were the 
primary focus because they host more organic matter, adsorb more heavy metals, and have 
higher porosities, which would yield more pore water for geochemical analyses. Each site was 
accessible by boat.  
Upon arrival at each site, surface water was sampled using a Van-Dorn water sampler. 
After collection, water samples were subjected to measurements of temperature, pH, dissolved 
oxygen (DO), conductivity, and oxidation-reduction potential (ORP) by portable meters. At 
certain collection sites, water-quality parameters were measured using an in situ multi-parameter 
monitor TROLL 9000.  All surface-water samples were filtered using a 0.45-?m nylon filter. 
Samples for trace element and cation analyses were acidified with trace-metal grade HNO3 and 
31 
 
stored in polyethylene bottles that were pre-leached by 3% HNO3 to ensure trace-metal 
cleanliness. 
Following surface-water sampling, 7 to 8 cores, separated from each other by 1 to 2 
meters, were collected at each site using a Wildco push-type corer. Each corer provided a 
minimum of 30 cm of in situ sediments. The metal corer was equipped with a plastic nose and a 
plastic liner (cab tube) to avoid metal contamination. Once core samples were taken, the cab 
tubes were removed and immediately capped to seal off oxygen. Each cab tube containing 
sediment was then packed with ice or dry ice for preservation purposes. All core samples were 
quickly transported back to the laboratory to be prepared for various sedimentological, 
geochemical, and microbial analyses. Plant samples also were collected at all sites for carbon 
isotope analysis and comparison with marsh sediment and BP crude oil isotope signatures. 
Weathered oils were scraped off from plants at heavily oil sites to characterize the source of oil 
and its degree of degradation. 
Laboratory Methods 
Due to the necessity of processing redox-sensitive samples in a timely fashion, temporary 
laboratories were set up in convenient locations near the sampling sites. Wet chemistry 
laboratories in the Stennis Space Center and Dauphin Island Sea Laboratories were utilized for 
the initial processing of core samples collected from Louisiana and Mississippi salt marshes, 
respectively.  
In the laboratory, sediment cores were processed in a sealed glove bag that was flushed 
with nitrogen and sealed to ensure an anoxic environment. Inside the glove bag, cores were 
sectioned into 3-cm segments and placed into 50-ml centrifuge tubes, which were labeled for 
32 
 
each specific range of depth. Some of these 3-cm sections were centrifuged to separate pore 
waters and sediments.  Pore waters were filtered through a 0.45-?m filter in the glove bag for 
various geochemical analyses listed in Table 2. Water samples were acidified by trace-grade 
HNO3 for trace-element and cation analyses. Water samples for total and organic mercury 
analyses were stored in VWR trace clean vials for later analysis. 
Table 2. Geochemical analyses performed on pore-water and sediment samples. 
 
Core 
 
Analysis 
 
Instrument 
 
Location of 
Analysis 
Analytical/ 
 
Preservation 
 
A Major Ions 
 
As Speciation 
 
 
 Trace Elements 
 
Ion Chromatography (IC) 
 
IC-Atomic Fluorescence 
Spectrometer 
 
ICP-MS 
Vassar College 
 
Vassar College 
 
 
Vassar College 
Flash Frozen 
 
Flash Frozen 
 
 
Acidified 
B Hg Speciation 
 
Fe(II) 
 
Sulfide 
Tekran 2500 
 
HACH spectrophotometer 
 
HACH spectrophotometer 
Woods Hole 
 
Field 
 
Field 
EPA method 
1631 
EPA method 
8146 
EPA method 
8131 
C Dissolved Organic 
Carbon (DOC) 
 
Sediment Total Organic 
Carbon 
TOC-V Combustion Analyzer 
 
 
LECO Carbon Analyzer 
Auburn 
 
 
Auburn 
Filtered 
 
 
Inorganic C 
removed by 
HCl 
D Grain Size 
Analysis 
Sieve/Pipette Auburn Ice 
E Sediment Bulk Elemental 
Composition 
 
Sediment 13C/12C 
ICP-MS 
 
 
Finnigan IRMS 
ACTLAB 
 
 
 
Florida State 
Total digestion 
 
 
EA-IRMS 
F Microbial Analysis Eppendorf thermal cycler AUM MPN/PCR 
G Organic compounds 
(crude oil/PAHs) 
GCMS Auburn      Biomarker 
Analysis 
EPA method 
3570 
H Extra   Cold room 
(5?C) 
33 
 
Cores were designated letters A through H (in no specific order) so that they could be 
separated and grouped on the basis of the analyses to be performed. Depending on the varying 
needs for preserving oxidation states for various analyses, cores were either processed in or out 
of the glove bag.  
Core A was sectioned into 3-cm segments within a nitrogen glove bag. Each segment was 
placed into a 50-ml centrifuge tube and labeled with the corresponding depth. After separation, 
the tubes were sealed to prevent oxidation and then centrifuged. The tubes were subsequently 
placed back into the nitrogen glove bag. Pore waters were then extracted and placed into pre-
labeled sterile 2-ml vials. Pore-water subsamples were analyzed for 1) major ions using ion 
chromatography (IC), 2) arsenic speciation using an ion chromatography atomic fluorescence 
spectrometer (IC AFS), and 3) trace elements using inductively coupled plasma mass 
spectrometry (ICP-MS). All analyses for this core were performed at Vassar College. Sediments 
from this core were retained for future testing. 
Core B was processed in a similar manner as Core A. The pore waters were extracted, 
placed into 2-ml vials, and split for three different analyses. One subsample set was sent to the 
Woods Hole Laboratory, MA, where it was analyzed for mercury speciation using a Tekran 
model 2500 Cold Vapor Atomic Fluorescence Spectrophotometer (CVAFS). The other two sets 
of pore-water subsamples were analyzed on site using a Hach spectrophotometer for ferrous iron 
using EPA method 8146 and reduced sulfur by EPA method 8131. These 2 analyses were 
performed immediately to minimize oxidation, which can alter speciation ratios. 
Core C was sectioned without a nitrogen glove bag and subsequently placed into 50-ml 
tubes. The tubes were then centrifuged. Afterwards, pore waters were placed into 2-ml vials for 
34 
 
storage. The pore waters were later analyzed for dissolved organic carbon (DOC) at the Auburn 
University Forestry Department using a TOC-V Combustion Analyzer. The sediments from Core 
C were later dried and pulverized to pass through a 230-mesh sieve. A portion of this powder 
was analyzed for total organic carbon using a LECO carbon analyzer in the sedimentology 
laboratory at Auburn University. 
Core D was sectioned outside of the nitrogen glove bag. It was divided into ten 3-cm 
segments, and placed into bags labeled with corresponding depth. The samples were brought 
back to Auburn University and analyzed for grain size. In the interest of time, only 3 samples 
from each site were analyzed. The surface (0-3 cm), the middle (12-15 cm), and the bottom (27-
30 cm) intervals were analyzed for each site in order to characterize the sediment column and 
grain-size distribution. The samples were separated into sand and silt/clay fractions by washing 
the samples with distilled water through a 230-mesh sieve. All sediments retained on the sieve 
were in the range of sand. Any obvious organics were picked out to reduce their impact on the 
weight of the sand fractions. Sand percentages were visually estimated, and if it was 
(qualitatively) determined that there was less than 5% sand, then the sand portion was thrown out 
and the sample recorded as consisting of less than 5% sand. If there was more than 5% sand, then 
the sample was retained, dried, and ultimately dry-sieved at 1-phi intervals from >-1 to 4 phi. 
Separate sand fractions were weighed and used to determine grain size distribution within coarse 
sediments. Sediments passing through the 4-phi sieve were flushed into a 1000-ml graduated 
cylinder. A 30-ml of sodium hexametaphosphate solution was added as a deflocculant, the 
container was filled to the 1000-ml mark, and the silt and clay fractions of the sample were 
determined by standard pipette techniques. 
35 
 
Core E was processed without the use of a nitrogen glove bag. This core was broken into 
ten 3-cm segments. Each segment was placed into a sample bag pre-labeled with a corresponding 
depth. The samples were brought back to Auburn University and dried at a temperature of 
approximately 100?C in order to achieve consistent drying. Once dried, the samples were 
powdered by mortar and pestle, and then they were passed through a 230-mesh sieve. 
Approximately 2 to 3 grams of the sample that passed through the sieve was placed in small 
sample bag pre-labeled with the corresponding depth. All ten samples from each core were then 
sent to ACME Labs in Vancouver, British Colombia, and analyzed for bulk chemical 
composition by inductively coupled plasma mass spectrometry (ICP-MS). Approximately 5 
grams of the remaining material was sent to the National High Magnetic Field Laboratory at 
Florida State University, where it was subjected to bulk sediment carbon isotopic analysis using 
a Finnigan mass spectrometer. Pristine plants, plants covered in oil, and initial BP crude oil from 
the Macondo-1 well also were subjected to the 13C/12C analysis at the High Magnetic Field 
Laboratory. 
The remaining powdered material from core E samples was bagged. Some of these 
samples were later used for x-ray diffraction analysis using a Rigaku Miniflex in the Chemistry 
Department at Auburn University. No attempts to remove organics from the samples were made, 
other than hand-picking large organic substances out prior to sieving. The surface (0-3 cm), 
middle (12-15 cm), and bottom (27-30 cm) sections were analyzed to characterize the 
mineralogy at each site. The samples were prepared for XRD analysis by first spreading a small 
amount of sample onto a zero-background disc. A few drops of hexane were then added to the 
samples to randomly orient the grains. The samples were then placed into the X-ray 
diffractometer with a start angle of 3? and a stop angle of 60?. After all of the samples were 
36 
 
analyzed, the raw files generated by the X-ray diffractometer were collected and analyzed with 
the program Crystal Match. 
Some of the other dried and bagged samples also were used for scanning electron 
microscopy (SEM) and energy dispersive X-ray (EDAX) analysis. In all, sediments from 2 sites 
(Bayou Dulac and Bay Jimmy North) were utilized in SEM/EDAX analysis in order to identify 
sulfides and any trace metals adsorbed on them. Sulfides were extracted by immersing samples 
in a centrifuge tube containing high-density tetrabromoethane. Samples were centrifuged at 3000 
rpm for 10 minutes. Next, the cake of lighter elements that was floating on top of the 
tetrabromoethane was removed, and the samples were centrifuged again at 3000 rpm for 10 
minutes. The cake was again removed, and the tetrabromoethane was poured off. Samples were 
then washed with acetone, placed in a filter paper, and vented in the fume hood for several hours. 
Residues were then dried in an oven overnight. After drying, the samples were removed from the 
filter paper and placed in a pre-cleaned 2-ml autosampler vial for storage. Some of the sample 
was then mounted on a glass slide with epoxy. The epoxy was ground down and smoothed to 
expose the powdered sample at the surface. Sulfides were identified with a reflecting light 
microscope. Photos were taken, and areas of interest were marked. Next, samples were gold-
coated and taken for SEM and EDAX analysis. After SEM/EDAX analysis, the epoxy-mounted 
grains on glass slides were analyzed for specific trace metal content via laser ablation-
inductively coupled plasma/mass spectrometry (LA-ICP/MS) at the National High Magnetic 
Field Laboratory at Florida State University in Tallahassee, FL. Equipment used included a UP 
193 FXArF (193 nm) excimer laser ablation system (New Wave Research, Fremont, CA, USA) 
coupled to a Thermo Finnigan Element XR ICP-MS. Since Fe and S are the two primary 
constituents of these samples, results generated were normalized to Fe and S. 
37 
 
Core F was processed as soon as possible after collection for preservation purposes. This 
core was processed inside a nitrogen glove bag in order to provide an anoxic environment. This 
sample was divided into ten 3-cm segments. Each segment was placed into a 50-ml centrifuge 
tube pre-labeled with the corresponding depths. The surface (0-3 cm), middle (12-15 cm), and 
bottom (27-30 cm) segments were collected from each site and heat sealed within a Mylar bag to 
reduce oxidation. The Mylar bags were labeled for each site and then sent to Dr. Benedict Okeke 
at Auburn University at Montgomery. Dr. Okeke performed microbial analysis using an 
Eppendorf thermo cycler and most probable number (MPN) and polymerase chain-reaction 
techniques. Extra samples were brought back to Auburn University and placed in storage for 
potential future analyses. 
Core G for each site was brought back to Auburn University as a whole core. The cores 
were heat sealed in Mylar bags and stored in a 5?C cold room located in Auburn University?s 
Funchess Hall. It was later determined that a couple of different analyses were necessary, and 
core G was selected for these. Polycyclic aromatic hydrocarbon (PAH) fingerprinting was 
employed to trace oils from contaminated sites back to those from the Macondo-1 well. PAH 
fingerprinting involves the extraction of PAHs from oiled sediment samples and subsequent 
analysis by a Waters orthogonal acceleration time-of-flight mass spectrometer (GC-TOF/MS). 
PAH extraction was performed at Auburn University utilizing a modification of EPA Method 
3570. The first step in this process was to break the core into ten 3-cm segments without the use 
of a nitrogen glove bag. The segments were placed in sample bags pre-labeled with 
corresponding depths. The surface (0-3 cm), middle (12-15 cm), and bottom (27-30 cm) 
segments were selected for analysis. In all, 5 of the 6 study sites were analyzed for PAH 
fingerprinting (lacking evidence of contamination, the Bayou Heron site was not utilized). Once 
38 
 
the cores were broken into segments, and the three segments from each site were selected, the 
PAH extraction process began.  
The PAH extraction process started by adding 5 g of anhydrous sodium sulfate to a pre-
cleaned PTFE extraction tube. Next, approximately 3 g of the sediment of interest were added to 
the tube. After that, 10 g of dichloromethane (DCM) were added to the tube, and the tube was 
sealed with a PTFE screw cap. The outside of the tube was then wrapped with parafilm, which 
allowed for easy detection of leaks. Samples were shaken for approximately 2 minutes to 
produce a slurry, and then rotated on a rotating incubator for approximately 24 hours. Next, the 
samples were centrifuged at 3000 rpm for 10 minutes. The liquid was then pipetted over to a 
16x100 glass extraction vial. This liquid was then filtered and placed into a new 16x100 glass 
extraction vial. The extraction vial was then placed under a fume hood and blown with nitrogen 
gas for at least 30 minutes. Once the DCM was volatilized, the PAHs were extracted from the 
glass vial by adding a final solution of hexane and methyl tert-butyl ether (1:1 ratio). The final 
solution was then extracted by a glass syringe, and 1.5 ml of the solution was added to a 2-ml 
autosampler vial. The vials containing the solutions were stored in the freezer until analysis by 
the GC/MS.   
Results show that GC-TOF/MS analyses in full-scan mode were not specific enough for 
fingerprinting petroleum compounds. Hence, a more sensitive method of gas chromatography-
selected ion mode/mass spectrometer (GC-SIM/MS) was used to generate gas fragmentograms 
(of selected organic molecule fragments) using a Agilent 5975C GC-MS, where specific mass-
to-charge (m/z ratios) could be identified for fingerprinting. Gas chromatographs were used to 
trace the weathering and biotransformation of oils in coastal wetlands with respect to the initial 
BP oil. Identifications of key organic compounds were achieved by comparison with special oil 
39 
 
biomarkers such as terpanes (m/z 191), steranes (m/z 217), and seco-hopanes (m/z 218).  The 
degree of similarity in biomarkers was used to assess whether extracted oils were originated from 
the Macondo-1 well, or from other Gulf oil sources. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
40 
 
 
RESULTS AND DISCUSSION 
 
Surface Water 
Water quality parameters of surface waters (Table 3) can change for a variety of reasons 
and at a variety of time scale: they may vary on a daily basis due to the effects of tides, and they 
also may vary seasonally; mixing between seawater and freshwater also affects the water quality. 
Shallow surface-water samples show varying ranges of temperature that correlate with sampling 
time. Mississippi sites, sampled in October, show higher temperatures than those recorded at 
Louisiana sites in January. Dissolved oxygen (DO) concentrations are also higher in colder 
water. Electrical conductivity and pH values show lower values than what is typically found in 
seawater, indicating that there is varying amounts of freshwater and seawater mixing within the 
estuaries. Positive ORP (65-230 mV) and relatively high DO values (6.9-12.32 mg/kg) indicate 
that surface waters were under oxidized conditions months after the oil spill. This shows that the 
majority of the oil in surface waters had evaporated, dispersed, or degraded by microbial activity. 
The dissolved organic carbon contents are slightly higher at oiled Louisiana sites (>40 mg/kg) 
with respect to those measured at Mississippi sites (< 30 mg/kg), suggesting the presence of very 
small quantities of residual oil in Louisiana surface waters. The pH values ranged from 7.54 to 
7.88 and 7.63 to 7.90 in the Mississippi and Louisiana sites, respectively. Processes such as 
biodegradation of oil, bacterial sulfate reduction, and seawater intrusion all can affect the pH of 
water, which in turn can affect the sorption and desorption of trace metals and methylation of 
mercury. 
 
