Varying Relative Degradation Rates of Oil in Different Forms and

College of Marine Science, University of South Florida, Saint Petersburg, Florida 33701, United ... Environmental Science & Technology 2015 49 (2), 84...
0 downloads 0 Views 1MB Size
Subscriber access provided by Penn State | University Libraries

Article

Varying relative degradation rates of oil in different forms and environments revealed by ramped pyrolysis Matthew A Pendergraft, and Brad Erik Rosenheim Environ. Sci. Technol., Just Accepted Manuscript • DOI: 10.1021/es501354c • Publication Date (Web): 08 Aug 2014 Downloaded from http://pubs.acs.org on August 12, 2014

Just Accepted “Just Accepted” manuscripts have been peer-reviewed and accepted for publication. They are posted online prior to technical editing, formatting for publication and author proofing. The American Chemical Society provides “Just Accepted” as a free service to the research community to expedite the dissemination of scientific material as soon as possible after acceptance. “Just Accepted” manuscripts appear in full in PDF format accompanied by an HTML abstract. “Just Accepted” manuscripts have been fully peer reviewed, but should not be considered the official version of record. They are accessible to all readers and citable by the Digital Object Identifier (DOI®). “Just Accepted” is an optional service offered to authors. Therefore, the “Just Accepted” Web site may not include all articles that will be published in the journal. After a manuscript is technically edited and formatted, it will be removed from the “Just Accepted” Web site and published as an ASAP article. Note that technical editing may introduce minor changes to the manuscript text and/or graphics which could affect content, and all legal disclaimers and ethical guidelines that apply to the journal pertain. ACS cannot be held responsible for errors or consequences arising from the use of information contained in these “Just Accepted” manuscripts.

Environmental Science & Technology is published by the American Chemical Society. 1155 Sixteenth Street N.W., Washington, DC 20036 Published by American Chemical Society. Copyright © American Chemical Society. However, no copyright claim is made to original U.S. Government works, or works produced by employees of any Commonwealth realm Crown government in the course of their duties.

Page 1 of 38

Environmental Science & Technology

1

Varying relative degradation rates of oil in different forms and

2

environments revealed by ramped pyrolysis

3 4

Matthew A Pendergraft†

5

and

6

Brad E Rosenheim†‡*

7 8 9

† Department of Earth and Environmental Sciences, Tulane University, New Orleans, Louisiana, 70118

10 11

‡ Presently at College of Marine Science, University of South Florida, St. Petersburg, Florida, 33701

12

* corresponding author

13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 1 ACS Paragon Plus Environment

Environmental Science & Technology

28

Abstract

29

Degradation of oil contamination yields stabilized products by removing and

30

transforming reactive and volatile compounds. In contaminated coastal environments,

31

the processes of degradation are influenced by shoreline energy, which increases the

32

surface area of the oil as well as exchange between oil, water, microbes, oxygen, and

33

nutrients. Here, a ramped pyrolysis carbon isotope technique is employed to investigate

34

thermochemical and isotopic changes in organic material from coastal environments

35

contaminated with oil from the 2010 BP Deepwater Horizon oil spill. Oiled beach

36

sediment, tar ball, and marsh samples were collected from a barrier island and a brackish

37

marsh in southeast Louisiana over a period of 881 days. Stable carbon (13C) and

38

radiocarbon (14C) isotopic data demonstrate a predominance of oil-derived carbon in the

39

organic material. Ramped pyrolysis profiles indicate that the organic material was

40

transformed into more stable forms. Our data indicate relative rates of stabilization in the

41

following order, from fastest to slowest: high energy beach sediments > low energy beach

42

sediments > marsh > tar balls. Oil was transformed most rapidly where shoreline energy

43

and the rates of oil dispersion and exchange with water, microbes, oxygen, and nutrients

44

were greatest.

45

46

47

48

2 ACS Paragon Plus Environment

Page 2 of 38

Page 3 of 38

Environmental Science & Technology

49

50

1. Introduction When oil contaminates an environment, multiple processes physically disperse the

51

oil and chemically transform it in a process referred to as weathering. The processes that

52

chemically change the oil, as well as their effects, can be collectively referred to as oil

53

degradation, and include evaporation, biodegradation, dissolution/water washing,

54

photooxidation/photodegradation, emulsification, and adsorption/sedimentation.1-12

55

These degradative processes remove and/or convert reactive and volatile compounds and

56

leave behind stabilized residues that can persist in the environment.4,5,11-13

57

Oil degradation rates are determined by various factors,4,5,9,14,15 with shoreline

58

energy being one of the most important for coastal oil spills.1,9 Microbes can consume

59

upwards of 50% of spilled oil4 and biodegradation rates are largely influenced by

60

coastline energy.1,5,9 Greater shoreline energy (wind, waves, and tides) increases

61

biodegradation rates by accelerating oil dispersion, which increases oil surface area

62

available to microbes16-18 and the supply of oxygen and nutrients (N and P), via

63

water,necessary for microbes to consume oil.19-21 High shoreline energy has been shown

64

to correspond to high rates of weathering,1,9 and longer oil persistence has been observed

65

on protected coastlines.22 Perhaps the longest-studied oil spill, the 1969 Florida spill in

66

West Falmouth, Massachusetts, resulted in oil persisting in a protected salt marsh with

67

low shoreline energy for three decades.23-25 White et al.25 concluded that physical

68

processes ultimately decide the fate of residual oil components at West Falmouth.

69 70

The large extent of the 2010 BP Deepwater Horizon oil spill (DwH) provides an opportunity to study degradation and transformation of oil deposited synchronously in

3 ACS Paragon Plus Environment

Environmental Science & Technology

71

different coastal environments. DwH is the largest accidental oil spill to date, having

72

released roughly ten times the volume of oil as the 1989 Exxon Valdez oil spill in the

73

Gulf of Alaska.26 Approximately 1,600 km of Gulf of Mexico shoreline and 75 linear km

74

of Louisiana coastal marsh received moderate to heavy oiling from DwH.27,28 Coastal

75

Louisiana is comprised of multiple environments including barrier islands directly

76

exposed to the energy of the Gulf of Mexico and semi-protected marshes that receive a

77

diminished, yet substantial, portion of that energy. The wetlands of this region constitute

78

about 37% of the coastal wetlands of the 48 conterminous United States,29,30 support

79

roughly 30% of the total United States fishing industry, and protect a network of

80

infrastructure responsible for an equal proportion of the country’s oil and gas supply.30

81

At the same time, the Mississippi River Delta suffers from significant subsidence-driven

82

land loss estimated at 4877 km2 during 1932 to 2010,29 and expected to reach 10,000+

83

km2 by the year 2100.31 Oil contamination can negatively impact marshes30,32 and

84

accelerated marsh shoreline erosion due to DwH has been documented.33 Assessment of

85

the degradation of oil in this ecosystem through time is important to discern where and

86

how oil degradation products may contribute to further stress on the coastal wetlands.

87

Here we employ ramped pyrolysis (RP) carbon isotope analysis34 to oil-impacted

88

organic material from a barrier island and a brackish marsh in order to test the hypothesis

89

that oil will be removed from coastal systems of Louisiana before post-depositional oil

90

transformation occurs. The RP isotope technique analyzes all acid insoluble organic

91

material (OM) in a sample and produces both a pyrolysis profile related to

92

thermochemical stability and an isotopic spectrum (14C and 13C) resulting from the

93

different thermochemical stabilities of admixed OC.34-38 4 ACS Paragon Plus Environment

The RP isotope technique has

Page 4 of 38

Page 5 of 38

Environmental Science & Technology

94

been previously shown to be effective at detecting and quantifying oil contamination in

95

sedimentary organic material (SOM)39 as it employs radiocarbon analyses, a sensitive

96

tracer of oil-derived organic carbon (OC). Effectively, oil and residual compounds from

97

its degradation lie on the completely radiocarbon-depleted endmember of the radiocarbon

98

scale (∆14C = -1000‰) and recent sediment and soil OC lies on the other end (near or

99

slightly above 0‰), with analytical precision on radiocarbon measurements generally

100

around 5-10‰. The use of 14C for oil spill studies 25,40-45 is not as prevalent as the use of

101

13 46-56

102

measurements compared to stable isotope analyses. Ultimately, this approach applied to

103

these environments can provide a basis for ongoing remediation efforts and efforts to

104

assess the toxicity of oil contamination and its degradation derivatives.