41 
 
Table 3. Surface-water data collected via in situ meters of TROLL 9000. 
Sample ID Water 
Depth (cm) 
Temp. 
(?C) 
pH ORP 
(mV) 
DO 
(mg/kg) 
Cond 
(mg/kg) 
DOC 
(mg/kg) 
WB 85 22.8 8.3 189 8 >2000 17.3 
LB 40 25.3 7.03 196 6.98 >2000 26.6 
WI 30 25.3 7.53 160 8.09 >2000 33.0 
BH 20 21.6 7.54 134 6.9 >2000 32.4 
PACB 25 23.1 7.88 135 7.7 >2000 31.3 
RG 20 8.8 7.63 230 10.80 16990 23.4 
BD 10 11.5 7.73 102 9.73 20000 40.0 
BB 10 10.4 7.81 65 10.72 18000 43.4 
BJN 5 6.6 7.90 220 12.32 15360 41.8 
BJS 5 7.2 8.08 180 11.65 13950 41.9 
 
 
Pore-water Geochemistry 
 Porewaters were measured directly in the field laboratories for reduced (solubilized) iron 
and sulfur content using a HACH spectrophotometer. Other pore-water subsamples also have 
been analyzed for major and trace element contents, as well as DOC. Porewaters extracted from 
one sediment core in each oiled Louisiana site were also measured for pH values at 3-cm depth 
intervals. 
 Reduced iron concentrations are typically low in seawater, and the measured reduced iron 
levels (Figure 14, Appendix 1) at the Mississippi (0.01 to 0.04 mg/kg) and Louisiana (0.01 to 
0.03 mg/kg) sites fall within this scenario. With very low concentrations, there is not a clear 
relationship between reduced iron at pristine and contaminated sites. Contaminated sites 
generally contain slightly less solubilized iron, indicating some dissolved iron has been removed 
during formation of iron-sulfide solids (see Petrographic section).  
42 
 
 
Figure 14. Box and whisker plot showing spatial variability of reduced iron. Ferrous iron concentrations 
are very low at many contaminated sites, indicating that most of the dissolved iron is removed by the 
formation of iron sulfides. Open circles represent outliers with distance from the box > 1.5 times the 
difference between the third and the first quarter. 
 
The level of reduced sulfur in porewater is an important indicator of redox conditions. 
Reduced sulfur concentrations were very low (<1 mg/kg) at unaffected salt marsh sites in 
Alabama (Natter, 2012).  In contrast, reduced sulfur contents are very high at contaminated 
Louisiana sites (Figure 15, Appendix 1). RG, the control site, had an average of approximately 8 
mg/kg. The heavily-oiled sites all showed extremely high levels of reduced sulfur: BD showed a 
range of 4 to 59 mg/kg; BB showed a range of 4 to 49 mg/kg; and BJN showed a range of 5 to 83 
mg/kg. Very high reduced sulfur and low reduced iron contents suggest that iron-reducing 
bacteria (FeRB) are being outcompeted by sulfate-reducing bacteria (see Microbial section) in 
oiled marsh environments. Influx of oil in muddy sediments probably provided additional 
substrate and carbon sources for sulfate-reducing bacteria.  
 
43 
 
 
Figure 15. Box and whisker plot showing spatial variability of reduced sulfur in pore waters. Reduced 
sulfur was found to be highest at contaminated sites. 
 
 
Reduced sulfide concentrations (Figure 16) show marked increases with respect to depth 
in the sediment column. Given that seawater contains copious amounts of sulfate (approximately 
2,000 ppm), it is likely that seawater is invading the deeper parts of the sediment column, where 
sulfate is being utilized as an electron acceptor by sulfate-reducing bacteria. Influx of oil fuels 
activities of sulfate-reducing bacteria, which convert sulfate to hydrogen sulfide and consume 
protons in porewater: 
 
SO4-2 + 2CH2O +2H+ ? 2CO 2 + H2S + 2H2O 
  
This reaction could explain the elevated pH levels with depth (Figure 17) in porewaters 
measured at the oiled Barataria Bay sites, as hydrogen ions are being consumed during the 
reaction, effectively making the water more basic. Any oil (i.e., organic material) present can 
invade into sediments along with the seawater, providing the substrate to allow for such a 
44 
 
reaction to occur.  Thus, the concurrent increases in pore-water, pH, and sulfide concentrations 
with depth indicates the combined effects of seawater intrusion and possibly enhanced bacterial 
sulfate reduction induced by spilled oil.  The low reduced iron concentrations (< 0.02 mg/kg) and 
very high levels of sulfide at highly contaminated Louisiana sites indicate that bacterial sulfate 
reduction has fixed most reduced Fe and other trace metals by forming iron sulfide solids (see 
Petrographic section).   
 
 
 
Figure 16. Profile showing reduced sulfur concentration with depth at several oiled marsh sites in 
Louisiana. The general trend shows significant increases in sulfide concentration with depth. 
 
 
 
 
45 
 
 
Figure 17. Profile illustrating pH trends with depth at heavily oiled marsh sites in Louisiana. The general 
trend shows significant increases in pH with depth. 
 
 
Figure 18 shows depth profiles and spatial variation of DOC concentrations in porewaters 
among the sites. At Mississippi sites, BH contains an average of twice as much DOC as PACB at 
depths > 15 cm. By contrast, PACB shows slightly higher DOC values (approximately 27-38 
ppm) than those at BH (approximately 12-32 ppm) in the upper 10 cm of the sediments. This 
contrast with depth suggests a possibility that residual oil remains in porewaters within the 
uppermost sediment column of PACB. This higher amount of DOC  near the water-sediment 
interface of PACB could explain why measured ORP levels (Table 3) are about the same at 
PACB and BH sites (135 vs. 134 mV, respectively), even though PACB was expected to be 
much more oxygenated in its high-energy, ocean-front environment.  
DOC concentrations of porewaters at BD, BB, and BJN sites averaged 227, 267, and 269 
mg/kg, respectively, compared with an average value of 96 mg/kg at the RG site. The DOC 
contents of porewater at these Louisiana oiled sites are much higher than those measured at less 
46 
 
affected BH and PACB sites in Mississippi (generally < 50 mg/kg). DOC levels also are much 
higher in porewaters than in surface water (Table 3) at heavily oiled sites.  These results indicate 
that elevated DOC levels could persist in sediment porewater for months or longer even after a 
significant portion of the oil in the surface water has evaporated, dispersed, or been degraded by 
microorganisms. Porewaters with very high DOC were noticeably discolored; some with a 
yellowish hue, and some were dark brown to black. These distinct colors may be caused by oil 
components and/or increased organic substances released by microbial activities fueled by the 
spilled oil. 
BH contains an average of twice as much DOC as PACB, reflecting its high TOC 
contents in sediments. However, PACB shows higher amounts of DOC through the upper 10 cm 
of the sediment column. This finding suggests that residual oil remains in porewaters within the 
uppermost sediment column of PACB. At the Louisiana sites, DOC levels tend to increase with 
depth. The DOC contents in near-surface sediments may be reduced by freshwater recharge from 
rainfall or shallow groundwater.  A positive relationship between DOC and TOC (r = 0.47) is 
observed, although the cause of correlation is not clear. This positive correlation suggests that 
either DOC or TOC may be used as an indicator of oil-contamination levels. Quantitative 
assessment of oil contamination also may be achieved by the stable carbon isotopic analysis of 
bulk sediments (see Carbon Isotope section). 
 The concurrent increase of DOC, TOC, pH and sulfide concentrations (see Figures 18, 
42, 17, and 16, respectively) with sediment depth suggests that oil could be intruding into the 
deeper portions along with seawater. This suggests, in turn, that not all of the spilled oil rose to 
the surface, and a fraction of oil plumes might spread in the water column and contaminate the 
underlying sediments. Moreover, the DOC levels are also much higher in porewaters than in 
47 
 
surface water (ranging from 23 to 43 mg/kg at heavily oiled Louisiana sites). This is also 
indicative that despite microbial degradation, evaporation, and dispersion processes, remnants of 
the oil are still remaining in the environment. These remnants could continue to persist in marsh 
sediments for many years (Oudot and Chaillan, 2010). 
It is important to note that the DOC levels of surface water at heavily oiled sites (range 
from 23 to 43 mg/kg) are similar in magnitude to those of surface water and porewater at 
unaffected sites (Table 3). This indicates that oils in the water column had evaporated or 
dispersed within about six to eight months after the spill. At the oiled Louisiana sites, DOC 
levels of porewater tend to increase with depth. The DOC contents in near-surface sediments 
may be reduced by freshwater recharge from rainfall or shallow groundwater.   
 
 
 
Figure 18. (A) Depth profile and (B) box and whisker-plot showing depth and spatial variability of DOC 
in pore waters. Contaminated sites show much higher DOC levels compared to those at non-contaminated 
sites. 
 
 
 
(A) (B) 
48 
 
Sediment Characteristics (Grain Size and Mineralogy) 
In order to characterize each site on the basis of the sediment texture, grain-size analyses 
were performed on sediment cores from 0-3 cm, 12-15 cm, and 27-30 cm intervals. Grain size 
can significantly affect the fate and mobility of trace metals in sediments. Fine-grained sediments 
(as well as organics) have a higher capacity to adsorb trace metals than coarse-grained sediments 
(Horowitz and Elrick, 1987). 
Ultimately, samples were classified based on their phi values on the modified Udden-
Wentworth scale. Phi values of -1 to 4, 4 to 8, and greater than 8 were designated as sand, silt, 
and clay, respectively. Using these designations, sand (when applicable), silt, and clay 
percentages from all sites were calculated and graphed in a ternary diagram (Figures 19-21). In 
addition, sediment mean phi size, mode, and textural group are listed in Tables 4-6. More 
detailed information is shown in Appendix 2. 
 The two Mississippi sites, BH and PACB, are relatively coarse-grained. BH contains 
approximately 30-35% sand in the upper (0-3 cm) and lower (27-30 cm) portions of the sediment 
core, while the middle portion (12-15 cm) grades to approximately 50% sand, perhaps due to 
inputs of tidal surge from a storm event. Overall, PACB is generally coarser than BH. BH is 
located in an inlet setting, while PACB is in a location that is more open to the Gulf and 
therefore more likely to receive coarse-grained sediments from higher-energy processes. PACB 
graded from 64% sand at the top to 74% sand at the bottom. BH is classified as a sandy silt 
throughout the entirety of the 30-cm core. PACB sediments grade from a muddy sand in the 
upper portion, through silty sand in the middle portion, and to silty sand to sandy silt in the 
lowest depth.  
49 
 
 The four Louisiana sites, RG, BD, BB, and BJN, showed variance in their grain size but 
are generally finer-grained relative to the two Mississippi sites. RG, the control site for the 
sampled Louisiana wetlands, is characterized by the coarsest-grained sediments. Sediments in 
RG were composed of approximately 50% sand in the upper (0-3 cm) and middle (12-15 cm) 
portion of the core, and graded to muds (silt and clay) in the lowest portion (27-30 cm) of the 
core. BD was dominated by fine-grained sediments, containing no sand. BD sediments become 
finer with depth, grading from about 70% silt and 30% clay in the upper part (0-3 cm) to about 
57% silt and 43% clay in the bottom (27-30 cm) portion. BB was also sand free, and sediments 
become finer with depth as well. BB sediments are composed of approximately 75% silt and 
25% clay in the upper portion (0-3 cm), and about 56% silt and 44% clay in the lower portion 
(27-30 cm). BJN also contained no sand; sediments are relatively coarser in the upper and lower 
parts (67% and 87% silt, respectively), and somewhat finer (58% clay) in the middle (12-15 cm) 
portion. The dominance of fine-grained sediments at these sites reflects the low energy 
environments within the Barataria Bay.   
Sediment grain size is important because of its effect on metal and oil retention in 
wetland sediments. Finer-grained sediments (i.e., clay minerals, oxides, sulfides, and organic 
matter) are the primary adsorptive surface for metals (Figure 22) and oils in marsh environments 
(Dzombak and Luthy, 1984). Conversely, coarser-grained sediments, such as quartzose and 
feldspathic sand, show limited ability to adsorb oil or metals (Ciccioli et al., 1980; Rogers et al., 
1980). 
50 
 
 
Figure 19. Folk classification ternary diagram showing sand, silt, and clay percent at 0-3 cm depth of ten 
different salt-marsh sites. 
 
Table 4. Textural parameters and classification of sediments in upper parts of cores from the 10 study 
sites. 
Sample 
ID 
Sand Silt Clay Sediment Name Textural 
Group 
 % % %   
      
WB 0.00 54.03 45.97 Mud Mud 
LB 75.25 15.87 8.88 Muddy very fine sand Muddy sand 
WI 88.46 7.93 3.61 Fine silty medium sand Silty sand 
BH 35.87 45.13 19.01 Very fine sandy coarse silt Sandy silt 
PACB 63.68 23.88 12.44 Muddy fine sand Muddy sand 
RG 56.69 34.83 8.47 Very coarse silty very fine sand Silty sand 
BD 0.00 70.31 29.69 Medium silt Silt 
BB 0.00 75.97 24.03 Medium silt Silt 
BJN 0.00 67.34 32.66 Very coarse silt Silt 
BJS 0.00 77.33 22.67 Very coarse silt Mud 
51 
 
 
Figure 20.  Folk classification ternary diagram showing sand, silt, and clay percent at 12-15 cm depth of 
ten different salt-marsh sites. 
 
Table 5. Textural parameters and classification of sediments in middle parts of cores from the 10 study 
sites. 
Sample 
ID 
Sand Silt Clay Sediment Name Textural 
Group 
 % % %   
      
WB 0.00 60.78 39.22 Mud Mud 
LB 83.45 11.48 5.07 Very coarse silty very fine sand Silty sand 
WI 93.30 4.00 2.70 Medium sand  Sand 
BH 50.63 37.07 12.30 Fine sandy very coarse silt  Sandy silt 
PACB 56.02 29.63 14.35 Very coarse silty fine sand  Silty sand 
RG 47.49 37.20 15.31 Very fine sandy very coarse silt  Sandy silt 
BD 0.00 65.55 34.45 Mud  Mud 
BB 0.00 62.09 37.91 Mud  Mud 
BJN 0.00 41.37 58.63 Mud  Mud 
BJS 0.00 73.57 26.43 Coarse silt  Silt 
52 
 
 
Figure 21.  Folk classification ternary diagram showing sand, silt, and clay percent at 27-30 cm depth of 
ten different salt-marsh sites. 
 
Table 6. Textural parameters and classification of sediments in middle parts of cores from the 10 study 
sites. 
Sample 
ID 
Sand Silt Clay Sediment Name Textural 
Group 
 % % %   
      
WB 0.00 61.73 38.27 Mud Mud 
LB 69.08 17.81 13.11 Muddy fine sand Muddy sand 
WI 92.66 4.66 2.68 Medium sand Sand 
BH 29.04 59.48 11.47 Very fine sandy coarse silt Sandy silt 
PACB 74.08 21.85 4.07 Coarse silty fine sand Silty sand 
RG 0.00 68.05 31.95 Medium silt Silt 
BD 0.00 57.52 42.48 Mud Mud 
BB 0.00 56.71 43.29 Mud Mud 
BJN 0.00 87.16 12.84 Medium silt Silt 
BJS 0.00 73.49 26.51 Coarse silt Silt 
53 
 
Mineralogy of sediments in the upper, middle, and lower sections of the cores was 
determined utilizing the XRD analyses described in the Methods section. Mineral contents in 
these sections are summarized in Tables 7-9. The percentages defined for the minerals are weight 
percent. Throughout all three sections of the sediment core, quartz and various clays are the 
primary minerals detected, reflecting the grain-size data with silt- and clay-sized particles 
comprising the majority of the samples. In the upper portion of the core, only a very few sulfates 
and sulfides were detected the XRD analysis. In the middle section of the sediment core, sulfide 
minerals show a marked increase, especially at oiled the Louisiana sites. In the lower section of 
the sediment core, sulfides, especially non-iron sulfides, show a very marked increase. 
Mineralogy of estuarine sediments is important because it reflects certain hydrological 
and geochemical changes taking place at depth. Formation of certain minerals can have profound 
effects on the pore-water chemistry in wetlands. For example, the formation of an evaporate 
mineral would reduce sulfate and other ion concentrations in porewaters. Clay minerals and 
sulfide solids have great sorbing capabilities to reduce metal concentrations in porewaters. At the 
Mississippi sites, more clay minerals are present in BH than in PACB, indicating possible higher 
metal adsorption capability in BH relative to PACB.  However, the levels of certain trace metals 
are slightly higher in PACB sediments than those in BH (see Sediment Geochemistry section), 
indicating minor metal contamination derived from spilled oils or other sources. At Louisiana 
sites, all three of the heavily-oiled zones (BD, BB, and BJN) contain higher clay mineral 
contents than does the slightly contaminated RG site. This suggests a higher metal retention 
potential at BD, BB, and BJN sites. 
Iron and non-iron sulfide minerals were common minerals present in the middle (12-15 
cm) and deepest (27-30 cm) sections of the sediment cores, especially in the more heavily-oiled 
54 
 
Louisiana marshes. In contrast, the top sections of the sediment cores show little or no sulfide 
solids at all the sites. The top portion near the sediment-water interface is under less- 
reducing conditions. Sulfates are generally predominate in the uppermost section of the cores,  
while sulfide solids formed from bacterial sulfate reduction dominate at greater depths under 
strong reducing conditions (see Background section). The fact that very few sulfates are found in 
the middle and lower sections of the sediment cores suggests either that nearly all sulfate solids 
have been reduced to sulfide by SRB at depth, or that they never formed at all.  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
55 
 
Table 7. Average mineral composition of sediment samples from XRD analyses for 0-3 cm interval. 
 
 
 
 
Table 8. Average mineral composition of sediment samples from XRD analyses for 12-15 cm interval. 
Minerals  WB    LB WI BH PACB RG BD BB BJN BJS 
12-15 cm  %  % % % % % % % % % 
           
Quartz  54 63 88 66 84 41 27   9 29 54 
Clays 20 29   7 26   9 52 15 51 51 15 
Sulfates   9   0   5   8   7   7 16 12   7   0 
Fe Sulfides   8   0   0   0   0   0 15   9 13   6 
Non-Fe Sulfides   9   8   0   0   0   0 27 19   0 25 
Other   0   0   0   0   0   0   0   0   0   0 
           
 
 
 
Table 9. Average mineral composition of sediment samples from XRD analyses for 27-30 cm interval. 
Minerals  WB    LB WI BH PACB RG BD BB BJN BJS 
27-30 cm  %  % % % % % % % % % 
           
Quartz  26 79 82 49 63 56 18 58 49 54 
Clays 42 16 12 23 24 23 41 29 15 19 
Sulfates   4   0   0   4   8   0   9   0   0   7 
Fe Sulfides 28   1   6   0   5   7   3   0   5   6 
Non-Fe Sulfides   0   4   0   3   0 14 29   6 31 14 
Other   0   0   0 21   0   0   0   7   0   0 
           
Minerals  WB    LB WI BH PACB RG BD BB BJN BJS 
0-3 cm  %  % % % % % % % % % 
           
Quartz  46 63 75 73 83 53 57 43 57 65 
Clays 48 37 15 27   9 41 27 50 43 15 
Sulfates   0   0 10   0   8   6   0   7   0 20 
Fe Sulfides   0   0   0   0   0   0   5   0   0   0 
Non-Fe Sulfides   0   0   0   0   0   0   0   0   0   0 
Other   6   0   0   0   0   0 11   0   0   0 
           
56 
 
Sediment Geochemistry  
The determination of bulk sediment geochemistry is important to this study, as it allows 
for quantification of total organic carbon contents and trace-metal concentrations, as well as an 
assessment of geochemical impacts of the oil spill on marsh sediments. Analyses involve the 
total digestion analysis via ICP/MS, petrographic (image) and semi-quantitative elemental 
analyses using SEM and EDAX, high-resolution microanalysis of sulfide solids using Laser 
Ablation ICP/MS, and TOC analysis. Sediments also were analyzed for their stable carbon 
isotopic signatures for comparison with marsh plants and initial BP crude oil. In addition to 
geochemical analyses, oil compounds extracted from sediments were analyzed for their general 
geochemical characteristics via GC-MS in full scan mode. Certain samples were further analyzed 
via GC-MS under high sensitivity single ion mode (SIM), allowing for characterization of 
petroleum biomarkers with a specific mass-to-charge (m/z) ratio of 191.  
Geochemical results from total digestion analysis show variations in concentrations of 
major and trace elements with depth (Figures 22 to 40, Appendices 3, 4).  The results are also 
plotted as box plots to illustrate the spatial variability among sites (Figures 22 to 40). Seventeen 
metals were chosen for analysis because they represent common contaminants in salt marshes 
(Huerta-Diaz and Morse, 1992; Olivie-Lauquet et al., 2000; Davranche et al., 2011), in crude oil 
(Karchmer and Gunn, 1952; Ball et al., 1960; Barwise, 1990; Kennicutt et al., 1991), or both. 
The results show that concentrations of numerous elements (e.g., Ni, Cu, Pb, Zn, Sr, Co, V, Ba, 
Hg, As, S, Fe) are generally higher in heavily-oiled Louisiana zones compared to less-affected 
and pristine sites at Mississippi.  
At the Mississippi sites, the concentrations of many metals in PACB sediments are 
typically 1 to 3 times higher than those associated with BH (Figures 22 to 40), despite the fact 
57 
 
that BH contains finer-sized sediments with greater metal sorption capabilities. PACB was 
slightly contaminated with the Macondo-1 oil spill, while BH was unaffected. Spilled oil, and 
perhaps higher terrestrial metal inputs, may account for the increased level of metals in PACB 
sediments.  In addition, many metals (Fe, S, Pb, Co, As, Hg) show a trend of increasing 
concentration from the surface to the middle parts (12-15 cm) of cores. The majority of metals at 
both sites decrease from the middle section to the bottom section (27-30 cm) of the cores. The 
slight enrichment of trace metals in shallow (post-industrial) sediments may also be related to 
riverine inputs derived from anthropogenic sources, as low sedimentation rates in these areas 
(approximately 0.2 cm/year) (Corbett et al., 2004) suggest that approximately only the upper 20 
cm of the sediment core is within the last 100 years, a period of time that would span the 
majority of the industrial age for this area of the United States.  
Metal concentrations in oiled Louisiana marsh sediments are much higher (as much as 
one order of magnitude) than those in Mississippi marshes (Appendices 3, 4). The slightly-oiled 
RG site contains the highest average concentrations for a few metals (e.g., As, Th, Ba, Hg). 
Otherwise, sites BD and BB generally contain the highest average metal concentrations.   
Because oil is known to carry numerous trace metals in its complex chemical make-up, it 
is likely that the oil that has inundated BD, BB, and BJN sites resulted in a high influx of trace 
metals. RG hosts the highest average concentrations of particular metals (As, Th, Ba, Hg) that 
are often anthropogenically concentrated. The RG site is located near the major outlet for Lake 
Pontchartrain in a highly-trafficked area. It is likely that RG receives metal inputs from Lake 
Pontchartrain discharge and heavy motor traffic. This can explain why the slightly-oiled RG site 
contains higher average metal levels than BJN, a site that was much more affected by the oil 
spill. BD and BB are located slightly further inland than BJN, yet they generally contained the 
58 
 
highest average metal concentrations. There are two possible interpretations for this: 1) BD and 
BB both have more metal sorption capabilities owing to their finer-grained sediments than BJN; 
and 2) BD and BB are less open to seawater flushing. Any oil that was washed into BB, and 
especially BD, likely became trapped while it slowly degraded instead of being flushed out. The 
Louisiana sites are similar to the Mississippi sites in that metal concentrations are generally 
higher in the upper and middle portions of the sediment columns while decreasing in the lower 
portions. A possible mechanism for this model is that metals are intruding down into the mid-
portion of the sediment columns, and the decrease of metal concentrations towards the lower 
sections of the sediment core reflects pre-industrial metal concentration levels. 
The level of certain metals/metalloids (e.g., arsenic) correlated well with (r = 0.47) the 
abundance of clay-sized particles (Figure 41). This confirms that the fine-grained sediments in 
salt marshes have high capacity to adsorb metals derived from terrestrial or marine sources.  This 
correlation suggests that the retention of trace metals in salt marshes is strongly controlled by the 
geology and sediment characteristics of each individual site. 
 
 
Figure 22. (A) Depth profile and (B) box and whisker plot showing depth- and spatial-variability of iron. 
Contaminated sites show much higher iron levels compared to those at non-contaminated sites. 
(A) (B) 
59 
 
 
 
Figure 23. (A) Depth profile and (B) box and whisker plot showing depth- and spatial-variability of 
sulfur. Contaminated sites show much higher sulfur levels compared to those at non-contaminated sites.  
 
 
 
 
 
 
 
 
 
 
 
Figure 24. (A) Depth profile and (B) box and whisker plot showing depth- and spatial-variability of 
copper. Contaminated sites show much higher copper levels compared to those at non-contaminated sites.   
(B) (A) 
(A) (B) 
60 
 
 
 
Figure 25. (A) Depth profile and (B) box and whisker plot showing depth- and spatial-variability of lead. 
Contaminated sites show much higher lead levels compared to those at non-contaminated sites. 
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 26. (A) Depth profile and (B) box and whisker plot showing depth- and spatial-variability of zinc. 
Contaminated sites show much higher zinc levels compared to those at non-contaminated sites. 
 
(B) (A) 
(B) (A) 
61 
 
 
 
Figure 27. (A) Depth profile and (B) box and whisker plot showing depth- and spatial-variability of 
nickel. Contaminated sites show much higher nickel levels compared to those at non-contaminated sites. 
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 28. (A) Depth profile and (B) box and whisker plot showing depth- and spatial-variability of 
cobalt. Contaminated sites show much higher cobalt levels compared to those at non-contaminated sites. 
(B) (A) 
(B) (A) 
62 
 
 
 
Figure 29. (A) Depth profile and (B) box and whisker plot showing depth- and spatial-variability of 
manganese. Contaminated sites show much higher manganese levels compared to those at non-
contaminated sites. 
 
 
 
 
 
 
 
 
 
 
 
Figure 30. (A) Depth profile and (B) box and whisker plot showing depth- and spatial-variability of 
arsenic. Contaminated sites show much higher arsenic levels compared to those at non-contaminated 
sites. 
(B) (A) 
(B) (A) 
63 
 
 
 
Figure 31. (A) Depth profile and (B) box and whisker plot showing depth- and spatial-variability of 
thorium. Contaminated sites show much higher thorium levels compared to those at non-contaminated 
sites. 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 32. (A) Depth profile and (B) box and whisker plot showing depth- and spatial-variability of 
strontium. Contaminated sites show much higher strontium levels compared to those at non-contaminated 
sites. 
(B) (A) 
(B) (A) 
64 
 
 
 
Figure 33. (A) Depth profile and (B) box and whisker plot showing depth- and spatial-variability of 
vanadium. Contaminated sites show much higher vanadium levels compared to those at non-contaminated 
sites. 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 34. (A) Depth profile and (B) box and whisker plot showing depth- and spatial-variability of 
phosphorous. Contaminated sites show much higher phosphorous levels compared to those at non-
contaminated sites. 
(B) (A) 
(B) (A) 
65 
 
 
 
Figure 35. (A) Depth profile and (B) box and whisker plot showing depth- and spatial-variability of 
barium. Contaminated sites show much higher barium levels compared to those at non-contaminated 
sites. 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 36. (A) Depth profile and (B) box and whisker plot showing depth- and spatial-variability of 
aluminum. Elevated aluminum levels likely reflect anthropogenic contamination. 
 
(B) (A) 
(B) (A) 
66 
 
 
 
Figure 37. (A) Depth profile and (B) box and whisker plot showing depth- and spatial-variability of 
mercury. Contaminated sites generally show much higher mercury levels compared to those at non-
contaminated sites. 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 38. (A) Depth profile and (B) box and whisker plot showing depth- and spatial-variability of 
calcium. Elevated calcium levels likely reflect anthropogenic contamination. 
 
(B) (A) 
(B) (A) 
67 
 
 
 
Figure 39. (A) Depth profile and (B) box and whisker plot showing depth- and spatial-variability of 
magnesium. Contaminated sites show much higher magnesium levels compared to those at non-
contaminated sites. 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 40. (A) Depth profile and (B) box and whisker plot showing depth- and spatial-variability of 
sodium. Contaminated sites show much higher sodium levels compared to those at non-contaminated 
sites. 
(B) (A) 
(B) (A) 
68 
 
 
Figure 41. An increase in As concentration corresponds to increasing clay content. 
 
 
Metal Enrichment in Wetland Sediments 
Concentrations of elements derived from bulk sediment geochemical analysis were 
normalized to aluminum, the selected reference element (Table 10). The average normalized 
enrichment factor (ANEF)  
crust
crust
sample
sample
AlMe
Al
Me
      (1) 
 
evaluates the enrichment of elements relative to aluminum. Aluminum is the third most abundant 
element in the earth?s crust (Wedepohl, 1995). Since there are no known anthropogenic sources 
of aluminum in marsh sediments, any metal with ANEF above 1 can be inferred as likely 
receiving anthropogenic inputs other than natural terrigenous sources.  
69 
 
Overall, ANEF values show enrichment of many metals at marsh sites beyond levels of 
terrestrial inputs, suggesting anthropogenic contamination from either industrial sources or from 
a marine source, such as an oil spill. In Mississippi, PACB has much higher ANEF values for As 
(mean = 35.28) in comparison to those at BH (mean = 13.62). In addition, sediments at PACB 
are enriched in many other metals (Ni, Co, V, Zn, Fe, Mn, etc.) with respect to those at BH. Ni 
and V are common metals found in crude oil, implying that PACB might be slightly 
contaminated by oil. BH is likely receiving anthropogenic inputs from nearby streams, leading to 
enriched metal concentrations. Although PACB also may receive some anthropogenic input, it is 
located farther from major stream sources than is BH. The higher enrichment levels observed at 
site PACB (those that are above levels at site BH) must be received from non-terrestrial sources. 
Spilled oil from the Macondo-1 well likely is responsible for elevated levels of certain metals 
(e.g., Zn, Mn, Fe, As, Ni, Co, V, Mg) at PACB.  
The Louisiana sites are enriched in many metals. Although RG is a relatively unaffected 
site, it is more highly enriched in many metals than heavily oiled sites BD, BB, and BJN. RG is 
located in close proximity to Lake Pontchartrain and Interstate 10, and therefore is subject to 
many potential anthropogenic sources of contamination from human traffic (boats, cars, etc). 
Carbon isotope signatures of sediments (see section below) indicate that RG only received slight 
contamination from the Macondo-1 well oil. Highest ANEF values of common elements in crude 
oil (e.g., Ni, V, S) are observed at BD, BB, and BJN sites in the Barataria Bay, suggesting that 
much of metal contamination at these sites is derived directly from the BP Macondo-1 oil spill. 
 
 
 
70 
 
Table 10. Calculated average normalized enrichment factor (ANEF) of selected elements at various salt 
marsh sites.   
Element WB LB WI BH PACB RG BD BB BJN BJS 
           
           
Cu 4.40 4.95 21.91 5.68 5.68 20.68 15.49 24.89 16.27 18.43 
Pb 4.53 6.32 6.04 8.92 5.87 7.61 5.39 7.64 6.70 6.28 
Zn 4.85 1.34 6.79 1.14 3.95 7.98 7.62 8.65 7.15 6.89 
Mn 2.12 0.34 0.90 0.47 3.44 3.93 3.46 3.42 3.06 3.59 
Fe 3.97 3.04 3.16 3.95 4.59 4.07 3.70 4.17 4.17 3.80 
Ba 0.16 0.13 0.15 0.18 0.17 1.22 0.74 0.82 0.93 0.85 
Hg 4.71 1.76 10.94 1.55 1.15 7.17 4.63 6.24 8.38 7.52 
As 20.97 23.48 23.78 13.62 35.28 27.73 16.92 16.79 16.58 23.34 
S 75.51 120.86 92.14 153.08 122.59 85.22 153.72 155.79 173.73 141.57 
Sr 0.38 0.81 0.82 0.88 0.64 0.85 1.60 1.66 2.01 1.63 
Ni 2.55 1.88 3.83 1.64 2.87 5.34 6.30 7.25 6.63 6.15 
Co 2.53 1.64 1.76 1.35 2.91 4.33 4.04 4.77 4.11 3.47 
V 2.57 4.74 3.58 2.53 4.56 3.49 3.26 3.39 3.92 3.79 
Th 2.69 4.67 2.37 4.54 3.89 4.38 2.71 2.98 3.36 3.80 
Ca 0.22 0.82 0.61 0.53 0.49 0.55 1.00 0.99 1.30 0.99 
Mg 1.23 1.40 3.14 1.92 2.04 2.45 3.97 3.95 4.43 4.21 
Na 0.77 2.55 4.74 3.28 2.82 1.44 4.58 4.52 6.08 4.77 
Al 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 
 
 
 
Total Organic Carbon in Sediments 
 Total organic carbon contents of sediments are summarized in Appendix 5. Results 
(Figure 42) not only show variations of TOC with depth, but also substantial differences among 
various marsh sites. BH shows slightly higher levels of TOC (mean = 5.0 %) than PACB (mean 
= 2.4 %), despite receiving no oil contamination. This suggests that BH receives more 
terrigenous carbon influx than does the PACB site. Moreover, BH is better sheltered from strong 
ocean currents from the Gulf and thus contains more fine-grained sediments than PACB. Fine-
grained sediments have greater potential to retain organic solids.  In contrast, PACB is open to 
flushing of ocean waves; it is likely that much of the oil contamination that the PACB site 
received has been dispersed and washed by longshore currents. TOC levels at heavily oiled 
71 
 
Louisiana sites (BD, BB, and BJN) are much higher (6.8 to 29 %) than those at RG site (mean = 
1.5%) and two Mississippi sites. The relatively low TOC and DOC contents at RG sites suggest 
that it was only slightly contaminated (compared to BD, BB, and BJN located in the Barataria 
Bay). 
 BD shows the highest TOC levels (up to 29%) among all marsh sites investigated in this 
study. BD is located in a narrow waterway landing into the large Batiste Bay; it is likely that oil 
plumes were funneled and concentrated through this narrow channel during high tides.  Large 
areas of dead marsh plants covered with oil were clearly visible in and around the BD, BB, and 
BJN sampling sites. All these sites show significant increases in TOC concentrations from the 
surface to middle sections (around 15 cm) of the core. The TOC contents in uppermost sediments 
may be reduced by microbial degradation, water mixing, wave flushing form tides, and the use of 
dispersants. Many oiled sites in the Barataria Bay have been treated by surface dispersant 
applications after oil washed ashore. Dispersants tend to change the inherent chemical and 
physical properties of oil so that natural microbes could digest oil faster (Kujawinski et al., 
2011).  Higher levels of TOC in contaminated sediments can be positively correlated to higher 
metal concentrations (Figure 43, Appendices 3, 4), indicating that organic carbon and metal 
contaminants are likely derived from the same source. TOC and DOC depth profiles also 
indicate that the contamination is not limited to surface sediments. Spilled oil may have spread 
throughout water column and, in addition to contaminating surface sediments, may have 
contaminated deeper sediments via mixing and intruding with denser seawater. 
 A linear relationship between DOC and TOC (r = 0.47) is observed, although the cause of 
correlation is not clear. This positive correlation suggests that either DOC or TOC may be used 
as an indicator for the level of oil contamination. Quantitative assessment of oil contamination 
72 
 
also may be achieved by the stable carbon isotopic signatures of bulk sediments (see Carbon 
Isotope section). 
Organic carbon is essential in wetlands, but too much of it can have a negative effect on 
wetlands. Elevated amounts of organic carbon can induce numerous detrimental effects: (1) 
organic carbon can be utilized as an electron donor by iron- and sulfate-reducing bacteria, 
thereby facilitating reducing conditions; (2) reducing conditions can lead to a subsequent 
mobilization of metals through disaggregation of host minerals; (3) organic matter can compete 
with metals for sorption onto mineral surfaces, further contributing to metal mobilization, and; 
(4) organic matter also can amplify the biological transformation of mercury into 
methylmercury.  
 