C

, mainly because of the relatively high cost and the novelty of these

105

106

2. Methods

107

2.1 Sample locations

108

Grand Isle and Bay Jimmy in southeast Louisiana were sampled over the course

109

of 881 days following the Macondo well blow-out that initiated DwH (Figure 1). Grand

110

Isle is a subtropical barrier island at the mouth of Barataria Bay with a gently sloping

111

sandy beach affected by moderate wave energy which increases episodically during

112

tropical cyclones (summer) and cold fronts (winter). Sediments and tar balls at two

113

locations at Grand Isle were repeatedly sampled: a relatively high energy site exposed to

114

direct wave energy from the Gulf of Mexico and a relatively low energy site located on

115

the lagoonal side of Grand Isle, protected from direct wave action from the Gulf of 5 ACS Paragon Plus Environment

Environmental Science & Technology

116

Mexico. The third sampling location was at Bay Jimmy, which lies within the brackish

117

marsh region of northeastern Barataria Bay.57 Although an erosive marsh with ~10’s of

118

km of southerly fetch, the Bay Jimmy site is considered a lower energy environment

119

compared to the two barrier island sites, which have even greater southerly fetch. During

120

the course of our sampling, we observed more geomorphic change at the Grand Isle sites

121

than at the Bay Jimmy site.

122

2.2 Sample collection and treatment

123

Sediment and tar balls were collected from Grand Isle and oiled marsh plants and

124

sediment were collected from Bay Jimmy. At Grand Isle, sediment was initially sampled

125

from the beach surface then, after geomorphic changes mixed the oil deposits into the

126

beach sediments, by digging trenches (~1 m depth) near the shoreline and sampling dark

127

subsurface layers and oily sheen with a petrochemical odor at the trench bottoms (see

128

abstract figure for an annotated photograph of a representative trench). Tar balls on the

129

beach between the two fixed sites and an oil/tar coating on a rocky groin near the higher

130

energy site were also collected from Grand Isle. We use the general term of “tar balls”

131

for a non-uniform set of samples with varying proportions of oil/tar and sediments.

132

Marsh samples from Bay Jimmy include clusters of oil and vegetation and the top (0-1

133

cm) of a 50 cm surface core collected with a hand auger.

134

Most samples were collected in glassware capped with aluminum foil (both

135

precombusted at 525°C for ≥ 2 h) and a plastic lid, and stored at -4°C under nitrogen gas.

136

Some samples from Bay Jimmy were collected in sealed plastic bags

137

(Whirlpack®/Ziploc®) when precombusted glassware was exhausted, but the samples

6 ACS Paragon Plus Environment

Page 6 of 38

Page 7 of 38

Environmental Science & Technology

138

were transferred to pre-combusted glass once in the laboratory (~3 h after sampling). The

139

crude oil, provided by BP (reference material ID: SOB-20100617-032; source sample ID:

140

ENT-052210-OL-041/043), was sampled directly from the Macondo wellhead and stored

141

at -4°C.

142

Samples from Grand Isle were ground with a mortar and pestle, acidified with

143

10% hydrochloric acid (HCl) to remove inorganic carbon, then repeatedly rinsed with

144

deionized water, centrifuged, decanted until a pH of ~6 was reached, and then dried at

145

60°C for 24 h or until completely dry. Acidification of samples was necessary to analyze

146

the organic material without inclusion of thermal decomposition of carbonate-carbon. It

147

has been demonstrated that rinsing of sediment and soil containing organic material after

148

acid treatment can mobilize some of the organic matter58, however the resulting

149

ambiguity of pyrolyzing samples containing carbonate minerals was considered a higher

150

cost to our experimental approach. Thus, samples from Bay Jimmy were also acid

151

treated after inspection for and removal of shell fragments, to ensure that all samples

152

were treated equally for this experiment.

153

154

155

2.2 Elemental and stable isotope analyses Samples were measured for organic carbon content (%OC) and bulk stable carbon

156

isotopic composition (δ13C), then subjected to ramped pyrolysis carbon isotope analysis.

157

Organic carbon content and stable carbon signatures were measured on 127 beach

158

sediment, tar ball, and marsh samples (Figure S1, Supplemental Information) at the

159

Stable Isotope Laboratory at Tulane University using an Elementar vario MICRO cube 7 ACS Paragon Plus Environment

Environmental Science & Technology

160

elemental analyzer interfaced to an Isoprime dual inlet isotope ratio mass spectrometer

161

(EA-IRMS) continuously monitoring isotope ratios of CO2 peaks in the carrier gas of He.

162

Values of %OC were used to calculate sample size and expected yields for RP analysis in

163

order to evaluate for complete carbon recovery. Stable carbon isotopic signatures are

164

expressed in δ notation and ‰ units, relative to the Pee Dee Belemnite (PDB) standard.59

165

2.3 Ramped pyrolysis 14C analysis

166

Sixty of the 127 samples were screened for reaction profiles using RP. Based on

167

this screening, 15 representative samples were re-analyzed by RP with CO2 collection

168

and isotopic analysis of the CO2. The same RP procedure was used as in previous

169

studies;34-39 this procedure consists of a smooth temperature ramp of 5°C min-1, 0% O2 in

170

the reaction chamber, and ~8% O2 in the combustion chamber. More details of the

171

analysis can be found in Rosenheim et al.34 Individual pyrolysis peaks, representing

172

thermochemically distinct components, were cryogenically collected at inflection points

173

in continuous aliquots.

174

Radiocarbon and stable carbon isotope analyses of the ramped pyrolysis CO2

175

aliquots were measured at the National Ocean Sciences Accelerator Mass Spectrometer

176

facility (NOSAMS) at Woods Hole Oceanographic Institution. Radiocarbon data,

177

reported in ∆ notation and per mil (‰) units, were calculated using: 1 ∆  ≅   =  − 1 × 1000

178

where is the fraction of the 14C/12C ratio of the measured sample compared to that of a

179

“modern” standard (1950 wood).60 We assume ∆14C to be equivalent to δ14C because

8 ACS Paragon Plus Environment

Page 8 of 38

Page 9 of 38

Environmental Science & Technology

180

less than three years passed between sample collection and measurement. 60 Ramped

181

pyrolysis AMS radiocarbon data are corrected for an analytical blank (9.3 ± 9.3 µg

182

modern blank and 0.5 ± 0.5 µg 14C-free blank for an entire run; these masses are divided

183

by the number of isotopic measurements made during each run) determined by repeated

184

measurements on isotope standards. Nine RP aliquots were depleted enough in 14C that

185

they resulted in less 14C than our determination of blank contamination in the method.

186

These values are treated as they were in Pendergraft et al.39; we use a maximum ∆14C

187

limit equivalent to 2σ uncertainty of the blank to report fraction modern values and to

188

calculate ∆14C values.