 
 
   Figure 42. (A) Depth profile and (B) box and whisker plot showing depth- and spatial-variability of   
   TOC. Contaminated sites show much higher TOC levels compared to those at non-contaminated sites. 
 
 
 
(B) (A) 
73 
 
 
Figure 43. Plot of higher Ni levels correspond more strongly to high TOC levels. 
 
 
 
Petrographic, SEM and LA-ICP-MS Analyses of Sulfide Solids 
Pyritic minerals with distinct framboidal form occur in Louisiana oiled marsh sediments 
(Figure 44).  Sedimentary pyrite that takes on a unique framboidal (?raspberry-like?) form has 
been interpreted to have originated authigenically (Berner, 1970; Wilkin and Barnes, 1996; 
Wilkin et al., 1996), biogenically (Folk, 2005; Donald and Southam, 1999), or a combination of 
both (Donald and Southam, 1999). Framboidal pyrites were found primarily at three heavily 
contaminated sites: BD, BB, and BJN. These three sites showed high levels of iron, sulfur, and 
TOC, the three necessary ingredients for sedimentary pyrite formation. Two Mississippi sites 
(BH and PACB) contained no or far fewer of pyrite-like sulfides. Thus, those sites were not 
examined. Only two of the sites hosting large amounts of framboidal sulfides (BD and BJN) 
were analyzed for their trace metal contents associated with pyrite. SEM and EDAX analysis 
74 
 
were first conducted in order to discern the grain size, texture, and chemical content of 
framboidal pyrites. SEM images demonstrate the occurrence of aggregates of equi-dimensional 
spheroids of about 10 ? 30 ?m (Figures 45-47). EDAX spectrum of these spheroids consistently 
results in peaks for Fe and S, with minor amounts of Si, O, and Al (Table 11). Other elements are 
much less abundant and thus cannot be quantitatively measured using EDAX. These iron sulfides 
have been interpreted as the pyritized corpses of nannobacterial cells embedded in decaying 
organic matter (Folk, 2005). Wilkin and Barnes (1996) presented formation mechanisms 
responsible for the unique pyrite framboid texture involving nucleation transform and 
aggregation of tiny microcrystals. The precipitation of framboidal pyrite was likely performed by 
sulfate-reducing bacteria fueled by inflow of organic matter.  
Influx of oil may affect the fate and transformation of trace metals in marsh sediments.  A 
question to be addressed in this research is whether the toxic metals (e.g., As and Hg) remain in 
solution or are largely sequestered in sulfide solids. Elevated levels of trace metals have been 
documented in oiled marsh sediments (see Sediment Geochemistry section). However, the pore-
water analysis showed very low metal concentrations in porewaters (Keimowitz, personal 
communication). It is hypothesized that many trace metals are sequestered in pyrite-like 
monosulfides formed in marsh sediments; those authigenic and biogenic pyrites have a large 
capacity for retaining chalcophile metals, thereby serving as ?sinks? for trace metals (Berner, 
1970; Huerta-Diaz and Morse, 1992; Orberger et al., 2003) in strongly-reducing conditions. 
 
 
 
 
75 
 
                   
                    
Figure 44. Photomicrographs in reflected light showing variations of the framboidal texture of biogenic 
pyrites formed in oiled Louisiana marshes. 
76 
 
 
 
 
Figure 45.  SEM photo and EDAX spectrum of framboidal pyrite (from BD S-2 Spectrum 2) 
showing iron and sulfur as primary constituents, with carbon being a lesser component. 
 
 
Start-up 
peak 
Fe 
C 
S 
77 
 
 
 
Figure 46.  SEM photo and EDAX spectrum of framboidal pyrite (from BD P-1 Spectrum 1) showing 
iron and sulfur as primary constituents, with O, Si, and Al being lesser components. 
Start-up peak 
Fe 
O 
S 
Al 
S
i 
78 
 
.
 
Figure 47.  SEM photo and EDAX spectrum of framboidal pyrite (BJN P-1 Spectrum 1) showing iron 
and sulfur as primary constituents, with calcium and titanium being lesser components. 
Start-up peak 
Fe 
Ti 
O 
S 
Si 
Ca 
79 
 
Table 11. Elemental composition by percentage of various slide-mounted and puck-mounted grains 
analyzed via SEM w/ EDAX. 
Sample Fe S Si Al  Total 
ID % % % %  % 
       
Slide-Mounted       
       
BD S-2 Spectrum 2 62.51 37.49 - -  100.00 
       
BD S-2 Spectrum 7 64.11 35.89 - -  100.00 
       
WB S-1 Spectrum 5 65.11 34.89 - -  100.00 
       
WB S-3 Spectrum 2 63.35 36.65 - -  100.00 
       
       
Puck-Mounted       
       
BD P-1 Spectrum 1 53.90 46.10 - -  100.00 
       
WB P-1 Spectrum 1 67.97 32.03 - -  100.00 
       
BJN P-1 Spectrum 1 32.64 55.10 8.80 3.46  100.00 
       
BJS P-1 Spectrum 1 50.61 48.24 1.15 -  100.00 
 
 
 
Trace metals, such as arsenic and mercury, however, were not detected by EDAX 
analyses. The sensitivity of the EDAX system appears to be insufficient for detecting minute 
quantities of trace metals that typically exist in sulfides. In order to quantify trace metal 
concentrations, laser ablation, coupled with high-resolution ICP-MS was used to measure the 
trace elements contents of sulfide solids. A petrographic microscope was utilized first to identify 
and locate crystals of framboidal pyrites. The selected crystals were ablated by the laser, and 
plasma containing the ablated particles was transported to the mass detector of ICP/MS system.  
The ablating spot size ranged from 15-25 ?m. Intensity (cps) of ionized metals associated with 
80 
 
the plasma cloud was recorded by a computer. The intensities give a relative abundance of the 
ions of interest. Intensities were then converted to concentrations using relative sensitivity 
factors determined on NIST SRM 610 (Gaboardi and Humayun, 2009).  This process has the 
capability of quantifying concentrations of trace metals with sensitivities that are orders of 
magnitude better than SEM/ EDAX. 
Several framboidal pyrites from BD and BJN sites were analyzed by LA-ICP-MS. A 
suite of metals of interest (S, V, Mn, Fe, Co, Ni, Cu, Zn, As, Se, Mo, Cd, Te, Hg, Pb) was 
decided ahead of time, and only those particular metals were measured for this study. Figures 48-
51 show the relative intensity of various metals with respect to time as the laser ablates deeper 
into crystals. Concentrations of metals have been normalized to iron and listed for each site 
studied (Tables 12-14). 
  Average S and Fe concentrations in framboid pyrites recovered from BD sites are 40.0 
% and 53.7 %, respectively. Among the three BJN samples, S averaged 33.7 % and Fe averaged 
59.3 %, respectively. These results confirmed that Fe and S are the main constituents in the 
samples. Analyzed pyrites also show high concentration of Mn, Pb, Zn, and As (average 
concentrations > 1,000 mg/kg) and minor amounts of Ni, Co, V, Hg, Se, and Cd. Metals Hg and 
Te are also present, but their concentrations are not calculated due to the lack of standard 
references.  In five samples (BD-4, BD-5, BD-6, BJN-1, BJN-2), some trace metals show very 
high concentrations. Over time, framboidal pyrites will stabilize, and their Fe/S ratios will 
change. As the grains mature and more iron and sulfur is accumulated, it is likely that trace metal 
sorption is slowed, leading to a decrease in the concentrations of these minor constituents. 
Samples BD-1, BD-3, BD-8, BD-9, and BJN-3 appeared to have the framboidal shape, but are all 
likely poorly-crystallized to amorphous Fe/S solids, as their Fe/S ratios are all nearly a 1:1 ratio 
81 
 
versus the framboidal pyrites with different Fe/S ratios (i.e. higher Fe and Lower S 
concentrations). Trace metals are sufficiently lower in these grains, so it is likely that as they 
sorbed more sulfur from the sulfur-rich waters, their ability to sorb trace elements declined, 
ultimately leading to a loss of intensity for trace elements in these grains. With continued sulfur 
saturation, it is likely that over time the amorphous Fe/S solids will convert into pyrite (FeS2).
82 
 
            
            
Figure 48. LA-ICP/MS spectrum of pyrites from Bayou Dulac, samples BD-1 through BD-4.  
(BD-1) (BD-2) 
(BD-3) (BD-4) 
83 
 
             
            
Figure 49. LA-ICP/MS spectrum of pyrites from Bayou Dulac, samples BD-5 through BD-8. 
(BD-7) 
(BD-6) (BD-5) 
(BD-8) 
84 
 
 
Figure 50. LA-ICP/MS spectrum of pyrites from Bayou Dulac, sample BD-9. 
 
 
 
 
 
 
 
 
(BD-9) 
85 
 
            
          
Figure 51. LA-ICP/MS spectrum of pyrites from Bay Jimmy North, samples BJN-1 through BJN-3.
(BJN-3) 
(BJN-1) (BJN-2) 
86 
 
Table 12. Average elemental concentrations measured from LA-ICP/MS analysis of pyrites from BD. 
Results are normalized to Fe. 
Metals Conc. BD 1 BD 2 BD 3 BD 4 BD 5 
       
S wt. % 47.9 31.3 49.6 14.2 2.5 
V mg/kg 208 477 10 134332 5202 
Mn mg/kg 738 4131 1312 14768 13968 
Fe wt. % 51.2 54.1 50.0 62.8 91.9 
Co mg/kg 29 87 209 235 739 
Ni mg/kg 51 0 449 240 1030 
Cu mg/kg 130 1071 38 1191 642 
Zn mg/kg 192 1872 83 18006 7765 
As mg/kg 7591 137509 2238 24137 679 
Se mg/kg 6 7 5 68 27 
Mo mg/kg 16 32 48 1096 274 
Cd mg/kg 3 9 4 394 32 
Te125(LR)* mg/kg - - - - - 
Hg202(LR)* mg/kg - - - - - 
Pb mg/kg 280 1128 43 36000 26024 
* not calculated due to lack of calibration standards 
 
 
 
Table 13. Average elemental concentrations measured from LA-ICP/MS analysis of pyrites from BD. 
Results are normalized to Fe. 
Metal Conc. BD 6 BD 7 BD 8 BD 9 
      
S wt. % 43.4 40.7 50.7 52.5 
V mg/kg 14569 312 39 4 
Mn mg/kg 6824 4718 1216 72 
Fe wt. % 25.6 51.6 48.9 47.3 
Co mg/kg 74 59 137 27 
Ni mg/kg 0 0 237 0 
Cu mg/kg 1814 1402 230 98 
Zn mg/kg 3859 1127 84 65 
As mg/kg 285240 75952 1295 2033 
Se mg/kg 0 0 3 0 
Mo mg/kg 14 243 44 2 
Cd mg/kg 138 50 6 4 
Te125(LR) mg/kg - - - - 
Hg202(LR) mg/kg - - - - 
Pb mg/kg 6367 1063 149 20 
87 
 
Table 14. Average elemental concentrations measured from LA-ICP/MS analysis of pyrites from BJN. 
Results are normalized to Fe. 
Metal Conc. BJN 1 BJN 2 BJN 3 
     
S wt. % 26.2 23.8 51.0 
V mg/kg 65984 83702 21 
Mn mg/kg 1901 1994 1068 
Fe wt. % 64.5 65.0 48.4 
Co mg/kg 135 130 1484 
Ni mg/kg 0 0 1671 
Cu mg/kg 1558 1390 312 
Zn mg/kg 4543 4211 56 
As mg/kg 1200 1500 652 
Se mg/kg 141 191 18 
Mo mg/kg 748 773 74 
Cd mg/kg 532 497 10 
Te125(LR) mg/kg - - - 
Hg202(LR) mg/kg - - - 
Pb mg/kg 17011 20068 445 
 
 
 
 
Microbial Communities in Affected Wetlands 
The most probable number (MPN) technique was utilized to quantify iron- and sulfate-
reducing bacteria in samples taken from the top (0-3 cm), middle (12-15 cm), and bottom (27-30 
cm) portion of sediment cores from each site. It was anticipated that anaerobic microbial 
populations would increase with depth in sediments, in response to more reducing conditions. 
Results show that, at many sites, the bacteria were more abundant in the upper portions of the 
sediments and that the bacterial populations varied inversely with depth (Appendices 6-7). In 
Mississippi, BH sediments contain significantly lower amounts of SRB than those at PACB. 
Perhaps levels of SRB activity increased in PACB in response to small inflow of oil from the 
Macondo-1 spill. In Louisiana, RG actually contained some of the highest numbers of SRB 
88 
 
(1600 MPN/g in the 0-3 cm section, and >1600 MPN/g in the 12-15 cm and 27-30 cm section) 
despite containing lower DOC and TOC concentrations than the other Louisiana sites. BD and 
BB show similarly high numbers in the upper sediments, with decreasing numbers deeper in the 
sediments. BJN had relatively high numbers in the upper section, but overall averaged only 
104.5 MPN/g, despite being heavily contaminated. The majority of sites sampled showed >1600 
MPN/g of FeRB, which plays a key role in iron reduction and subsequent formation of iron 
sulfide. 
Sulfate-reducing bacteria were expected to be more active in deeper layers due to more 
favorable reducing conditions. The SRB MPN results showed an opposite trend: the anaerobic 
bacterial communities decreased in number with depth. A likely explanation for this is that there 
is not enough organic carbon to sustain larger communities beneath the sediment surface. 
Moreover, most of the oil that washed onshore likely settled at the of water-sediment interface 
and enhanced the microbial activities there. Many sites show high values of SRB through the 
sampled intervals at depth, supporting active SRB biomineralization processes (i.e., sulfide 
formation) that retain most trace metals in sediments. The Mississippi PACB site was slightly 
contaminated with oil and contains higher bacteria populations than BH (which was unaffected), 
largely due to more organic carbon (electron donors) in the environment. It is not clear why RG 
contains higher numbers of bacteria than the contaminated sites; a possible reason is that the RG 
site is more restricted to wave flushing than the Barataria Bay sites, meaning that the Barataria 
Bay sites would become more oxidized. It is possible that those sites in the more open Barataria 
Bay could be subjected to other, not yet understood conditions which negatively affect microbial 
communities.
89 
 
GC-MS Analysis of Bulk Oil and Petroleum Biomarkers 
Organic compounds were extracted from oiled sediments and contaminated plant samples 
using a modified EPA 3570 method. In addition, initial source crude from the Macondo-1 well 
acquired from BP was prepared. All extracted samples were diluted with hexane using a 200:1 
ratio. Most of the solutions produced from unaffected sites were clear, while samples extracted 
from oiled sites exhibited yellowish hues or were dark brown to black. GC-MS analysis of these 
extracted organic compounds was conducted to define the source and the extent of degradation 
of spilled oil in affected salt marshes.  
Samples were first analyzed via CG-MS-TOF. GC-MS full-scan spectra allow the entire 
range of compounds comprising the hydrocarbon to be shown. Full-scan spectra alone are not 
very useful for hydrocarbon fingerprinting. Hence, in order to fingerprint the source of oil, the 
GC-MS was also run in high-sensitivity selected ion mode (SIM) to provide an analysis of 
specific compounds known as biomarkers. GC-MS-SIM analysis produces fragmentograms that 
show unique spectra for ions with specific mass-to-charge ratios (m/z) of 191, 217, and 218. 
The samples analyzed by GC-MS analysis include: (1) a sample of crude oil from the 
Macondo-1 well; (2) samples of degraded oil scrapped off plants collected at BJN site; (3) PAHs 
extracted from surface oiled sediments at BJN; and (4) PAHs extracted from sediments located 
in the middle (12-15 cm) of the sediment columns at BD sites.  
A GC-MS full spectrum of the BP Macondo-1 crude oil is shown in Figure 52.  In GC-
MS analysis, lighter organic components are vaporized during early stages at lower temperatures 
and heavier ones are vaporized later at higher temperatures. The GC-MS spectrum clearly shows 
that the BP crude sample is much more plentiful in lighter components, as indicated by the 
occurrence of highest peaks in the first 14 minutes. Figure 55 shows a full-scan chromatogram of 
90 
 