189

190

191

3. Results Depleted radiocarbon values (-891 ±232‰; Figure 2 and Table S2) dominate the

192

aliquots of CO2 collected during RP, with the exception of the marsh surface sample

193

collected at 678 d, which had no visible oil. Stable carbon isotopic signatures (-27.5 ±

194

2.2‰; Figure 2 and Table S2) are also generally depleted relative to Gulf of Mexico

195

marine SOC (‐21.4±1.9‰)38. We calculate a geometric mean isotopic value (equivalent

196

to a bulk isotopic value) using: 







2  =    ; ℎ   = 1

197

where δgm represents the geometric mean isotopic value,  represents the fraction, in

198

each aliquot, of total CO2 generated from the sample, and  represents the associated 9 ACS Paragon Plus Environment

Environmental Science & Technology

199

isotopic ratios. ∆14Cgm (-877(±268)‰, range: -996 to 0‰) and δ13Cgm (-27.6(±2.3)‰,

200

range: -28.8 to -20.5‰) characterize each whole sample subjected to RP (Table S2).

201

Assuming sample composition to be a binary mixture of oil and background organic

202

carbon (OCb), a Bayesian multi-source isotope mixing model was employed to the

203

radiocarbon data to estimate component fractions.61 The mixing model has the same

204

conventional formula as Equation 3, but δgm is replaced by δ (the measured isotopic

205

composition from a sample comprised of a mixture of endmembers). The model is able

206

to incorporate known variability in endmembers and analytical error associated with the

207

isotopic measurements. We use the most negative, blank-corrected ∆14C value measured

208

for oil using RP AMS and the associated analytical uncertainty (-998.2±1.8‰) for the oil

209

endmember, and the mean ∆14C value and associated analytical uncertainty (86.9±4.0‰)

210

from RP AMS analysis of two unoiled marsh samples collected pre-DwH for the OCb

211

endmember. Calculated fraction oil (foil) values from radiocarbon data and the mixing

212

model quantify oil in the CO2 aliquots (Table S2) and show high fractions of OC

213

comprised of oil (0.899(±0.216)). Applying to the mixing model geometric mean

214

isotopic data calculated using Equation 2 yields geometric mean fraction oil (foil-gm)

215

values that quantify oil for entire beach sediment, tar ball, and marsh samples

216

(0.88(±0.22)) analyzed by RP AMS. The evolution of CO2 over the pyrolysis ramp estimates decomposition reaction

217

 !"#$"$%&

218

rates 

219

temperature is linear with time.34,36 RP data of CO2 concentration versus temperature are

220

normalized to allow for comparison between samples with different amounts of carbon.

221

As a result, the areas under reaction profiles are equal and can be interpreted considering

$

' for the mixture of compounds comprising the OC because

10 ACS Paragon Plus Environment

Page 10 of 38

Page 11 of 38

Environmental Science & Technology

222

the percent of total OC that pyrolyzes within continuous temperature ranges. Pyrolysis at

223

higher temperatures results from greater thermochemical stability. Here, we consider

224

temperatures of < 300°C, 300-500°C, and > 500°C as low, mid, and high, respectively.

225

Time series of RP data present varying thermochemical trends amongst the

226

different sample types and environments (Figure 3). At 88 d, Grand Isle sediment from

227

both high and low energy sites experience a majority of pyrolysis (63% and 68% of total

228

pyrolysis, respectively) at low temperatures (< 300°C), but at 678 d these samples

229

pyrolyze almost entirely (82 and 89%, respectively) at mid to high temperatures (>

230

300°C; Figure 3 A and B). RP data for marsh samples from Bay Jimmy (Figure 3C) are

231

characterized by significant (50%) low-temperature pyrolysis persisting through 535 d

232

and minimal (16%) low-temperature pyrolysis at 694 d. Tar balls from Grand Isle

233

(Figure 3D) continue to yield a majority of pyrolysis (59%) below 300°C through 881 d,

234

with the exception of a tar ball from 678 d that presents an anomalous reaction profile.

235

236

4. Discussion

237

4.1 A dominant oil signature in ∆14C and δ13C data through 881 days

238

Radiocarbon and stable carbon isotopic data for CO2 aliquots produced during

239

RP demonstrate a dominance of oil-derived carbon in the sediments and soils for >678 d

240

after the Macondo well explosion (Figure 2, Table S1). A large portion (88%) of CO2

241

aliquots were measured with radiocarbon values below -800‰ (minimum of -998‰) and

242

correspondingly high calculated fraction oil values (maximum of 0.998; Table S2). For

243

the tar balls, a maximum ∆14C value of -977‰, corresponding to a minimum foil value of 11 ACS Paragon Plus Environment

Environmental Science & Technology

244

0.966 (Table S2), confirms compositions dominated by oil-derived C for 881 d, including

245

the sample with an anomalous reaction profile (Figure 3D).Stable carbon isotopic data

246

also support the prominence of oil in the OC of most CO2 aliquots. We use δ13C to

247

indicate oil in pyrolysates but not for quantification purposes because δ13C is not as

248

sensitive a tracer of oil as is ∆14C and because ∆14C inputs can be constrained by a binary

249

mixing model. The expected sources of carbon at the study sites and their associated

250

δ13C values are: oil (-27.3‰), marine organic material (-20‰), and brackish marsh

251

organic material (-16.9 to -12.5‰).39,42,57,59,62 Stable carbon isotopic data for the samples

252

analyzed by RP indicate OC dominated by petrogenic carbon in all the samples, yielding

253

a mean δ13Cgm value (27.6 ± 2.3)‰) comparable to that of the Macondo oil (27.3‰). RP

254

CO2 aliquot δ13C data below the lowest expected endmember indicate that stable carbon

255

isotopes are not uniform in the different compounds of the oil mixture and they are

256

fractionated chemically and/or isotopically during RP, as previously observed.35,38,39

257

Inclusion of C3 terrigenous carbon (δ13C = -34 to -23‰)63 is also possible and could

258

account for δ13C values below that of oil. In the case of fractionation, this would not

259

affect radiocarbon data as they are corrected for stable isotope values. No matter the

260

reason, our results indicate that the process responsible for transformation of oil in these

261

environments has not fractionated the oil-derived carbon isotopically.

262

263

264 265

4.2 Evidence for chemical transformation of oil and derivatives Considering that isotopic data demonstrate the OC is dominated by oil for nearly all samples (Figure 2, Table S2), the observed changes in thermochemical stability 12 ACS Paragon Plus Environment

Page 12 of 38

Page 13 of 38

Environmental Science & Technology

266

(Figure 3) can be interpreted as evidence of oil stabilization through degradation.

267

Therefore, we reject the null hypothesis that oil was removed from these depositional

268

settings before undergoing transformation. The pyrolysis profiles is most apparent in the

269

disappearance of low temperature pyrolysis over time, shifting the decomposition of the

270

oil and derivatives to higher overall temperatures. This indicates more thermochemical

271

stability in the OC through time.

272

groups of compounds occurs fastest in higher energy beach sediments. Ramped pyrolysis

273

data for sediments from the Grand Isle high and low energy sites (Figure 3 A and B,

274

respectively) display similar decreases in low temperature pyrolysis and increases in high

275

temperature pyrolysis. Isotopic data for each reaction profile shows oil to be the major

276

source of OC at all temperatures for both sites (Figures 4 and S3-S5). Evidence of faster

277

oil degradation at the high energy site than at the low energy site exists at 337 d, with

278

relatively more low temperature pyrolysis (42% of total pyrolysis) persisting at the low

279

energy site than at the high energy site (15%; Figure 3 A and B). Additionally, a lower

280

∆14Cgm value (by 103‰) and a correspondingly higher foil-gm value (by 0.095) for the low

281

energy site at 337 d (Table S2) indicate a higher proportion of oil remaining there than at

282

the high energy site due to a slower rate of oil degradation and/or dispersal. Similar RP

283

profiles at 678 d (Figure 3 A and B) indicate the oil at both sites had reached similar

284

states of degradation by that point.