BJS oiled sediment, indicating the presence of various hydrocarbons. Though not part of the 
areas analyzed for this study, BJS is in very close proximity to BJN, and likely resembles what a 
full-scan would look like for degraded oil in BJN. Heavier components persist (over the 14 ? 26 
minute range), while lighter compounds are largely absent from the graph. Fragmentograms of 
degraded oils extracted from a depth of 12 ? 15 cm from oiled BJS and BD sites also show a 
relative lack of light compounds but exhibit multiple high-intensity peaks over the 16-21 minute 
range for heavy compounds (Figure 56). This pattern indicates that the degraded oils are more 
enriched in heavier compounds than the initial BP source oils. This large contrast demonstrates 
that, whereas most light compounds are biodegraded or vaporized quickly (within months), the 
residues of heavier fractions of oil remain in sediments, and even as the oil seeps deeper into 
sediments, bacteria are not necessarily degrading the heavier fractions. Oudot and Chaillan 
(2010) have shown that the heavier saturated components of oil (e.g., asphaltenes, resins, and 
polycyclic aromatics) can remain in the environment for at least decades after contamination, and 
this pattern can be seen in the spectra for the degraded oils extracted from marsh plants and 
sediments at heavily contaminated Louisiana sites. In addition to typical oil degradation 
(evaporation, dispersion, etc.), it seems likely that microbial communities are preferentially 
utilizing the lighter carbon compounds as their carbon source, leading to a residual oil, rich in 
heavy components. 
Petroleum biomarkers with specific mass-to-charge (m/z) ratios (i.e. m/z 191, 217, 218, 
etc.) are made up of terpanes (m/z 191) and steranes (m/z 271, 218) from a particular source and 
reservoir. These specific biomarkers are resistent to biodegradation and environment alteration 
compared to most organic compounds, thus providing a reliable way to correlate the spilled oils 
with their initial sources. Biomarkers of the hydrocarbon have also been analyzed by GC-MS-
91 
 
SIM in an attempt to correlate the degraded oils from marsh sediments and plants to the 
Macondo-1 well oil. Steranes and terpanes are great biomarkers to use because they tend to 
remain unchanged through various degradation processes; they are often used in oil-oil and oil-
source correlations (Barakat et al., 2002). Ratios of different compounds analyzed in the m/z 191 
peaks of oil from sediments and plants (Table 15) match well with ratios found in the initial 
crude oil sample from the BP well, despite differences in the fragmentograms from the oil found 
in the sediments and plants is quite different from the BP sample. Ts/Tm (18?-22,29,30-
trisnorneohopane/17?-22,29,30-trisnorhopane) ratios, which are routinely used in oil-spill 
forensics due to their general lack of degradation, show a narrow window of ratios among the 
various samples analyzed (0.900-1.078), suggesting a common origin for them all. Tricyclic 
terpanes are also very good fingerprinting compounds; 24Tri/23Tri (C24 tricyclic terpane/C23 
tricyclic terpane) ratios also show a very narrow range (0.909-1.040) among the various 
contaminated sample sites and Macondo-1 source crude. C29/C30 (17?,21?(H)-30-
norhopane/17?, 21?(H)-hopane) ratios among plant and surface sediment samples and the BP 
crude sample fall within a narrow range (0.531-0.592). However, sediments collected from the 
middle of the sediment columns in Bayou Dulac have slightly different signatures (0.691). Ratios 
of 29D/29H (18?(H)-30-norneohopane/17?,21?(H)-30-norhopane) in the Bay Jimmy North and 
BP samples are very similar (0.557 and 0.564, respectively).  
In summary, the results suggest that microbes are degrading the lighter compounds, as 
evidenced in the weathering patterns of the full GC-MS spectrum and fragmentograms from the 
various oiled sediments and degraded oil samples. Biomarkers, due to their resistance to 
biodegradation over long periods of time in the environment, show an affinity between BP crude 
oil and the oils from contaminated sediments and plants. Our GC-MS spectrum confirms that 
92 
 
heavier components are not degraded (microbially or otherwise) or vaporized, as evidenced by 
the enrichment of heavier compounds in the fragmentograms. 
 
 
93 
 
 
Figure 52. Gas chromatogram of BP Macondo-1 crude oil showing much higher quantities of lighter compounds (up to the 14 minute mark) than 
heavier ones (later times).
94 
 
 
 
Figure 53. Fragmentograms produced by GC/MS-SIM analysis showing the enrichment of heavier 
carbon components in (A) BP crude oil from the Macondo-1 well, (B) degraded oil from plants in Bay 
Jimmy South, and (C) degraded oil from plants in Bay Jimmy North. 
95 
 
 
Figure 54. Fragmentograms produced by GC/MS-SIM analysis showing the enrichment of heavier 
carbon components in (A) oil from surficial sediment samples in Bay Jimmy South, and (B) oil from 
surficial sediment samples in Bay Jimmy North. 
 
 
 
96 
 
 
 
 
Figure 55. Gas chromatogram of oiled BJS sediment (0-3 cm) showing much higher quantities of heavier 
components, implying that microbes are preferentially utilizing the lighter components of oil as a carbon 
source. 
 
97 
 
 
Figure 56. Fragmentograms produced by GC/MS-SIM analysis showing the enrichment of heavier 
carbon components in (A) oil from 12-15 cm deep  sediment samples in Bay Jimmy South, and (B) oil 
from 12-15 cm sediment sample in Bay Jimmy North. 
 
 
 
 
98 
 
Table 15.  Calculated ratios of selected biomarkers associated with BP crude oil and various oil samples 
extracted from marsh sediments and plants. 
Oil samples   Ts/Tm1 24Tri/23Tri2 C29/C303 29D/29H4 
BP crude oil 1.070 0.914 0.586 0.564 
Weathered oil/BJS 1.078 0.909 0.537 0.564 
Weathered oil/BJN 1.057 0.912 0.531 0.557 
Surface sediment/BJS 1.074 0.940 0.587 0.559 
Surface sediment/BJN 0.965 1.001 0.592 - 
Sediment (15 cm)/BJS 0.900 1.040 0.771 - 
Sediment (15 cm)/BD 0.962 0.960 0.691 - 
 
1Ts/Tm = 18?-22,29,30-trisnorneohopane/17?-22,29,30-trisnorhopane 
224Tri/23Tri = C24 tricyclic terpane/C23 tricyclic terpane 
3C29/C30 = 17?,21?(H)-30-norhopane/17?,21?(H)-hopane 
429D/29H = 18?(H)-30-norneohopane/17?,21?(H)-30-norhopane 
 
 
 
Carbon Isotopic Compositions 
The stable carbon-isotopic compositions of wetland sediments are determined primarily 
by the type of vegetation growing in the area. These isotopic values can be skewed when oil is 
introduced into the environment. For example, crude oil may have much different carbon 
isotopic signatures (more negative) than the vegetation, resulting in a substantial shift in 13C/12C 
ratios of bulk sediments. Carbon isotopic signatures of plants reflect the preferential use of 12C 
during photosynthesis (Park and Epstein, 1961). The 12C/13C ratios vary among various types of 
plants, because different plants have separate pathways for carbon fixation (O?Leary, 1988). 
Fossil fuels, such as petroleum formed from the bacterial oxidation of organic compounds are 
typically depleted in 13C (< -15?, PDB) relative to an inorganic carbon source such as marine 
carbonate rocks (? 0 ?).  
99 
 
Carbon isotopic analyses were performed on initial crude oil collected from the 
Macondo-1 well, sediment cores from different depths, and plants collected from each marsh 
site. Crude oils originating from the Gulf of Mexico region typically have ?13C values ranging 
from -26.6 to -33.0? (Stahl, 1977; Macko and Parker, 1983). The initial BP crude oil from the 
Macondo-1 well falls precisely within this range with an average ?13C value of -27.0?. Isotopic 
analysis of the oil scraped off of plant samples (i.e. weathered oil) at BJN site yielded a very 
similar ?13C value of -26.7 ? .  This result indicates that the isotopic signatures are conservative 
and not affected by oil degradation, an observation made previously in Spartina plants in a study 
by Benner et al. (1987). Thus, stable carbon isotopic analysis can provide a reliable way to trace 
the spilled oil in coastal marshes. Marsh plants and their residues constitute the main sources of 
organic matter in marsh sediments. As long as the marsh plants carry a ?13C signature 
distinguishable from spilled oil, contaminated sediments will exhibit large variation in ?13C 
values compared to those of plants. ?13C values of plants and sediments at all sites are listed in 
Appendix 5. Both C3-type Juncus and C4-type Spartina plants are found at BH sites. Only 
Spartina plants are found at PACB site. Three Louisiana marsh sites (RG, BD, and BB) are 
dominated by the C4 plant Spartina sp., which has ?13C values ranging from -14.4 to -17.7? 
(Chmura et al., 1987), higher than those of BP crude oil. The BJN site contains both Juncus       
(-27.1? ) and Spartina (-14.7? ), although likely Juncus comparatively minor. 
 Carbon isotopic compositions of BP oil, marsh sediments, and marsh plants were plotted 
on a histogram (Figure 57) and a box plot (Figure 58). At the Mississippi sites, BH sediments are 
more depleted in 13C (mean ?13C = -24.5?) than PACB sediments (mean ?13C = -21.7? ). This 
may be related to the type of plants at these sites, as PACB is dominated solely by Spartina with 
an average ?13C value of -14.1?. In contrast, BH contains both Spartina (?13C value of -14.2?) 
100 
 
and Juncus plants with much lower ?13C value of -25.2?. ?13C values of sediments are 
significantly lower than those of the dominant marsh plants at the PACB site, indicating some 
degree of contamination from isotopically light oil. At the Louisiana sites, RG held an average 
?13C signature of -21.5? . At the three Barataria sites, BD, BB, and BJN, average ?13C values for 
sediments are -19.6? , -18.9?,  and -18.3? , respectively, significantly lower than those of their 
C4-dominated vegetation (-14.8?0.6 ?). This reflects  the influence of isotopically light crude 
oil. As expected, contaminated sediments show strong depletion in 13C due to the incursion of 
oil. In summary, stable carbon isotopic signatures can serve as a conservative tracer to 
investigate the source of spilled oil in coastal marshes, provided that the marsh site is dominated 
by C4 plants and organic matter with distinctly different ?13C values than those of spilled oils.   
 
 
 
 
 
 
 
 
 
 
 
 
 
101 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 57. Histogram showing variations between the three types of material subjected to carbon isotopic 
analysis (plants, sediments, oil). The histogram shows an influence of oil on the sediments, as the wetland 
sediments are more depleted in 13C than the plants. 
 
 
 
 
 
 
 
 
Oil Plant 
                                                                  Sediment 
 
  
102 
 
 
 
 
 
Figure 58. Box plot showing the range of ?13C signatures within and among sites. 
 
 
 
 
 
 
 
 
 
 
103 
 
 
 
CONCLUSIONS 
 
 The 2010 Gulf oil spill had significant impacts on affected Mississippi and Louisiana 
coastal wetland sites (PACB, BD, BB, BJN). Comparison with non-contaminated or less-
affected sites (BH, RG), provides a picture of the impact the oil spill has had within the first 6 to 
9 months after the Deepwater Horizon explosion. Results indicate that the sediment and pore-
water geochemistry in these contaminated estuarine settings have been greatly affected. Total 
digestion analysis of wetland sediments shows higher concentrations of certain trace 
metals/metalloids (e.g., Ni, Cu, Pb, Zn, Co, V, Ba, Hg, As) in heavily-oiled Louisiana wetlands 
compared to less-affected and pristine sites in Mississippi. In addition, average normalized 
enrichment factor calculations indicate that metals are enriched beyond terrestrial levels, 
supporting a marine/oil source for metal contamination. Levels of certain metals/metalloids (e.g., 
arsenic) in sediments correlate well with (r = 0.47) the abundance of clay size particles, 
confirming that the fine-grained sediments in salt marshes have high capacity to adsorb metals 
derived from terrestrial or marine sources. Higher metal concentrations in oiled sediments also 
can be positively correlated to higher TOC contents, indicating that organic carbon and metal 
contaminants are likely derived from the same source. At heavily-oiled Louisiana sites (e.g., BD, 
BB, BJN), elevated levels of metals and total organic carbon (TOC) have been found in 
sediments down to depths of 30 cm. Contamination is not limited to shallow sediments; oil and 
various associated metals have invaded into deeper (pre-industrial) portions of the marsh 
sediments. 
104 
 
 Porewaters extracted from contaminated Louisiana sediments are characterized by very 
high levels of DOC (up to hundreds of mg/kg) and reduced sulfur concentrations (up to 80 
mg/kg). In general, pristine sites exhibit much lower concentrations in DOC (generally < 30 
mg/kg) and reduced sulfur contents (< 1 mg/kg). The influx of oil into the wetlands may have 
provided the initial substrate and carbon source for stimulating sulfate-reducing bacteria. 
Moreover, pore-water pH values show a general increasing trend (ranging from 6.6 to 8.0) with 
depth, possibly reflecting the combined effects of bacterial sulfate reduction and saltwater 
intrusion at depth. Despite high levels of trace metals in bulk sediments, concentrations of trace 
metals dissolved in porewaters are generally low. This result is unexpected, as inflow of oil and 
bacterial reduction of metal-sorbed sediments would typically lead to higher dissolved metal 
concentrations in contaminated water. Geochemical analyses indicate that most metals are 
sequestered in sulfides and other solids in sediments via adsorption or co-precipitation processes. 
SEM analysis identified pyrite-like sulfides with distinct framboidal form in oiled sediments.  
EDAX analysis further confirmed the presence of Fe and S as the main constituents in these 
framboids.  LA-ICP-MS analyses show that sulfide framboids contain various levels of trace 
metals. Some analyzed pyrite grain show high concentrations of Mn, Pb, Zn, and As (average 
concentrations > 1,000 mg/kg) and minor amounts of Ni, Co, V, Hg, Se, and Cd. Sulfide solids 
likely serve as local sinks for chalcophile (?sulfur-loving?) trace metals under sulfate-reducing 
conditions. Increased bacterial populations were found primarily in oiled wetlands (PACB, BD, 
BB, and BJN) and have likely greatly affected the fate and transformation of metals within these 
environments. Abundance of SRB and elevated sulfide concentrations in porewaters extracted 
from heavily oiled Louisiana sites suggest that microbial sulfate reduction may be enhanced by 
the influx of oil and organic matter.  It appears that high organic matter content and bacterially-
105 
 
mediated sulfate reduction facilitate metal retention via sulfide formation in the oiled marsh 
sediments. 
 GC-MS full-scan analysis shows significant degradation of lighter compounds while 
heavier oils persist in sediments. This result suggests that natural microbes have initially utilized 
oil as a metabolic carbon source; microbes appear to preferentially break the lighter compounds 
of the oil to gain energy. This implies that the impacted wetlands likely will become enriched in 
heavier components of the oil, which can remain in environments up to decades after an oil spill 
(Oudot and Chaillain, 2010). High sensitivity GC-MS-SIM biomarker analysis clearly correlates 
M-252 crude oil to organic compounds extracted from marsh sediments down to 15 cm. The 
extraction protocol and biomarker correlation can be potentially applied to monitor long-term 
transformation of persistent oil compounds in heavily contaminated wetlands. Carbon isotopic 
measurements show that the spilled BP oil has a unique ?13C signature that is significantly 
different from those of the C4 plants that dominate Louisiana salt marshes (Spartina sp.).  The 
Barataria sites (BD, BB, and BJN) appear to have received the most severe contamination based 
on ?13C signatures that are significantly more depleted  than those of local living plant mass or 
decomposed plant parts. Such a large carbon isotopic difference between the marsh vegetation 
and the oil provides an excellent opportunity to examine the source and movement of spilled oils 
in coastal marshes. 
Recent studies have shown that isolated giant plumes of  the spilled BP spilled oil still 
exist under the Gulf of Mexico (New York Times, 2012), and it is probable that these oil plumes 
will continue to wash into these coastal wetlands over time with the aid of storm surge and 
hurricane activities. This study shows that microbial degradation of oil and formation of 
framboidal sulfides serve to reduce the levels of oil and immobilize trace metals in coastal 
106 
 
wetlands. A chief concern is that, in Fe-limited salt-marsh environments, formation of iron 
sulfides may not keep pace with oil-related metal contamination. Moreover, re-oxidation in 
tidally-influenced marshes has the potential to oxidize and subsequently disaggregate the 
sulfides, thereby releasing sorbed metals from the sulfides and into the water column. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
107 
 
 
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Cosmochimica Acta, v. 61, p. 323-339. 
  
Wilkin, R. T., Barnes, H. L., and Brantley, S. L., 1996, The size distribution of framboidal pyrite  
in modern sediments: An indicator of redox conditions: Geochimica et Cosmochimica 
Acta, v. 60, p. 3897?3912. 
 