285

In this study, oil transformation to more stable

Marsh RP data (Figures 3C and 4) indicate slower oil transformation than in

286

beach sediment. More low temperature pyrolysis in the marsh at 535 d (50%) than in the

287

low energy beach sediments at 337 d (42%) indicates greater preservation of less stable

288

oil moieties in the marsh . A second peak shifted to higher temperatures between 337 d 13 ACS Paragon Plus Environment

Environmental Science & Technology

289

and 535 d (Figure 3C) is likely due to a relative increase in OCb (Figure 4 and Table S2).

290

Pyrolysis at 694 d occurs fully in the temperature range of the control sample (Figures 3C

291

and 4) and isotopic data confirm the lack of oil visible that day at Bay Jimmy (Figure 4

292

and Table S2). This sample indicates the importance of using both the reaction shape and

293

the isotopic composition to discern transformation versus complete degradation or

294

erosion of the oil contamination.

295

Transformation does not seem to occur within tar ball microenvironments, where

296

only a crust of oil interacts with the surroundings and most oil mass is untouched (Figure

297

3D). Tar balls yielding a majority of pyrolysis (59%) at low temperatures through 881 d

298

indicate preservation of the oil comprising the tar balls. A tar ball at 678 d (foil-gm =

299

0.998) that resembled asphalt or black rubber upon collection presented a unique RP

300

profile (Figure 3D) that we interpret as oil that has undergone different degradative

301

pathway than the other tar balls. Aeppli et al.11 determined that samples with a similar

302

appearance collected at Grand Isle and the Chandeleur Islands, LA did not fit the two

303

dimensional gas chromatography flame ionization detection (GCxGC-FID) fingerprint of

304

Macondo oil.

305

The relative oil transformation rates observed in our sample sets are in agreement

306

with degradation rates in previous studies. Oil degradation was fastest at the high energy

307

beach site because mechanical energy was greatest there and resulted in fastest dispersion

308

and surface area maximization of oil in the water and sediments and greatest exchange

309

between oil, pore- and overlying waters, microbes, oxygen, and nutrients.1,9,64,65 Oil

310

degradation was slower in the marsh than in the beach sediments due to less mechanical

311

energy at the marsh. In addition, marshes contain high amounts of other organic material 14 ACS Paragon Plus Environment

Page 14 of 38

Page 15 of 38

Environmental Science & Technology

312

that can be preferentially consumed by microbial communities, thus limiting nutrients

313

necessary for microbial consumption of oil17,18. Anoxia in marsh sediments can also slow

314

oil degradation but is not considered to be a significant factor in this study because the

315

marsh samples were collected from the surface. Tar balls degraded the slowest because

316

they protect the majority of their mass from exchange with water, oxygen, and nutrients

317

by a small surface area-to-mass ratio.17,66 Our findings are in agreement with other

318

studies that have documented the persistence of tar balls67,68. Despite their heavily

319

weathered appearance, tar balls shelter significant (~30%) concentrations of saturates,

320

compounds that formed a relatively large portion (62-74%) of the Macondo crude oil.69

321

Whereas Elango et al.68 presents slow degradation of oil components in tar balls, our RP

322

data present an even more extreme scenario: minimal degradation of labile oil

323

compounds between 46 d and 881 d after initiation of DwH. This evidence of such slow

324

oil degradation in tar balls helps explain their persistence for years to decades in coastal

325

environments after an oil spill.67

326 327

4.3 Insight into oil transformation

328

The stabilization of the oil-derived compounds observed in RP data likely result from

329

both the loss of labile compounds and the conversion of labile compounds into more

330

stable compounds (Figure 3, except 3D). Oil degradation has largely been considered in

331

terms of the loss of certain compounds and has been evaluated through the use of ratios

332

of GC-amenable compounds. The degradation product is more stable than the original oil

333

because the more volatile and reactive compounds are preferentially lost and/or

334

converted, leaving behind recalcitrant compounds (generally in the form of a growing

15 ACS Paragon Plus Environment

Environmental Science & Technology

335

unresolved complex mixture (UCM) in GC terminology). In the RP data from beach and

336

marsh OC, we observe this in the loss of low temperature pyrolysis over time and the

337

persistence of pyrolysis at mid and high temperatures (Figure 3). However, a question to

338

be asked is whether the remaining compounds were present in the original oil or if some

339

of them were generated during degradation. Recent efforts on DwH oil have provided

340

new insight into the transformation of oil compounds. Two-dimensional gas

341

chromatography (GCxGC) has helped show that degraded oil can be largely comprised of

342

saturated hydrocarbons, present in the crude oil, as well as oxygenated hydrocarbons,

343

such as carboxylic acids, that appear to be the result of biodegradation (carboxylic acids

344

have been identified in biodegraded source oils for decades,70-73 yet they had been largely

345

ignored in oil contamination until recently11,69,74). The identification of stable compounds

346

formed from crude oil components is significant because it demonstrates that degradation

347

doesn’t only imply the loss of compounds through evaporation or mineralization into

348

CO2. In light of this information, we propose that the decrease in prominence of low

349

temperature pyrolysis and increase in prominence of high temperature pyrolysis

350

presented here (Figure 3) is likely the result of both the loss of less thermochemically

351

stable compounds and their conversion into more thermochemically stable compounds.

352

Compounds that pyrolyze at mid and high temperatures are likely a combination of

353

saturated hydrocarbons, oxygenated hydrocarbon residues, and other compounds yet to

354

be identified in degraded oil.11,69,74,75

355 356

4.4 Constraint of specific degradation processes using ramped pyrolysis data

16 ACS Paragon Plus Environment

Page 16 of 38

Page 17 of 38

Environmental Science & Technology

357

Oil evaporated in the laboratory and tar from a rocky groin provide insight into

358

the RP signatures of evaporation and biodegradation, the degradation processes that most

359

affect oil in the environment.1,3,4,7,9,10 The residue that remained after evaporating

360

Macondo crude oil at 60°C for 310 hs shows a similar RP profile as the crude oil, but

361

shifted to only slightly higher temperatures (~75°C, Figure 5A). Thus, evaporation can

362

account for the slight shift to higher temperatures of the prominent, low temperature peak

363

in the reaction profiles of the 88 d beach sediments (Figure 3 A and B). However, the

364

evaporation of crude oil in the laboratory did not result in the nearly complete loss of

365

low-temperature pyrolysis that occurred in beach sediment and marsh samples after 88 d.

366

The RP profiles of two tar deposits collected from a rocky groin at Grand Isle (Figure 4B)

367

exhibit a loss of low temperature pyrolysis similar to that observed in the sedimentary OC

368

from Grand Isle and Bay Jimmy. One sample was taken from the top of the rocky groin

369

where it was exposed to direct solar radiation and remained dry most of the time. These

370

are conditions we deem less hospitable to microbes. The other sample was collected

371

from within the rocky groin where it was out of direct sunlight and often wet from wave

372

and tidal action; conditions more hospitable to microbes. The sample from the more

373

hospitable environment displays a loss of low temperature pyrolysis relative to the

374

sample from the inhospitable environment (Figure 5B). Isotopic data for both samples

375

confirm their compositions to be largely oil (foil-gm = 0.986 and 0.910). We interpret these

376

two pairs of samples as evidence that the disappearance of low temperature pyrolysis

377

observed in sedimentary beach and marsh OC over the course of 600+ d is largely due to

378

biodegradation.