Wright D. A., and Welbourn, P., 2002, Environmental Toxicity, Cambridge University Press,  
    Cambridge, UK, 630 pp. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
114 
 
Appendix 1.  Dissolved organic carbon, dissolved reduced Fe and sulfide contents of porewaters. 
Sample Sediment Pore-water Pore-water Fe Pore-water sulfide 
ID depth (cm) DOC (mg/kg) (mg/kg) (mg/kg) 
     
WB 0-3 38.19 - - 
WB 3-6 30.80 - .002 
WB 6-9 70.80 - - 
WB 9-12 64.88 0.09 .100 
WB 12-15 46.77 - - 
WB 15-18 35.54 0.05 - 
WB 18-21 38.80 0.07 - 
WB 21-24 37.12 0.03 - 
WB 24-27 32.62 - - 
WB 27-30 36.80 0.13 - 
     
LB 0-3 19.88 - - 
LB 3-6 0.60 0.25 .080 
LB 6-9 0.55 - - 
LB 9-12 26.30 0.36 .690 
LB 12-15 12.90 - - 
LB 15-18 14.45 - - 
LB 18-21 1.92 - - 
LB 21-24 14.63 - - 
LB 24-27 0.16 - - 
LB 27-30 13.40 - - 
     
WI 0-3 0.21 - - 
WI 3-6 31.54 0.61 .003 
WI 6-9 54.62 - - 
WI 9-12 25.83 0.62 .787 
WI 12-15 26.91 - - 
WI 15-18 18.94 - - 
WI 18-21 - - - 
WI 21-24 - - - 
WI 24-27 - - - 
WI 27-30 - - - 
     
BH 0-3 16.19 0.03 - 
BH 3-6 19.56 0.03 - 
BH 6-9 12.06 0.01 - 
BH 9-12 18.27 0.02 - 
BH 12-15 13.08 0.01 - 
BH 15-18 24.98 0.02 - 
BH 18-21 19.65 0.01 - 
BH 21-24 20.20 0.02 - 
BH 24-27 22.86 0.01 - 
BH 27-30 - 0.03 - 
115 
 
     
PACB 0-3 37.86 0.02 - 
PACB 3-6 31.60 0.02 - 
PACB 6-9 27.62 0.01 - 
PACB 9-12 15.66 0.03 - 
PACB 12-15 26.19 0.01 - 
PACB 15-18 0.25 0.02 - 
PACB 18-21 0.53 0.01 - 
PACB 21-24 11.22 0.04 - 
PACB 24-27 10.24 0.01 - 
PACB 27-30 0.35 - - 
     
RG 0-3 35.74 - .030 
RG 3-6 48.67 0.01 - 
RG 6-9 61.06 0.02 - 
RG 9-12 56.56 0.02 - 
RG 12-15 96.19 0.02 - 
RG 15-18 112.60 - - 
RG 18-21 122.90 - - 
RG 21-24 142.90 - - 
RG 24-27 162.50 - - 
RG 27-30 173.00 0.01 8.86 
     
BD 0-3 79.03 0.02 .003 
BD 3-6 185.80 0.01 4.40 
BD 6-9 234.00 0.01 - 
BD 9-12 231.70 0.02 23.52 
BD 12-15 224.40 0.01 28.96 
BD 15-18 225.40 0.01 41.84 
BD 18-21 229.80 0.02 58.68 
BD 21-24 234.70 0.01 53.60 
BD 24-27 227.30 0.01 46.00 
BD 27-30 225.80 0.02 - 
     
BB 0-3 69.40 0.03 41.50 
BB 3-6 134.10 0.03 19.48 
BB 6-9 148.40 0.01 26.92 
BB 9-12 50.03 0.02 33.08 
BB 12-15 213.80 0.01 32.96 
BB 15-18 334.20 0.02 41.28 
BB 18-21 361.10 0.01 44.64 
BB 21-24 253.70 0.02 48.00 
BB 24-27 226.00 0.01 49.20 
BB 27-30 102.80 0.03 30.80 
     
BJN 0-3 85.07 0.02 .270 
BJN 3-6 182.40 0.01 4.82 
BJN 6-9 239.50 0.01 20.12 
116 
 
BJN 9-12 137.90 0.02 35.34 
BJN 12-15 234.40 0.01 54.24 
BJN 15-18 269.40 0.01 50.80 
BJN 18-21 108.20 0.02 69.10 
BJN 21-24 75.42 0.01 65.10 
BJN 24-27 308.00 0.01 70.40 
BJN 27-30 391.10 0.02 82.80 
     
BJS 0-3 69.63 0.03 .010 
BJS 3-6 109.30 0.03 .240 
BJS 6-9 142.20 0.01 4.62 
BJS 9-12 188.70 0.02 6.32 
BJS 12-15 231.40 0.01 9.12 
BJS 15-18 274.00 0.02 7.52 
BJS 18-21 308.40 0.01 8.32 
BJS 21-24 334.20 0.02 6.64 
BJS 24-27 279.90 0.01 4.06 
BJS 27-30 346.90 0.03 2.78 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
117 
 
Appendix 2a. Grain distribution by weight percent in 0-3 cm sediments.     
Phi Size WB LB WI BH PACB RG BD BB BJN BJS 
0-3 cm % % % % % % % % % % 
           
<-1 phi 0.00 0.00 0.20 0.00 0.00 0.00 0.00 0.00 0.00 0.00 
-1 to 0 phi 0.00 0.00 0.23 2.26 0.00 0.00 0.00 0.00 0.00 0.00 
0 to 1 phi 0.00 0.15 4.96 0.55 0.05 0.00 0.00 0.00 0.00 0.00 
1 to 2 phi 0.00 1.13 47.68 2.48 10.67 0.06 0.00 0.00 0.00 0.00 
2 to 3 phi 0.00 23.41 29.06 14.75 33.60 23.51 0.00 0.00 0.00 0.00 
3 to 4 phi 0.00 49.90 5.79 15.71 18.83 33.11 0.00 0.00 0.00 0.00 
4 to 5 phi 3.32 5.95 1.14 9.56 8.32 22.44 7.29 19.77 22.56 30.81 
5 to 6 phi 13.74 2.93 0.97 13.98 5.95 3.17 15.63 18.22 15.15 18.02 
6 to 7 phi 22.75 3.21 2.11 8.22 4.50 6.05 30.21 21.71 13.47 13.95 
7 to 8 phi 7.58 1.70 2.47 7.36 3.51 1.58 12.50 11.24 13.80 9.88 
8 to 9 phi 6.64 2.08 1.23 6.01 1.60 1.58 4.69 5.04 2.36 4.65 
9 to 10 phi 9.48 1.42 1.23 2.82 1.37 2.70 7.29 8.53 10.10 7.85 
> 10 phi 36.49 7.46 2.38 16.19 11.06 5.77 22.40 15.50 22.56 14.83 
 
 
Appendix 2b. Grain distribution by weight percent in 12-15 cm sediments.   
Phi Size WB LB WI BH PACB RG BD BB BJN BJS 
12-15 cm % % % % % % % % % % 
           
<-1 phi 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 
-1 to 0 phi 0.00 0.02 0.09 0.00 0.00 0.00 0.00 0.00 0.00 0.00 
0 to 1 phi 0.00 0.51 5.88 0.24 0.35 0.12 0.00 0.00 0.00 0.00 
1 to 2 phi 0.00 1.11 56.28 3.30 11.76 0.41 0.00 0.00 0.00 0.00 
2 to 3 phi 0.00 37.90 26.54 22.24 34.79 16.54 0.00 0.00 0.00 0.00 
3 to 4 phi 0.00 43.63 3.92 21.89 9.02 30.46 0.00 0.00 0.00 0.00 
4 to 5 phi 10.64 8.32 0.70 13.90 9.05 18.98 1.68 0.00 5.82 9.69 
5 to 6 phi 14.01 1.00 0.70 10.25 8.28 9.24 7.56 3.79 9.84 23.35 
6 to 7 phi 14.57 0.42 1.57 7.66 6.49 4.41 26.89 27.96 6.22 18.50 
7 to 8 phi 11.48 1.16 0.52 4.54 3.93 3.25 20.17 23.22 12.45 13.22 
8 to 9 phi 10.08 0.58 0.52 0.71 1.88 1.33 9.24 7.11 7.03 8.81 
9 to 10 phi 4.76 0.83 1.30 1.96 3.59 4.08 9.24 9.00 11.65 7.05 
> 10 phi 34.45 4.24 1.39 10.34 10.76 11.24 25.21 28.91 46.99 19.38 
           
 
 
 
 
118 
 
Appendix 2c. Grain distribution by weight percent in 27-30 cm sediments. 
Phi Size WB LB WI BH PACB RG BD BB BJN BJS 
27-30 cm % % % % % % % % % % 
           
<-1 phi 0.00 0.00 0.27 0.00 0.00 0.00 0.00 0.00 0.00 0.00 
-1 to 0 
phi 0.00 0.15 0.62 0.52 0.05 0.00 0.00 0.00 0.00 0.00 
0 to 1 phi 0.00 0.76 6.92 1.08 0.66 0.00 0.00 0.00 0.00 0.00 
1 to 2 phi 0.00 2.30 65.92 2.52 17.25 0.00 0.00 0.00 0.00 0.00 
2 to 3 phi 0.00 34.56 16.30 11.49 45.64 0.00 0.00 0.00 0.00 0.00 
3 to 4 phi 0.00 31.10 2.54 13.43 10.46 0.00 0.00 0.00 0.00 0.00 
4 to 5 phi 3.91 4.88 2.87 19.19 6.91 3.75 4.51 1.64 4.05 21.86 
5 to 6 phi 12.85 2.62 0.38 16.44 7.78 12.62 12.78 14.25 32.43 23.72 
6 to 7 phi 15.92 4.25 0.38 10.46 4.07 24.46 11.65 16.71 45.27 13.26 
7 to 8 phi 14.53 3.71 0.70 6.09 1.36 19.72 19.55 13.15 4.73 9.30 
8 to 9 phi 14.53 2.35 0.32 7.31 1.73 7.50 9.02 10.96 0.68 5.35 
9 to 10 
phi 7.54 2.89 0.26 3.25 0.37 16.57 9.02 9.32 2.03 6.98 
> 10 phi 30.73 10.22 2.43 8.22 3.70 15.38 33.46 33.97 10.81 19.53 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
119 
 
Appendix 3. Bulk major ion compositions of coastal wetland sediments.  
Sample Sample Fe K P Al S Ca Mg Na 
ID depth 
(cm) 
% % % % % % % % 
          
WB 0-3 3.400 0.25 0.043 2.090 1.670 0.160 0.450 0.791 
WB 3-6 3.390 0.24 0.039 2.150 1.850 0.180 0.460 0.714 
WB 6-9 3.270 0.26 0.034 2.170 1.860 0.180 0.530 1.007 
WB 9-12 2.900 0.22 0.030 1.830 1.690 0.190 0.420 0.778 
WB 12-15 2.930 0.20 0.027 1.970 1.860 0.200 0.400 0.502 
WB 15-18 3.120 0.21 0.028 2.190 1.950 0.160 0.410 0.393 
WB 18-21 2.940 0.19 0.024 1.930 1.870 0.140 0.370 0.275 
WB 21-24 2.420 0.15 0.019 1.580 1.480 0.130 0.290 0.184 
WB 24-27 2.570 0.17 0.020 1.600 1.440 0.130 0.340 0.190 
WB 27-30 2.330 0.15 0.016 1.180 1.430 0.110 0.320 0.168 
          
LB 0-3 0.250 0.04 0.003 0.310 0.290 0.600 0.100 0.428 
LB 3-6 0.220 0.04 0.001 0.320 0.250 0.050 0.090 0.348 
LB 6-9 0.240 0.03 0.002 0.300 0.300 0.050 0.070 0.247 
LB 9-12 0.280 0.04 0.001 0.340 0.320 0.040 0.070 0.271 
LB 12-15 0.430 0.04 0.001 0.370 0.510 0.040 0.080 0.283 
LB 15-18 0.310 0.02 0.001 0.210 0.420 0.030 0.050 0.196 
LB 18-21 0.460 0.04 0.001 0.370 0.590 0.040 0.080 0.212 
LB 21-24 0.420 0.03 0.001 0.310 0.540 0.030 0.080 0.220 
LB 24-27 0.430 0.03 0.001 0.250 0.550 0.030 0.060 0.187 
LB 27-30 0.620 0.03 0.001 0.300 0.690 0.050 0.070 0.187 
          
WI 0-3 0.450 0.09 0.019 0.360 0.500 0.130 0.260 0.917 
WI 3-6 0.970 0.14 0.020 0.720 0.880 0.200 0.430 1.348 
WI 6-9 1.260 0.16 0.022 1.010 1.080 0.230 0.560 1.337 
WI 9-12 1.150 0.14 0.018 0.870 0.960 0.190 0.440 1.004 
WI 12-15 1.030 0.13 0.014 0.740 0.870 0.340 0.400 1.006 
WI 15-18 0.750 0.10 0.009 0.590 0.650 0.090 0.290 0.689 
WI 18-21 0.750 0.11 0.008 0.630 0.650 0.100 0.310 0.847 
WI 21-24 0.410 0.06 0.005 0.340 0.340 0.050 0.170 0.549 
WI 24-27 0.370 0.06 0.004 0.340 0.330 0.060 0.160 0.500 
WI 27-30 0.520 0.08 0.005 0.400 0.510 0.080 0.240 0.739 
          
BH 0-3 0.700 0.12 0.004 0.550 0.640 0.180 0.190 0.745 
BH 3-6 0.740 0.13 0.003 0.640 0.680 0.110 0.200 0.602 
BH 6-9 0.890 0.14 0.002 0.640 0.870 0.110 0.200 0.496 
BH 9-12 0.990 0.10 0.001 0.490 1.140 0.100 0.160 0.451 
BH 12-15 1.120 0.06 0.001 0.330 1.320 0.060 0.110 0.320 
BH 15-18 0.650 0.05 0.001 0.280 0.840 0.050 0.090 0.287 
BH 18-21 0.310 0.05 0.001 0.220 0.430 0.050 0.080 0.266 
BH 21-24 0.210 0.04 0.001 0.200 0.280 0.040 0.070 0.244 
120 
 
BH 24-27 0.190 0.04 0.001 0.200 0.270 0.040 0.070 0.252 
BH 27-30 0.140 0.04 0.001 0.180 0.220 0.030 0.060 0.216 
          
PACB 0-3 0.260 0.05 0.014 0.160 0.150 0.060 0.080 0.383 
PACB 3-6 0.560 0.08 0.012 0.290 0.530 0.100 0.120 0.418 
PACB 6-9 1.450 0.18 0.013 0.740 1.320 0.160 0.260 0.588 
PACB 9-12 1.000 0.13 0.010 0.540 0.900 0.080 0.190 0.419 
PACB 12-15 1.340 0.16 0.012 0.660 1.130 0.100 0.220 0.459 
PACB 15-18 1.420 0.18 0.012 0.680 1.130 0.080 0.220 0.423 
PACB 18-21 1.190 0.18 0.010 0.650 0.920 0.090 0.220 0.412 
PACB 21-24 0.950 0.16 0.008 0.600 0.740 0.080 0.190 0.369 
PACB 24-27 1.050 0.16 0.008 0.620 0.850 0.080 0.190 0.398 
PACB 27-30 0.750 0.11 0.005 0.440 0.650 0.050 0.140 0.323 
          
RG 0-3 1.010 0.15 0.050 0.580 0.340 0.200 0.300 0.512 
RG 3-6 1.130 0.15 0.040 0.610 0.720 0.220 0.270 0.305 
RG 6-9 1.400 0.16 0.038 0.680 0.960 0.140 0.300 0.296 
RG 9-12 1.300 0.15 0.041 0.640 0.910 0.160 0.290 0.254 
RG 12-15 1.420 0.17 0.040 0.730 0.960 0.180 0.340 0.258 
RG 15-18 1.810 0.20 0.033 0.970 1.400 0.160 0.380 0.388 
RG 18-21 1.460 0.24 0.031 1.190 0.940 0.160 0.450 0.494 
RG 21-24 1.410 0.25 0.027 1.130 1.060 0.160 0.460 0.609 
RG 24-27 1.140 0.25 0.027 1.110 0.640 0.150 0.440 0.507 
RG 27-30 1.540 0.26 0.028 1.250 1.030 0.150 0.470 0.509 
          
BD 0-3 1.390 0.33 0.043 1.010 1.320 0.530 0.620 1.336 
BD 3-6 1.460 0.36 0.037 1.190 1.370 0.280 0.680 1.367 
BD 6-9 1.680 0.38 0.031 1.190 1.570 0.270 0.680 1.256 
BD 9-12 1.880 0.38 0.030 1.180 2.020 0.300 0.700 1.384 
BD 12-15 1.810 0.33 0.035 1.020 2.440 0.370 0.700 1.617 
BD 15-18 1.870 0.34 0.040 1.160 2.470 0.400 0.770 1.639 
BD 18-21 1.480 0.26 0.042 0.760 2.890 0.500 0.790 2.159 
BD 21-24 1.360 0.36 0.039 1.150 1.790 0.410 0.790 1.733 
BD 24-27 1.150 0.31 0.036 1.000 1.570 0.410 0.740 1.617 
BD 27-30 1.260 0.27 0.035 0.860 1.700 0.360 0.650 1.301 
          
BB 0-3 1.760 0.30 0.049 0.860 1.780 0.510 0.590 1.402 
BB 3-6 1.980 0.34 0.030 0.970 2.070 0.260 0.620 1.351 
BB 6-9 1.430 0.36 0.028 1.060 1.310 0.240 0.640 1.180 
BB 9-12 1.370 0.36 0.033 1.130 1.380 0.300 0.700 1.299 
BB 12-15 1.900 0.28 0.047 0.930 2.990 0.490 0.740 1.946 
BB 15-18 1.900 0.33 0.039 1.020 2.420 0.420 0.730 1.647 
BB 18-21 1.410 0.25 0.031 0.790 1.300 0.210 0.470 0.744 
BB 21-24 1.370 0.25 0.041 0.700 2.610 0.550 0.810 2.467 
BB 24-27 1.600 0.36 0.030 1.250 1.110 0.230 0.660 0.850 
BB 27-30 1.260 0.35 0.033 1.210 0.800 0.300 0.660 1.023 
121 
 