379

17 ACS Paragon Plus Environment

Environmental Science & Technology

380

381

4.5 Other processes affecting isotopic trends Isotopic data show evidence of stable isotope fractionation at the most depleted

382

∆14C values and mixing with other OC sources at less depleted ∆14C values. At 88d,

383

radiocarbon data pooled from the two barrier island sites (Figure 6A) show that oil is the

384

only carbon source (∆14C ≈ -1000‰), and there is no mixing occurring between sources

385

of carbon. The variation in δ13C is interpreted as RP causing isotopic fractionation or

386

chemical separation of oil components that are both isotopically (δ13C) and

387

thermochemically distinct. Stable carbon isotope fractionation has been observed before

388

in RP,35,38,39 however it is important to note that radiocarbon values, which are used to

389

calculate foil, are corrected for stable carbon isotope composition,34,60 thus fractionation

390

does not affect 14C quantification. As the oil mixes with OCb in the environment and

391

∆14C values become less negative (Figure 6A), a mixing relationship, with variation in

392

both δ13C and ∆14C. dominates the fractionation signal. Increasing steepness of linearly

393

regressed data in δ13C-∆14C space at different sampling dates (Figure 6A) indicates

394

admixture of OCb over time. Data from tar samples show a similar trend but at a slower

395

rate, indicating a slower rate of incorporation of OCb into tar balls (Figure S6B). It is

396

important to note that the amounts of OCb are small, but RP isotopic analysis is sensitive

397

enough to reveal the isotopic effect. A mixing line that better encompasses this system’s

398

endmembers can be generated by linearly regressing all the marsh data together (Figure

399

6B) because earlier samples are comprised almost exclusively of oil and the marsh

400

sample from 694 d is nearly devoid of oil. Plotting δ13C versus 1/foil in a Keeling-like

401

plot76 (Figure 6B), as in Pendergraft et al.,39 accurately estimates the δ13C value of

402

Macondo oil (-27.1‰ where 1/foil = 1) to within twice the measurement error (1σ = 18 ACS Paragon Plus Environment

Page 18 of 38

Page 19 of 38

Environmental Science & Technology

403

0.1‰) of the measured value (-27.3‰).39,42 Data at lower 1/foil values (higher foil) exhibit

404

fractionation in their δ13C variation, whereas variation in both 1/foil and δ13C at higher

405

1/foil values (lower foil) demonstrates admixture of OCb.

406

4.6 Significance of results

407

Our RP isotope analysis of oil-impacted beach and marsh SOM presents

408

transformation of oil by a complex set of processes analyzing all of the OM in the

409

system, including compounds not initially present in the petroleum contamination. For

410

all three locations, higher shoreline energy implies faster dispersion of oil and greater

411

exchange with water, microbes, oxygen, and nutrients.1,5,9,16-21 Higher energy

412

environments can also imply faster and more admixture with other ambient sources of

413

organic material after the oil contamination event. Overall, isotopic data reveal that oil

414

dominated the organic carbon in coastal Louisiana after the 2010 Deepwater Horizon oil

415

spill and persisted, especially in tarballs, for 678-881+ d. Ramped pyrolysis reaction

416

profiles show oil transformation in beach sediments and on the marsh surface and oil

417

preservation in tar balls. These findings are in agreement with previous studies that

418

found oil in tar balls, aggregates, and thick emulsions can persist in the environment

419

much longer than oil from the same source but in dispersed forms.17,18 Relative oil

420

degradation rates, from fastest to slowest, for the four sample types is as follows: higher

421

energy beach sediment > lower energy beach sediment > marsh surface > tar balls.

422

Transformation of the oil seems to have been microbially mediated, with mixing

423

processes also recognized in isotope time series, particularly in the marsh, an

424

environment rich in OCb. The persistence of oil in this region is important due to the

425

vulnerability of the area where a large proportion of this oil was deposited. The presence 19 ACS Paragon Plus Environment

Environmental Science & Technology

426

of transformed oil compounds may prolong the effects of the oil deposition, especially in

427

a sensitive and important ecosystem.

428

429

Figures

Abstract Figure. Representative trench dug at Grand Isle with inlaid ramped pyrolysis trend. Sampling focused on dark sediment layers and infiltrated groundwater with oil sheen and petrochemical odor at bottom of the trench. Image: B.E. Rosenheim. (amended by M.A. Pendergraft) 430 431

20 ACS Paragon Plus Environment

Page 20 of 38

Page 21 of 38

Environmental Science & Technology

432 433

Figure 1. Sampling locations in Bay Jimmy (A.) and at Grand Isle (B.) in southeast Louisiana. Samples collected where indicating lines meet the adjacent land.

21 ACS Paragon Plus Environment

Environmental Science & Technology

Page 22 of 38

Figure 2. Radiocarbon (∆14C) and stable carbon (δ13C) data for the CO2 aliquots produced and collected during RP display a dominance of oil in the OC for this sample set, with the exception of the aliquots from the marsh sample from 678 d. Dashed lines are at the isotopic signatures of the Macondo oil. Symbols indicate sample type: diamond – beach SOM; triangle – marsh SOM; circle – tar ball. Colors represent sampling date and are scaled to the color bar. 434 435 436 437 438 439 440 441 442 443 444 445 446

22 ACS Paragon Plus Environment

Page 23 of 38

Environmental Science & Technology

Figure 3. RP reaction profile trends over time for four samples types. Individual plots display evolution of CO2 over a smooth temperature ramp to 800°C, and plots are colored based on time from the well blow-out. Profiles for Macondo crude oil (black) and a control sample from unoiled marsh (white) given for reference.A. Grand Isle beach sediments from the high energy site. B. Grand Isle beach sediments from the low energy site. C. Marsh samples from Bay Jimmy within Barataria Bay. D. tar samples from grand Isle. 447 448

23 ACS Paragon Plus Environment

Environmental Science & Technology

Page 24 of 38

Figure 4. RP isotopic data for marsh samples. A. Trend in profiles over time. Profiles for Macondo crude oil (black) and a control sample from unoiled marsh (white) given for reference. B.-D. Profiles with isotopic data for samples at 337, 535, and 694 d. Left axis in top panel is CO2 evolution. Right axis is ∆14C. Horizontal bars indicate temperature intervals over which the aliquots of CO2 were collected. Bottom panel plots δ13C (points in white) for the same intervals. Tmax is temperature at which maximum pyrolysis occurs. Geometric mean isotopic values are shown by dashed lines in green (∆14C) and blue (δ13C). Errors on the isotopic measurements are smaller than the symbols used to plot the values. 449 450 451 452 453 454 455 456 457 458

24 ACS Paragon Plus Environment

Page 25 of 38

Environmental Science & Technology

Figure 5. A. Oil evaporated at ~60°C shows a loss of compounds below that temperature yet continues to present a dominant low temperature peak. B. Tar sampled from a rocky groin presents a loss of oil compounds that pyrolyze at low temperatures, similar to the oil in beach sediment and marsh samples. 459 460 461 462

463

464

465

466

25 ACS Paragon Plus Environment

Environmental Science & Technology

Figure 6. A. Carbon isotopic compositions of aliquots of sediment samples produced by RP AMS. Dark blue – 88 d; light blue – 337 d; orange – 678 d. The dotted lines are at the isotopic values for Macondo crude oil. Variation in d13C with minimal variation in ∆14C is interpreted as evidence of fractionation. Slopes of linear regressions for each date are interpreted to be proportional to degree of mixing (addition of OCb to the oil). B. Plotting δ13C vs. 1/foil for all CO2 aliquots from marsh samples produces a Keeling-like plot that yields a d13C estimate for oil of -27.1‰ at 1/foil = 1. 467 468

469

Supplemental Information

26 ACS Paragon Plus Environment

Page 26 of 38

Page 27 of 38

Environmental Science & Technology

%OC (black circles, left axis) and δ13C (red diamonds, right axis) over time for 127 beach sediment (A.), tar balls (B.), and marsh samples (C.). Right axis marked at δ13C values for Macondo oil (-27.3‰, black), marine OC (-20‰, blue), and brackish marsh OC (-16‰, green). Figure S1.

470

27 ACS Paragon Plus Environment

Environmental Science & Technology

471

Page 28 of 38

Table S2. RP AMS data. Sample DB475

DB639

day count 88

337

RP Temp. µ mol C Limit, °C



362

53.32

0.0108 0.0016 -989

2

-27.9

0.991

446

22.74

0.0170 0.0029 -983

3

-27.6

0.986

714

25.09

0.0181 0.0026 -982

3

-

0.985

272

15.79

0.0486 0.0065 -952

7

500

56.54

0.2150 0.0019 -787

2

-27.2

824

48.70

0.0851 0.0022 -916

2

-28.0

21.52

0.1398 0.0065 -861

7

15.01

0.0218 0.0106 -978 11

139.26 0.0029 0.0008 -997 20.92

0.0102 0.0051 -990

1

702

41.68

0.0107 0.0025 -989

3

285

31.92

0.0133 0.0033 -987

3

499

28.92

0.0751 0.0036 -925

4

763

17.91

0.0174 0.0059 -983

6

487

17.41

0.1436 0.0081 -857

8

824

15.41

0.0407 0.0101 -960 10

347

133.00 0.0028 0.0009 -997

1

-29.3

6

-27.6

-996

1

-28.9

4

149.52 0.0018 0.0007 -998

1

626

28.59

0.0074 0.0037 -993

4

337

49.90

0.0064 0.0032 -994

3

710

28.60

0.0236 0.0055 -977

5

100.73 0.0265 0.0018 -974

2

400 676 329

49.19

0.1165 0.0031 -884

3

175.04 0.0446 0.0008 -956

1

0.998

0.977 0.989 0.991 -28.5

-990

3

-28.9

-996

1

-26.2

0.983 -27.9 -28.5

0.993 -28.4

0.991

-28.5

0.963

0.987 0.998

-26.6 -29.4

0.981 -28.6

-27.2 -944

2

-28.7

1

-28.5

0.994 0.978

-27.7

0.977

-27.3

0.961

-25.8 -869

0.998 0.987

-29.2 3

0.868 0.961

-27.6

-987

0.987 0.933

-28.4

0.0081 0.0041 -992

410

-28.8

-28.2 -905

39.48

5

0.924 0.867

-27.7

-26.5

6

881

2

0.955

-28.4

-26.8 -963

0.994

0.805

-28.8

3

0.0135 0.0054 -987

-27.9

-28.6

0.0039 0.0034 -993

0.0119 0.0059 -988

DB656

-29.3

31.17 29.55

678

1

661

18.53

DB341

-995

-29.4

700

694

-28.4

6

199

DB707

6

0.0127 0.0063 -987

678

535

-909

17.14

DB653

DB659

-29.8

401 315

337

2

5

507

DB657

-

0.997

DB646

881

-28.4

foil

-28.1

418

DB654



2

-860

1



3

752

-989

δ13C δ13Cgm

0.0044 0.0022 -996

336

46



0.0067 0.0026 -993

88

DB649



14 ∆ Cgm

29.22

DB658

678



24.52

503

DB665

∆14C

205

678

337



162

DB643

DB670

Fm

0.893

441

50.94

0.1336 0.0021 -867

2

-27.9

681

88.72

0.3049 0.0016 -697

2

-24.5

335

39.40

0.9694 0.0027

-38

3

391

29.40

0.9760 0.0039

-31

4

-20.8

713

84.00

0.9153 0.0029

-91

3

-20.9

334

25.61

0.0125 0.0063 -987

6

722

32.06

0.0162 0.0049 -984

5

238

13.70

0.0169 0.0077 -983

8

356

26.80

0.1104 0.0037 -890

4

-27.2

0.899

676

52.60

0.1169 0.0021 -884

2

-25.8

0.895

-66

-986

2

4

-18.4

-27.7

0.879 0.723 -20.2

0.109 0.165 -26.7

-25.8 -900

2

-27.5

0.115

0.986 0.985

-26.4

0.980

all radiocarbon data corrected for RP AMS blank; error propagated for gemoetric mean (gm) error

472

all δ13Cgm 1σ between 0.0 and 0.1; f OCb = 1 - f oil

28 ACS Paragon Plus Environment

Figure S3. RP isotopic data for high energy beach sediment samples. Profiles for Macondo crude oil (black) and a control sample from unoiled marsh (white) given for reference. A. Trend in profiles over time. B.-D. Profiles with isotopic data for samples at 88, 337, and 678 d. Left axis in top panel is CO2 evolution. ∆14C data points plot on right axis. Horizontal bars indicate temperature intervals over which the aliquots of CO2 were collected. Bottom panel plots δ13C for the same intervals. Tmax is temperature at which maximum pyrolysis occurs. Geometric mean isotopic values and dashed lines in red (∆14C) and blue (δ13C). Errors on the isotopic measurements are smaller than the symbols used to plot the values. Radiocarbon values here are not blank-corrected, which would only cause minimal change, on the scale of the size of the data points.

Page 29 of 38 Environmental Science & Technology

473

474

29

ACS Paragon Plus Environment

475

Figure S4. RP isotopic data for low energy beach sediment samples. Profiles for Macondo crude oil (black) and a control sample from unoiled marsh (white) given for reference. A. Trend in profiles over time. B.-D. Profiles with isotopic data for samples at 88, 337, and 678 d. Left axis in top panel is CO2 evolution. Right axis is ∆14C. Horizontal bars indicate temperature intervals over which the aliquots of CO2 were collected. Bottom panel plots δ13C for the same intervals. Tmax is temperature at which maximum pyrolysis occurs. Calculated bulk isotopic values are shown by dashed lines in red (∆14C) and blue (δ13C). Errors on the isotopic measurements are smaller than the symbols used to plot the values. Radiocarbon values here are not blank-corrected, which would only cause minimal change, on the scale of the size of the data points.

Environmental Science & Technology

30

ACS Paragon Plus Environment

Page 30 of 38

476

Figure S5. RP isotopic data for tar samples. Profiles for Macondo crude oil (black) and a control sample from unoiled marsh (white) given for reference. A. Trend in profiles over time. B.-E. Profiles with isotopic data for samples at 46, 507, 678, and 881 d. Left axis in top panel is CO2 evolution. Right axis is ∆14C. Horizontal bars indicate temperature intervals over which the aliquots of CO2 were collected. Bottom panel plots δ13C for the same intervals. Tmax is temperature at which maximum pyrolysis occurs. Calculated bulk isotopic values are shown by dashed lines in red (∆14C) and blue (δ13C). Errors on the isotopic measurements are smaller than the symbols used to plot the values. Radiocarbon values here are not blank-corrected, which would only cause minimal change, on the scale of the size of the data points.

Page 31 of 38 Environmental Science & Technology

31

ACS Paragon Plus Environment

Environmental Science & Technology

Figure S6. A. Carbon isotopic compositions of aliquots of sediment samples produced by RP AMS. Dark blue – 88 d; light blue – 337 d; orange – 678 d. The dotted lines are at the isotopic values for Macondo crude oil. Slopes of linear regressions for each date are interpreted to be proportional to degree of mixing (addition of OCb to the oil). At 88 d, variation in δ13C data with minimal variation in ∆14C data is interpreted as evidence of fractionation. At 337 d and 678 d, increasing variation in ∆14C with respect to variation in δ13C is interpreted as an increasing degree of incorporation of OCb. B. When treated similarly, data from tar balls produce less steep slopes, implying less incorporation of OCb and less mixing of oil into the environment when in the form of tar balls. Dark blue – 46 d; yellow – 507 d; orange – 678 d; maroon – 881 d. 477

32 ACS Paragon Plus Environment

Page 32 of 38

Page 33 of 38

Environmental Science & Technology

478 479 480 481 482 483 484 485 486 487 488 489 490 491 492 493 494 495 496 497 498 499 500 501 502 503 504 505 506 507 508 509 510 511 512 513 514 515 516 517 518 519