          
BJN 0-3 1.380 0.32 0.037 0.820 1.700 0.470 0.650 1.847 
BJN 3-6 1.600 0.31 0.034 0.750 2.120 0.670 0.680 2.063 
BJN 6-9 1.320 0.31 0.035 0.820 1.650 0.350 0.650 1.781 
BJN 9-12 0.980 0.31 0.032 0.850 1.130 0.330 0.620 1.394 
BJN 12-15 1.280 0.31 0.027 0.770 1.560 0.330 0.590 1.460 
BJN 15-18 1.480 0.29 0.033 0.770 2.120 0.400 0.650 1.828 
BJN 18-21 1.180 0.26 0.029 0.750 1.550 0.320 0.550 1.418 
BJN 21-24 1.150 0.23 0.041 0.700 2.040 0.450 0.640 1.990 
BJN 24-27 0.880 0.17 0.022 0.460 0.800 0.130 0.280 0.433 
BJN 27-30 1.150 0.27 0.037 0.860 1.410 0.300 0.550 1.190 
          
BJS 0-3 1.390 0.29 0.047 0.810 1.580 0.450 0.600 1.356 
BJS 3-6 1.380 0.30 0.035 0.900 1.290 0.220 0.550 0.953 
BJS 6-9 1.770 0.28 0.037 0.820 2.080 0.300 0.590 1.223 
BJS 9-12 1.590 0.29 0.039 0.780 2.210 0.370 0.700 1.791 
BJS 12-15 1.270 0.30 0.036 0.860 1.610 0.310 0.640 1.460 
BJS 15-18 1.220 0.33 0.032 0.950 1.300 0.280 0.630 1.395 
BJS 18-21 1.230 0.29 0.029 0.750 1.380 0.280 0.570 1.263 
BJS 21-24 0.710 0.24 0.024 0.620 0.700 0.230 0.440 0.871 
BJS 24-27 0.580 0.22 0.019 0.550 0.780 0.240 0.450 1.025 
BJS 27-30 0.550 0.20 0.018 0.490 0.510 0.150 0.330 0.572 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
122 
 
Appendix 4a.  Trace metal compositions (in mg/kg) of coastal wetland sediments. 
Sample Sample Cu Pb Zn Ni Co Mn 
ID depth 
(cm) 
mg/kg mg/kg mg/kg mg/kg mg/kg mg/kg 
        
WB 0-3 20.40 21.50 76.00 13.60 8.60 381.00 
WB 3-6 21.00 20.80 78.00 13.30 8.40 384.00 
WB 6-9 15.10 20.20 73.00 13.10 8.30 350.00 
WB 9-12 13.30 16.90 63.00 11.20 7.00 308.00 
WB 12-15 13.70 18.80 65.00 11.40 6.80 314.00 
WB 15-18 14.80 21.20 68.00 12.70 7.40 296.00 
WB 18-21 24.90 19.30 59.00 11.90 6.40 230.00 
WB 21-24 10.80 15.90 46.00 8.80 5.20 167.00 
WB 24-27 10.60 15.80 45.00 9.90 6.10 174.00 
WB 27-30 8.70 13.90 39.00 8.20 5.80 149.00 
        
LB 0-3 3.10 4.40 3.00 1.40 0.50 12.00 
LB 3-6 2.30 4.90 3.00 1.30 0.60 7.00 
LB 6-9 1.30 4.40 2.00 1.60 0.60 5.00 
LB 9-12 2.90 4.50 2.00 1.20 0.70 5.00 
LB 12-15 3.50 5.20 2.00 1.70 1.10 6.00 
LB 15-18 3.20 3.50 2.00 0.90 0.60 4.00 
LB 18-21 2.70 4.50 3.00 1.10 0.80 8.00 
LB 21-24 2.30 3.90 3.00 1.40 0.70 8.00 
LB 24-27 2.50 3.20 3.00 1.40 0.70 7.00 
LB 27-30 3.60 3.90 4.00 1.70 1.20 8.00 
        
WI 0-3 17.30 5.20 24.00 3.70 0.80 23.00 
WI 3-6 21.20 10.00 33.00 7.90 1.90 53.00 
WI 6-9 24.10 14.20 45.00 9.00 2.40 71.00 
WI 9-12 21.00 12.60 50.00 7.90 2.20 61.00 
WI 12-15 24.20 11.70 43.00 6.80 2.10 57.00 
WI 15-18 14.80 8.30 23.00 4.20 1.40 39.00 
WI 18-21 11.30 7.50 25.00 5.00 1.50 34.00 
WI 21-24 15.50 4.00 14.00 3.20 0.80 17.00 
WI 24-27 42.60 3.80 13.00 2.90 0.90 15.00 
WI 27-30 13.00 4.40 10.00 4.20 1.60 17.00 
        
BH 0-3 8.50 7.10 9.00 2.60 1.00 23.00 
BH 3-6 3.00 8.10 7.00 3.00 1.00 18.00 
BH 6-9 4.60 10.40 6.00 2.70 1.50 17.00 
BH 9-12 6.90 9.70 5.00 2.60 1.40 15.00 
BH 12-15 2.70 7.60 2.00 1.90 1.80 13.00 
BH 15-18 2.20 5.60 1.00 0.80 0.50 10.00 
BH 18-21 1.20 4.90 1.00 0.70 0.30 7.00 
BH 21-24 2.10 4.40 1.00 0.60 0.30 6.00 
123 
 
BH 24-27 1.30 4.60 1.00 0.70 0.20 6.00 
BH 27-30 4.50 4.30 1.00 0.40 0.10 5.00 
        
PACB 0-3 3.40 3.20 6.00 1.00 0.80 52.00 
PACB 3-6 4.60 4.20 11.00 2.10 1.30 71.00 
PACB 6-9 7.00 8.50 22.00 5.10 3.30 240.00 
PACB 9-12 5.60 6.40 17.00 4.10 2.40 156.00 
PACB 12-15 10.80 8.10 19.00 4.80 2.80 205.00 
PACB 15-18 4.30 8.20 18.00 4.40 3.00 224.00 
PACB 18-21 5.70 7.60 13.00 4.60 2.70 141.00 
PACB 21-24 2.90 6.50 12.00 4.00 2.10 78.00 
PACB 24-27 3.40 7.10 11.00 4.10 2.30 61.00 
PACB 27-30 2.70 5.60 7.00 3.00 2.30 32.00 
        
RG 0-3 66.00 13.30 45.00 8.80 4.60 410.00 
RG 3-6 22.80 10.90 39.00 9.50 5.50 176.00 
RG 6-9 17.70 11.20 41.00 10.20 5.70 169.00 
RG 9-12 28.40 10.40 43.00 9.90 5.40 164.00 
RG 12-15 23.80 13.10 45.00 10.60 5.80 200.00 
RG 15-18 19.80 17.70 48.00 12.10 5.80 236.00 
RG 18-21 24.00 17.80 44.00 11.50 4.20 200.00 
RG 21-24 45.10 17.10 46.00 10.60 4.30 205.00 
RG 24-27 29.90 14.80 41.00 10.40 4.40 178.00 
RG 27-30 25.30 17.30 51.00 14.50 7.30 180.00 
        
BD 0-3 22.90 11.50 44.00 12.60 5.40 211.00 
BD 3-6 28.20 11.40 61.00 14.80 5.20 206.00 
BD 6-9 20.50 10.20 62.00 15.30 5.70 219.00 
BD 9-12 21.20 11.10 41.00 12.30 5.40 258.00 
BD 12-15 34.10 15.70 44.00 17.20 7.90 262.00 
BD 15-18 30.70 14.00 61.00 19.40 6.80 264.00 
BD 18-21 35.00 13.00 48.00 18.70 8.30 298.00 
BD 21-24 36.30 12.50 73.00 17.80 7.30 247.00 
BD 24-27 37.40 11.50 46.00 13.70 4.00 228.00 
BD 27-30 25.40 10.70 53.00 13.50 5.70 217.00 
        
BB 0-3 126.20 32.00 67.00 16.70 8.30 283.00 
BB 3-6 40.80 11.00 62.00 16.50 7.80 229.00 
BB 6-9 32.20 11.00 47.00 12.40 5.50 192.00 
BB 9-12 25.70 14.50 47.00 14.20 5.30 198.00 
BB 12-15 50.20 21.60 74.00 26.40 11.70 259.00 
BB 15-18 36.40 14.70 60.00 20.10 8.00 252.00 
BB 18-21 16.00 10.50 41.00 12.40 4.50 163.00 
BB 21-24 42.50 12.70 51.00 17.30 6.40 251.00 
BB 24-27 22.60 16.10 61.00 16.00 6.10 192.00 
BB 27-30 35.10 17.00 50.00 14.60 4.60 198.00 
124 
 
        
BJN 0-3 24.70 13.20 52.00 15.40 4.40 173.00 
BJN 3-6 28.10 12.60 50.00 14.90 6.10 195.00 
BJN 6-9 25.00 11.80 40.00 13.30 4.40 170.00 
BJN 9-12 27.10 11.00 42.00 11.70 5.30 160.00 
BJN 12-15 20.60 10.30 39.00 10.60 6.40 191.00 
BJN 15-18 26.70 12.80 35.00 11.30 5.20 220.00 
BJN 18-21 23.90 10.20 30.00 11.50 3.80 127.00 
BJN 21-24 25.70 13.80 27.00 12.60 3.90 151.00 
BJN 24-27 9.00 5.60 19.00 6.60 3.00 72.00 
BJN 27-30 18.00 9.80 31.00 12.50 3.70 119.00 
        
BJS 0-3 31.80 12.80 43.00 13.40 5.60 219.00 
BJS 3-6 45.60 12.40 48.00 14.40 5.60 241.00 
BJS 6-9 26.00 12.40 46.00 14.60 6.20 271.00 
BJS 9-12 27.30 12.60 42.00 14.00 5.30 279.00 
BJS 12-15 38.00 11.80 44.00 13.60 4.90 204.00 
BJS 15-18 22.70 10.80 37.00 11.20 3.50 181.00 
BJS 18-21 21.90 9.90 32.00 10.30 3.20 172.00 
BJS 21-24 20.00 7.20 24.00 8.00 1.90 123.00 
BJS 24-27 15.80 8.00 21.00 6.80 1.80 111.00 
BJS 27-30 12.50 6.20 18.00 6.30 2.20 79.00 
  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
125 
 
Appendix 4b.  Trace metal compositions (in mg/kg) of coastal wetland sediments. 
Sample Sample As Th Sr V Ba Cr Hg 
ID depth 
(cm) 
mg/kg mg/kg mg/kg mg/kg mg/kg mg/kg mg/kg 
         
WB 0-3 10.70 7.10 33.00 35.00 32.00 32.00 0.08 
WB 3-6 10.50 7.20 32.00 35.00 32.00 31.00 0.08 
WB 6-9 10.30 7.30 39.00 35.00 31.00 30.00 0.08 
WB 9-12 9.60 6.30 33.00 29.00 25.00 26.00 0.07 
WB 12-15 9.80 6.70 32.00 34.00 26.00 27.00 0.06 
WB 15-18 10.90 7.20 29.00 38.00 28.00 29.00 0.07 
WB 18-21 10.50 6.80 27.00 35.00 25.00 27.00 0.06 
WB 21-24 8.30 5.70 21.00 29.00 20.00 21.00 0.05 
WB 24-27 9.00 6.10 24.00 30.00 23.00 25.00 0.05 
WB 27-30 9.30 5.40 22.00 25.00 19.00 19.00 0.04 
         
LB 0-3 1.70 1.70 37.00 10.00 4.00 4.00 0.00 
LB 3-6 1.50 1.90 8.00 11.00 3.00 4.00 0.00 
LB 6-9 1.90 2.10 7.00 11.00 3.00 4.00 0.01 
LB 9-12 2.10 2.10 7.00 10.00 5.00 3.00 0.00 
LB 12-15 3.20 2.30 8.00 12.00 3.00 5.00 0.00 
LB 15-18 1.90 1.50 5.00 8.00 2.00 3.00 0.00 
LB 18-21 1.80 2.20 8.00 11.00 4.00 7.00 0.01 
LB 21-24 1.30 1.80 7.00 8.00 4.00 6.00 0.00 
LB 24-27 1.30 1.60 6.00 8.00 3.00 5.00 0.00 
LB 27-30 1.80 1.80 8.00 10.00 4.00 6.00 0.02 
         
WI 0-3 2.20 1.20 19.00 6.00 7.00 11.00 0.05 
WI 3-6 4.80 2.20 28.00 19.00 9.00 22.00 0.05 
WI 6-9 5.20 2.70 32.00 26.00 13.00 28.00 0.06 
WI 9-12 4.50 2.40 26.00 22.00 10.00 12.00 0.07 
WI 12-15 4.10 2.00 26.00 18.00 8.00 20.00 0.06 
WI 15-18 2.80 1.90 15.00 13.00 7.00 15.00 0.04 
WI 18-21 3.50 1.90 17.00 14.00 7.00 15.00 0.04 
WI 21-24 2.40 1.00 10.00 9.00 5.00 9.00 0.04 
WI 24-27 2.10 1.20 10.00 8.00 5.00 10.00 0.03 
WI 27-30 3.70 1.70 14.00 13.00 5.00 12.00 0.01 
         
BH 0-3 2.40 2.70 21.00 13.00 9.00 7.00 0.00 
BH 3-6 1.90 3.20 18.00 14.00 8.00 7.00 0.00 
BH 6-9 2.00 3.10 19.00 13.00 7.00 7.00 0.01 
BH 9-12 2.70 2.70 17.00 10.00 6.00 5.00 0.01 
BH 12-15 2.20 1.80 12.00 6.00 4.00 3.00 0.01 
BH 15-18 0.70 1.70 10.00 4.00 3.00 2.00 0.00 
BH 18-21 0.50 1.50 9.00 3.00 3.00 2.00 0.01 
BH 21-24 0.50 1.40 7.00 3.00 3.00 2.00 0.00 
126 
 
BH 24-27 0.50 1.40 8.00 3.00 6.00 2.00 0.00 
BH 27-30 0.50 1.40 7.00 2.00 4.00 2.00 0.00 
         
PACB 0-3 1.70 0.90 7.00 9.00 4.00 2.00 0.00 
PACB 3-6 3.10 1.50 10.00 12.00 5.00 5.00 0.00 
PACB 6-9 6.50 3.40 19.00 20.00 9.00 12.00 0.02 
PACB 9-12 4.20 2.60 13.00 14.00 7.00 1.00 0.00 
PACB 12-15 6.10 3.20 15.00 18.00 9.00 11.00 0.00 
PACB 15-18 6.30 3.40 15.00 18.00 9.00 11.00 0.00 
PACB 18-21 6.10 3.50 15.00 17.00 9.00 10.00 0.00 
PACB 21-24 4.90 3.20 13.00 16.00 8.00 9.00 0.02 
PACB 24-27 5.30 3.40 14.00 17.00 8.00 9.00 0.00 
PACB 27-30 3.80 2.40 10.00 12.00 6.00 6.00 0.01 
         
RG 0-3 4.30 3.80 26.00 14.00 123.00 11.00 0.02 
RG 3-6 4.60 4.00 26.00 15.00 71.00 11.00 0.03 
RG 6-9 5.60 4.50 20.00 16.00 52.00 11.00 0.03 
RG 9-12 6.60 4.20 21.00 15.00 105.00 11.00 0.03 
RG 12-15 6.50 4.70 24.00 18.00 134.00 12.00 0.05 
RG 15-18 8.00 5.20 33.00 23.00 82.00 15.00 0.06 
RG 18-21 5.30 5.90 37.00 27.00 72.00 17.00 0.06 
RG 21-24 6.90 5.50 41.00 29.00 65.00 17.00 0.06 
RG 24-27 4.70 5.80 40.00 26.00 60.00 17.00 0.06 
RG 27-30 7.70 6.40 36.00 29.00 52.00 18.00 0.07 
         
BD 0-3 3.00 3.80 65.00 23.00 97.00 16.00 0.02 
BD 3-6 2.60 4.20 58.00 22.00 58.00 17.00 0.02 
BD 6-9 3.30 5.00 55.00 23.00 62.00 18.00 0.03 
BD 9-12 5.20 5.00 59.00 25.00 63.00 18.00 0.04 
BD 12-15 10.40 3.90 69.00 24.00 61.00 16.00 0.05 
BD 15-18 5.00 3.80 71.00 22.00 66.00 16.00 0.04 
BD 18-21 6.00 2.20 81.00 21.00 54.00 12.00 0.05 
BD 21-24 3.60 3.70 71.00 26.00 71.00 17.00 0.04 
BD 24-27 2.70 3.20 73.00 24.00 72.00 15.00 0.02 
BD 27-30 2.70 3.30 63.00 21.00 60.00 14.00 0.03 
         
BB 0-3 5.40 3.70 64.00 21.00 78.00 14.00 0.05 
BB 3-6 4.80 4.50 56.00 21.00 57.00 16.00 0.04 
BB 6-9 3.10 4.50 57.00 23.00 63.00 17.00 0.04 
BB 9-12 3.20 4.20 60.00 25.00 65.00 18.00 0.04 
BB 12-15 7.10 2.10 85.00 22.00 58.00 14.00 0.05 
BB 15-18 4.50 3.40 73.00 23.00 72.00 16.00 0.05 
BB 18-21 2.70 3.70 42.00 16.00 62.00 12.00 0.02 
BB 21-24 4.80 2.30 94.00 24.00 65.00 13.00 0.06 
BB 24-27 2.80 6.00 49.00 24.00 77.00 19.00 0.04 
BB 27-30 2.20 5.30 59.00 27.00 86.00 19.00 0.04 
127 
 