References (1) Rashid, M. A. Degradation of Bunker C oil under different coastal environments of Chebaducto Bay, Nova Scotia. Estuar. Coast. Mar. Sci. 1974, 2, 137-144. (2) Ward, D. M.; Atlas, R. M.; Boehm, P. D.; Calder, J. A. Microbial biodegradation and chemical evolution of oil from the Amoco spill. Ambio. 1980, 9(6), 277-283. (3) DeLaune, R. D.; Gambrell, R. P.; Pardue, J. H.; Patrick Jr., W. H. Fate of petroleum hydrocarbons and toxic organics in Louisiana coastal environments. Estuaries. 1990, 13(1), 72-80. (4) Wolfe, D. A.; Hameedi, M. J.; Michel, J.; Payne, J. R.; Galt, J. A.; Watabayashi, G.; Braddock, J.; Hanna, S.; Short, J.; O’Claire, C.; Rice, S.; Sale, D. The fate of the oil spilled from the Exxon Valdez. Environ. Sci. Technol. 1994, 28(13), 561-568. (5) Bence, A. E.; Kvenvolden, K. A.; Kennicutt, M. C. Organic geochemistry applied to environmental assessments of Prince William Sound, Alaska, after the Exxon Valdez oil spill – a review. Org. Geochem. 1996, 24(1), 7-42. (6) Wang, Z.; Fingas, M.; Page, D. S. Review – Oil spill identification. J. Chromatogr. A. 1999, 843, 369-411. (7) Prince, R. C.; Garrett, R. M.; Bare, E. R.; Grossman, M. J.; Townsend, T.; Suflita, J. M.; Lee, K.; Owens, E. H.; Sergy, G. A.; Braddock, J. F.; Lindstrom, J. E.; Lessard, R. R. The roles of photooxidation and biodegradation in long-term weathering of crude and heavy fuel oils. Spill Sci. Technol. B. 2003, 8(2), 145-156. DOI 10.1016/S1353-2561(03)000173 (8) Alaska North Slope Crude Blends; U.S. Department of Commerce; National Oceanic and Atmospheric Administration (NOAA); National Ocean Sevice; Office of Response and Restoration: Washington, DC, 2006; http://response.restoration.noaa.gov/oil-andchemical-spills/oil-spills/resources/alaska-north-slope-crude-blends.html (9) Owens, E. H.; Taylor, E.; Humphrey, B. The persistence and character of stranded oil on coarse-sediment beaches. Mar. Pollut. Bull. 2008, 56, 14-26. DOI 10.1016/j.marpolbul.2007.08.020 (10) Atlas, R. M.; Hazen, T.C. Oil biodegradation and bioremediation: a tale of the two worst spills in U.S. history. Environ. Sci. Technol. 2011, 45, 6709-6715. DOI 10.1021/es2013227 (11) Aeppli, C.; Carmichael, C. A.; Nelson, R. K.; Lemkau, K. L.; Graham, W. M.; Redmond, M. C.; Valentine, D. L.; Reddy, C. M. Oil weathering after the Deepwater Horizon disaster led to the formation of oxygenated residues. Environ. Sci. Technol. 2012, 46, 8799-8807. DOI 10.1021/es301538 (12) Liu, Z.; Liu, J.; Zhu, Q.; Wu, W. The weathering of oil after the Deepwater Horizon oil spill: insights from the chemical composition of the oil from the sea surface, salt marshes and sediments. Environ. Res. Lett. 2012, 7, 035302. DOI 10.1088/17489326/7/3/035302 (13) Ryerson, T. B.; et al. Atmospheric emissions from the Deepwater Horizon spill constrain air-water partitioning, hydrocarbon fate, and leak rate. Geophys. Res. Lett. 2011, 38, 1-6. DOI 10.1029/2011GL046726

33 ACS Paragon Plus Environment

Environmental Science & Technology

520 521 522 523 524 525 526 527 528 529 530 531 532 533 534 535 536 537 538 539 540 541 542 543 544 545 546 547 548 549 550 551 552 553 554 555 556 557 558 559 560 561 562 563

(14) Atlas, R. M. Effects of temperature and crude oil composition on petroleum biodegradation. Appl. Microbiol. 1975, 30(3), 396-403. (15) Hayes, M. O.; Michel, J.; Noe, D. C. Factors controlling initial deposition and long-term fate of spilled oil on gravel beaches. International Oil Spill Conference Proceedings: March 1991. 1991, 1991(1), 453-460. DOI 10.7901/2169-3358-1991-1-453 (16) Gatellier, C. R.; Oudin, J. L.; Fusey, P.; Lacaze, J. C.; Priou, M. L. Experimental ecosystems to measure fate of oil spills dispersed by surface active products. International Oil Spill Conference Proceedings: March 1973. 1973, 1973(1), 497-504. DOI 10.7901/2169-3358-1973-1-497 (17) Atlas, R. M. Microbial degradation of petroleum hydrocarbons: an environmental perspective. Microbiol. Rev. 1981, 45(1), 180-209. (18) Atlas, R. M. Petroleum biodegradation and oil spill bioremediation. Mar. Pollut. Bull. 1995, 31(4-12), 178-182. (19) McLachlan, A. Water filtration by dissipative beaches. Limnol. Oceanogr. 1989, 34(4), 774-780. (20) Forster, S.; Huettel, M.; Ziebis, W. Impact of boundary layer flow velocity on oxygen utilisation in coastal sediments. Mar. Ecol. Prog. Ser. 1996, 143, 173-185. (21) Huettel, M.; Rusch, A. Transport and degradation of phytoplankton in permeable sediment. Limnol. Oceanogr. 2000, 45(3), 534-549. (22) Kingston, P. F. Long-term environmental impact of oil spills. Spill Sci. Technol. B. 2002, 7(1-2), 53-61. (23) Reddy, C. M.; Eglington, T. I.; Hounshell, A.; White, H. K.; Xu, L.; Gaines, R. B.; Frysinger, G. S. The West Falmouth oil spill after thirty years: the persistence of petroleum hydrocarbons in marsh sediments. Envrion. Sci. Technol. 2002. 36, 4754-4760. DOI 10.1021/es020656n (24) Peacock, E. E.; Nelson, R. K.; Solow, A. R.; Warren, J. D.; Baker, J. L.; Reddy, C. M. The West Falmouth oil spill: ~100 Kg of oil found to persist decades later. Environ. Forensics. 2005, 6, 273-281. DOI 10.1080/15275920500194480 (25) White, H. K.; Liu, X.; Lima, A. L. C.; Eglington, T. I.; Reddy, C. Abundance, composition, and vertical transport of PAHs in marsh sediments. Environ. Sci. Technol. 2005, 39, 8273-8280. DOI 10.1021/es050475w (26) Crone, T. J.; Tolstoy, M. Magnitude of the 2010 Gulf of Mexico oil leak. Science. 2010, 330, 634. DOI 10.1126/science.1195840 (27) Barron, M. G. Ecological impacts of the Deepwater Horizon oil spill: implications for immunotoxicity. Toxicol. Pathol. 2012, 40, 315-320. DOI 10.1177/0192623311428474 (28) Silliman, B. R.; van de Koppel, J.; McCoy, M. W.; Diller, J.; Kasozi, G. N.; Earl, K.; Adams, P. N.; Zimmerman, A. R. Degradation and resilience in Louisiana salt marshes after the BP-Deepwater Horizon oil spill. P. Natl. Acad. Sci. USA. 2012, 109(28), 11234-11239. DOI 10.1073/pnas.1204922109 (29) Couvillion, B. R.; Barras, J. A.; Steyer, G. D.; Sleavin, W.; Fischer, M.; Beck, H.; Trahan, N.; Griffin, B.; Heckman, D. Land area change in coastal Louisiana from 1932 to 2010: U.S. Geological Survey Scientific Investigations Map 3164, scale 1:265,000, 12 p. pamphlet. 2011. 34 ACS Paragon Plus Environment