         
BJN 0-3 4.60 3.60 63.00 21.00 67.00 13.00 0.05 
BJN 3-6 4.60 3.40 86.00 20.00 71.00 12.00 0.07 
BJN 6-9 3.00 3.30 64.00 20.00 65.00 13.00 0.05 
BJN 9-12 2.50 3.40 59.00 21.00 64.00 14.00 0.05 
BJN 12-15 3.50 3.90 59.00 23.00 59.00 13.00 0.06 
BJN 15-18 4.20 3.70 69.00 24.00 56.00 7.00 0.07 
BJN 18-21 2.70 3.50 59.00 20.00 55.00 12.00 0.04 
BJN 21-24 3.30 2.60 78.00 21.00 59.00 12.00 0.03 
BJN 24-27 1.60 2.60 28.00 12.00 41.00 7.00 0.02 
BJN 27-30 2.30 3.30 55.00 20.00 66.00 13.00 0.02 
         
BJS 0-3 6.70 3.50 60.00 21.00 69.00 14.00 0.05 
BJS 3-6 6.70 4.30 42.00 20.00 50.00 14.00 0.05 
BJS 6-9 9.40 3.60 52.00 20.00 52.00 13.00 0.06 
BJS 9-12 9.00 3.10 64.00 20.00 54.00 5.00 0.06 
BJS 12-15 4.60 3.60 58.00 21.00 56.00 14.00 0.05 
BJS 15-18 3.10 4.10 55.00 22.00 62.00 15.00 0.02 
BJS 18-21 3.20 4.10 49.00 20.00 56.00 13.00 0.04 
BJS 21-24 1.70 3.70 41.00 16.00 51.00 10.00 0.03 
BJS 24-27 1.70 3.50 45.00 18.00 49.00 10.00 0.03 
BJS 27-30 1.40 3.30 30.00 14.00 41.00 9.00 0.02 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
128 
 
Appendix 5.  Sediment total organic carbon contents (TOC) and carbon isotopic compositions of bulk 
sediments, marsh plants, oil sample scrapped off the oiled plants, and BP MC-252 oil.  
Sample Sample TOC ???C ???C ???C ???C 
ID depth(cm) sed(%) sed(PDB) Juncus(PDB) Spartina(PDB) oil(PDB) 
       
WB plant - - -27.6   
WB 0-3 2.230 -25.9    
WB 3-6 2.290 -25.5    
WB 6-9 1.830 -25.3    
WB 9-12 2.240 -25.4    
WB 12-15 2.190 -25.4    
WB 15-18 1.970 -25.3    
WB 18-21 1.770 -25.3    
WB 21-24 2.330 -25.2    
WB 24-27 1.770 -25.4    
WB 27-30 1.770 -25.4    
       
LB plant - - -24.1   
LB 0-3 1.980 -26.1    
LB 3-6 2.220 -26.3    
LB 6-9 2.060 -26.0    
LB 9-12 1.930 -25.9    
LB 12-15 1.850 -26.1    
LB 15-18 1.720 -25.8    
LB 18-21 1.100 -26.3    
LB 21-24 1.320 -26.0    
LB 24-27 1.390 -26.1    
LB 27-30 2.000 -26.1    
       
WI plant - -  -15.0  
WI 0-3 2.720 -23.6    
WI 3-6 2.990 -22.6    
WI 6-9 3.030 -21.7    
WI 9-12 2.660 -21.9    
WI 12-15 1.910 -21.4    
WI 15-18 2.220 -21.6    
WI 18-21 1.390 -21.9    
WI 21-24 1.470 -22.7    
WI 24-27 1.760 -22.0    
WI 27-30 2.500 -23.4    
       
BH plant - - -25.2 -14.5  
BH 0-3 1.730 -24.0    
BH 3-6 2.040 -23.9    
BH 6-9 1.940 -23.5    
BH 9-12 2.120 -23.1    
BH 12-15 2.180 -23.9    
129 
 
BH 15-18 1.710 -24.6    
BH 18-21 1.460 -25.0    
BH 21-24 1.490 -25.2    
BH 24-27 1.460 -25.8    
BH 27-30 1.420 -26.3    
       
PACB plant - -  -14.1  
PACB 0-3 0.323 -21.1    
PACB 3-6 0.697 -20.1    
PACB 6-9 0.598 -19.4    
PACB 9-12 0.811 -19.6    
PACB 12-15 0.909 -19.7    
PACB 15-18 0.985 -20.8    
PACB 18-21 0.835 -23.3    
PACB 21-24 1.120 -23.7    
PACB 24-27 0.831 -24.2    
PACB 27-30 0.818 -24.8    
       
RG plant - -  -14.4  
RG 0-3 1.010 -22.7    
RG 3-6 1.110 -23.1    
RG 6-9 1.200 -24.0    
RG 9-12 1.050 -23.6    
RG 12-15 1.940 -23.5    
RG 15-18 2.190 -20.2    
RG 18-21 1.690 -19.9    
RG 21-24 1.400 -18.5    
RG 24-27 1.580 -19.9    
RG 27-30 1.680 -19.9    
       
BD plant - -  -15.1  
BD 0-3 4.530 -19.4    
BD 3-6 21.500 -20.3    
BD 6-9 28.900 -21.1    
BD 9-12 19.800 -20.6    
BD 12-15 24.400 -19.7    
BD 15-18 19.200 -20.5    
BD 18-21 19.000 -19.6    
BD 21-24 18.600 -19.2    
BD 24-27 20.280 -18.6    
BD 27-30 22.350 -17.3    
       
BB plant - -  -15.6  
BB 0-3 6.790 -18.9    
BB 3-6 11.100 -20.3    
BB 6-9 10.700 -20.5    
BB 9-12 11.700 -19.8    
BB 12-15 13.600 -19.7    
130 
 
BB 15-18 9.370 -18.2    
BB 18-21 4.270 -18.9    
BB 21-24 8.840 -17.4    
BB 24-27 9.160 -17.9    
BB 27-30 9.350 -17.8    
       
BJN plant - - -27.1 -14.7 -26.7 
BJN 0-3 7.810 -18.2    
BJN 3-6 5.090 -18.0    
BJN 6-9 10.100 -18.1    
BJN 9-12 7.720 -18.7    
BJN 12-15 6.820 -18.2    
BJN 15-18 6.780 -18.3    
BJN 18-21 4.120 -18.4    
BJN 21-24 4.370 -18.8    
BJN 24-27 4.010 -17.6    
BJN 27-30 14.090 -18.3    
       
BJS plant - - -24.2 -14.3 -26.7 
BJS 0-3 6.270 -22.2    
BJS 3-6 9.720 -22.6    
BJS 6-9 5.330 -22.1    
BJS 9-12 16.200 -21.2    
BJS 12-15 14.700 -20.7    
BJS 15-18 10.300 -20.0    
BJS 18-21 9.720 -19.3    
BJS 21-24 7.010 -19.7    
BJS 24-27 6.820 -18.7    
BJS 27-30 4.500 -18.9    
       
MC 252  Crude     27.1 
       
 
 
 
 
 
 
 
 
 
131 
 
Appendix 6a. Summary of number of positive tubes in the SRB MPN cultures inoculated with sediment 
core samples from heavily contamination sites. 
Sample Depth 10  fold 100 fold 1000 fold MPN 
 (cm)     
      
Bay Jimmy South (BJ) 1 0 - 3 5 2 0 150 
Bay Jimmy South (BJ) 2 0 - 3 5 2 0 150 
Bay Jimmy South (BJ) 1 12 - 15 5 3 1 79 
Bay Jimmy South (BJ) 2 12 - 15 5 3 0 110 
Bay Jimmy South (BJ) 1 27 - 30 5 2 0 150 
Bay Jimmy South (BJ) 2 27 - 30 5 0 1 31 
Bay Jimmy North (BN) 1 0 - 3 5 2 0 150 
Bay Jimmy North (BN) 2 0 - 3 5 5 2 540 
Bay Jimmy North (BN) 1 12 - 15 5 5 1 350 
Bay Jimmy North (BN) 2 12 - 15 5 4 3 280 
Bay Jimmy North (BN) 1 27 - 30 5 3 0 79 
Bay Jimmy North (BN) 2 27 - 30 5 4 0 130 
Bayou Batiste Core C (BB) 1 0 - 3 5 4 5 1600 
Bayou Batiste Core C (BB) 2 0 - 3 5 5 5 1600 
Bayou Batiste Core C (BB) 1 12 - 15 5 5 3 920 
Bayou Batiste Core C (BB) 2 12 - 15 5 5 3 920 
Bayou Batiste Core C (BB) 1 27 - 30 5 1 5 220 
Bayou Batiste Core C (BB) 2 27 - 30 5 5 0 240 
Bayou Dulac Core C (BD) 1 0 - 3 5 5 3 920 
Bayou Dulac Core C (BD) 2 0 - 3 5 5 3 920 
Bayou Dulac Core C (BD) 1 12 - 15 5 5 0 240 
Bayou Dulac Core C (BD) 2 12 - 15 5 4 0 130 
Bayou Dulac Core C (BD) 1 27 - 30 5 1 0 33 
Bayou Dulac Core C (BD) 2 27 - 30 5 1 0 33 
      
 
 
 
 
 
 
 
132 
 
Appendix 6b. Summary of number of positive tubes in the SRB MPN cultures inoculated with sediment 
core samples from intermediate contaminated sites. 
Sample Depth   10 fold 100 fold 1000 fold MPN 
 (cm)     
      
Rigolets (RG) 1 0 - 3 5 5 4 1600 
Rigolets (RG) 2 0 - 3 5 5 5 1600 
Rigolets (RG) 1 12 - 15 5 5 5 1600 
Rigolets (RG) 2 12 - 15 5 5 5 1600 
Rigolets (RG) 1 27 - 30 5 5 5 1600 
Rigolets (RG) 2 27 - 30 5 5 5 1600 
Point Aux Chenes Bay (PA) 1 0 - 3 5 5 1 350 
Point Aux Chenes Bay (PA) 2 0 - 3 5 5 1 350 
Point Aux Chenes Bay (PA) 1 12 - 15 3 2 0 14 
Point Aux Chenes Bay (PA) 2 12 - 15 5 5 1 350 
Point Aux Chenes Bay (PA) 1 27 - 30 5 2 1 70 
Point Aux Chenes Bay (PA) 2 27 - 30 3 2 0 14 
Walker Island (W) 1 0 - 3 5 5 1 350 
Walker Island (W) 2 0 - 3 5 5 1 350 
Walker Island (W) 1 9-12 5 1 0 33 
Walker Island (W) 2 9-12 5 0 0 23 
Walker Island (W) 1 15-18 5 1 0 33 
Walker Island (W) 2 15-18 5 2 1 70 
 
 
 
 
 
 
 
 
 
 
 
 
133 
 
Appendix 6c. Summary of number of positive tubes in the SRB MPN cultures inoculated with sediment 
core samples from pristine sites. 
Sample Depth  10  fold 100 fold 1000 fold MPN 
 (cm)     
      
Long?s Bayou (LB) 1 0 - 3 5 5 3 920 
Long?s Bayou (LB) 2 0 - 3 5 5 2 540 
Long?s Bayou (LB) 1 12 - 15 5 1 0 33 
Long?s Bayou (LB) 2 12 - 15 5 0 0 23 
Long?s Bayou (LB) 1 27 - 30 0 1 1 1.8 
Long?s Bayou (LB) 2 27 - 30 1 1 0 1.9 
Weeks Bay Force F Core (WF) 1 0 - 3 5 5 1 350 
Weeks Bay Force F Core (WF) 2 0 - 3 5 5 2 540 
Weeks Bay Force F Core (WF) 1 12 - 15 5 4 1 170 
Weeks Bay Force F Core (WF) 2 12 - 15 5 5 2 540 
Weeks Bay Force F Core (WF) 1 27 - 30 5 5 2 540 
Weeks Bay Force F Core (WF) 2 27 - 30 5 5 3 920 
Weeks Bay Force E Core (WE) 1 0 - 3 5 5 3 920 
Weeks Bay Force E Core (WE) 2 0 - 3 5 5 1 350 
Weeks Bay Force E Core (WE) 1 15-18 5 4 0 130 
Weeks Bay Force E Core (WE) 2 15-18 5 4 0 130 
Weeks Bay Force E Core (WE) 1 27 - 30 5 5 4 1600 
Weeks Bay Force E Core (WE) 2 27 - 30 5 5 1 350 
Bayou Heron (BH) 1 0 - 3 5 5 2 540 
Bayou Heron (BH) 2 0 - 3 5 5 3 920 
Bayou Heron (BH) 1 12 - 15 5 2 0 49 
Bayou Heron (BH) 2 12 - 15 5 0 0 23 
Bayou Heron (BH) 1 27 - 30 3 1 0 11 
Bayou Heron (BH) 2 27 - 30 2 0 0 4.5 
      
 
 
 
 
 
 
 
 
134 
 
 Appendix 7a. Summary of number of positive tubes in the IRB MPN cultures inoculated with sediment 
core samples from heavily contamination sites. 
Sample Depth  10 fold 100 fold 1000 fold MPN 
      
      
Bay Jimmy South (BJ) 1 0 - 3 5 5 5 >1600 
Bay Jimmy South (BJ) 2 0 - 3 5 5 5 >1600 
Bay Jimmy South (BJ) 1 12 - 15 5 5 5 >1600 
Bay Jimmy South (BJ) 2 12 - 15 5 5 5 >1600 
Bay Jimmy South (BJ) 1 27 - 30 5 5 5 >1600 
Bay Jimmy South (BJ) 2 27 - 30 5 5 5 >1600 
Bay Jimmy North (BN) 1 0 - 3 5 5 5 >1600 
Bay Jimmy North (BN) 2 0 - 3 5 5 5 >1600 
Bay Jimmy North (BN) 1 12 - 15 5 5 5 >1600 
Bay Jimmy North (BN) 2 12 - 15 5 5 5 >1600 
Bay Jimmy North (BN) 1 27 - 30 5 5 5 >1600 
Bay Jimmy North (BN) 2 27 - 30 5 5 5 >1600 
Bayou Batiste Core C (BB) 1 0 - 3 5 5 5 >1600 
Bayou Batiste Core C (BB) 2 0 - 3 5 5 5 >1600 
Bayou Batiste Core C (BB) 1 12 - 15 5 5 5 >1600 
Bayou Batiste Core C (BB) 2 12 - 15 5 5 5 >1600 
Bayou Batiste Core C (BB) 1 27 - 30 5 5 5 >1600 
Bayou Batiste Core C (BB) 2 27 - 30 5 5 5 >1600 
Bayou Dulac Core C (BD) 1 0 - 3 5 5 5 >1600 
Bayou Dulac Core C (BD) 2 0 - 3 5 5 5 >1600 
Bayou Dulac Core C (BD) 1 12 - 15 5 5 5 >1600 
Bayou Dulac Core C (BD) 2 12 - 15 5 5 5 >1600 
Bayou Dulac Core C (BD) 1 27 - 30 5 5 5 >1600 
Bayou Dulac Core C (BD) 2 27 - 30 5 5 5 >1600 
      
 
 
 
 
  
 
 
135 
 
Appendix 7b. Summary of number of positive tubes in the IRB MPN cultures inoculated with sediment 
core samples from pristine sites. 
Sample Depth 10 fold 100 fold 1000 fold MPN 
 (cm)     
      
Long?s Bayou (LB) 1 0 - 3 5 5 5 >1600 
Long?s Bayou (LB) 2 0 - 3 5 5 5 >1600 
Long?s Bayou (LB) 1 12 - 15 5 5 5 >1600 
Long?s Bayou (LB) 2 12 - 15 5 5 5 >1600 
Long?s Bayou (LB) 1 27 - 30 5 5 5 >1600 
Long?s Bayou (LB) 2 27 - 30 5 5 5 >1600 
Weeks Bay Force F Core (WF) 1 0 - 3 5 5 5 >1600 
Weeks Bay Force F Core (WF) 2 0 - 3 5 5 5 >1600 
Weeks Bay Force F Core (WF) 1 12 - 15 5 5 5 >1600 
Weeks Bay Force F Core (WF) 2 12 - 15 5 5 5 >1600 
Weeks Bay Force F Core (WF) 1 27 - 30 5 5 5 >1600 
Weeks Bay Force F Core (WF) 2 27 - 30 5 5 5 >1600 
Weeks Bay Force E Core (WE) 1 0 - 3 5 5 5 >1600 
Weeks Bay Force E Core (WE) 2 0 - 3 5 5 5 >1600 
Weeks Bay Force E Core (WE) 1 15-18 5 5 5 >1600 
Weeks Bay Force E Core (WE) 2 15-18 5 5 5 >1600 
Weeks Bay Force E Core (WE) 1 27 - 30 5 5 5 >1600 
Weeks Bay Force E Core (WE) 2 27 - 30 5 5 5 >1600 
Bayou Heron (BH) 1 0 - 3 5 5 5 >1600 
Bayou Heron (BH) 2 0 - 3 5 5 5 >1600 
Bayou Heron (BH) 1 12 - 15 5 5 5 >1600 
Bayou Heron (BH) 2 12 - 15 5 5 5 >1600 
Bayou Heron (BH) 1 27 - 30 5 5 5 >1600 
Bayou Heron (BH) 2 27 - 30 5 5 5 >1600