Page 34 of 38

Page 35 of 38

Environmental Science & Technology

564 565 566 567 568 569 570 571 572 573 574 575 576 577 578 579 580 581 582 583 584 585 586 587 588 589 590 591 592 593 594 595 596 597 598 599 600 601 602 603 604 605 606

(30) Mendelssohn, I. A.; Andersen, G. L.; Baltz, D. M.; Caffey, R. H.; Carman, K. R.; Fleeger, J. W.; Joye, S. B.; Lin, Q.; Maltby, E.; Overton, E. B.; Rozas, L. P. Oil Impacts on coastal wetlands: implications for the Mississippi River Delta ecosystem after the Deepwater Horizon oil spill. BioScience. 2012, 62(6), 562-574. DOI 10.1525/bio.2012.62.6.7 (31) Blum, M. D.; Roberts, H. H. Drowning of the Mississippi Delta due to insufficient sediment supply and global sea-level rise. Nat. Geosci. 2009, 2, 488-491. DOI 10.1038/NGEO553 (32) Hester, M. W.; Mendelssohn, I. A. Long-term recovery of a Louisiana brackish marsh plant community from oil-spill impact: vegetation response and mitigating effects of marsh surface elevation. Mar. Environ. Res. 2000, 49, 233-254. (33) McClenachan, G.; Turner, R. E.; Tweel, A. W. Effects of oil on the rate and trajectory of Louisiana marsh shoreline erosion. Environ. Res. Lett. 2013, 8, 044030. DOI 10.1088/1748-9326/8/4/044030 (34) Rosenheim, B. E.; Day, M. B.; Domack, E. W.; Schrum, H.; Benthein, A.; Hayes, J. M. Antarctic sediment chronology by programmed-temperature pyrolysis: methodology and data treatment. Geochem. Geophy. Geosy. 2008, 9(4), Q04005. DOI 10.1029/2007GC001816 (35) Rosenheim, B. E.; Galy, V. Direct measurement of riverine particulate organic carbon age structure. Geophys. Res. Lett. 2012, 39, L19703. DOI 10.1029/2012GL052883 (36) Rosenheim, B. E.; Roe, K. M.; Roberts, B. J.; Kolker, A. S.; Allison, M. A.; Johannesson, K. H. River discharge influences on particulate organic carbon age structure in the Mississippi/Atchafalaya River system. Global Biogeochem. Cy. 2013a, 27, 1-13. DOI 10.1002/gbc.20018 (37) Rosenheim, B. E.; Santoro, J. A.; Gunter, M.; Domack, E. W. Improving Antarctic sediment 14C dating using ramped pyrolysis: an example from the Hugo Island Trough. Radiocarbon. 2013b, 55(1): 115-126. DOI 10.2458/azu_js_rc.v55i1.16234 (38) Rosenheim, B. E.; Pendergraft, M. A.; Flowers, G. C.; Carney, R.; Sericano, J.; Amer, R. M.; Chanton, J.; Dincer, Z.; Wade, T. Employing extant stable carbon isotope data in Gulf of Mexico sedimentary organic matter for oil spill studies. Deep Sea Res. Pt. II. 2014. DOI 10.1016/j.dsr2.2014.03.020 (39) Pendergraft, M. A.; Dincer, Z.; Sericano, J. L.; Wade, T.; Kolasinski, J.; Rosenheim, B. E. Linking ramped pyrolysis isotope data to oil content through PAH analysis. Environ. Res. Lett. 2013, 8, 044038. DOI 10.1088/1748-9326/8/4/044038 (40) White, H. K.; Reddy, C. M.; Eglinton, T. I. Radiocarbon-based assessment of fossil fuel-derived contaminant associations in sediments. Envrion. Sci. Technol. 2008, 42, 5428-5434. DOI 10.1021/es800478x (41) Ahad, J. M. E.; Burns, L.; Mancini, S.; Slater, G. F. Assessing microbial mptake of petroleum pydrocarbons in groundwater systems using natural abundance radiocarbon. Environ. Sci. Technol. 2010, 44, 5092-5097. DOI 10.1021/es100080c (42) Graham, W. M.; Condon, R. H.; Carmichael, R. H.; D’Ambra, I.;Patterson, H. K.; Linn, L. J.; Hernandez, F. J. Jr. Oil carbon entered the coastal planktonic food web

35 ACS Paragon Plus Environment

Environmental Science & Technology

607 608 609 610 611 612 613 614 615 616 617 618 619 620 621 622 623 624 625 626 627 628 629 630 631 632 633 634 635 636 637 638 639 640 641 642 643 644 645 646 647 648 649

during the Deepwater Horizon oil spill. Environ. Res. Lett. 2010, 5, 045301. DOI 10.1088/1748-9326/5/4/045301 (43) Chanton, J. P.; Cherrier, J.; Wilson, R. M.; Sarkodee-Ado, J.; Bosman, S.; Mickle, A.; Graham, W. M. Radiocarbon evidence that carbon from the Deepwater Horizon spill entered the planktonic food web of the Gulf of Mexico. Environ. Res. Lett. 2012, 7, 045303. DOI 10.1088/1748-9326/7/4/045303. (44) Cherrier et al. 2013 (45) Mahmoudi, N.; Fulthorpe, R. R.; Burns, L.; Mancini, S.; Slater, G. F. Assessing microbial carbon sources and potential PAH degradation using natural abundance 14C analysis. Environ. Pollut. 2013, 175, 125-130. DOI 10.1016/j.envpol.2012.12.020. (46) Silverman, S. R.; Epstein, S. Carbon isotopic compositions of petroleums and other sedimentary organic materials. Am. Assoc. Pet. Geol. Bull. 1958, 42, 5, 998-1012. (47) Matthews, D. E.; Hayes, J. M. Isotope-ratio-monitoring gas chromatographymass spectrometry. Anal. Chem. 1978, 50, 11, 1468-1473. (48) Chung, H. M.; Brand, S. W.; Grizzle, P. L. Carbon isotope geochemistry of Paleozoic oils from Big Horn Basin. Geochim. Cosmochim. Acta. 1981, 45, 1803-1815. (49) Macko, S. A.; Parker, P. L.; Botello, A. V. Persistence of spilled oil in a Texas salt marsh. Environ. Pollut. B. 2. 1981, 119–128. (50) Macko, S. A.; Parker, P. L. Stable nitrogen and carbon isotope ratios of beach tars on South Texas barrier islands. Mar Environ Res. 1983, 10, 93-103. (51) Sofer, Z. Stable carbon isotope compostions of crude oils: application to source depositional environments and petroleum alteration. AAPG Bull. 1984, 68, 1, 31-49. (52) Mansuy, L.; Philp, R. P.; Allen, J. Source identification of oil spills based on the isotopic composition of individual components in weathered oil samples. Environ. Sci. Technol. 1997, 31, 3417-3425. (53) Wang, Z.; Fingas, M.; Landriault, M.; Sigouin, L. Identification and linkage of tarballs from the coasts of Vancouver Island and Northern California using GC/MS and isotopic techniques. J. High Resol. Chromatogr. 1998, 21, 7, 383-395. (54) Pond, K. L.; Huang, Y.; Wang, Y.; Kulpa, C. F. Hydrogen isotopic composition of individual n-alkanes as an intrinsic tracer for bioremediation and source identification of petroleum contamination. Environ. Sci. Technol. 2002, 36, 724-728. (55) Li, Y.; Xiong, Y.; Yang, W.; Xie, Y.; Li, S.; Sun, Y. Compound-specific stable carbon isotopic composition of petroleum hydrocarbons as a tool for tracing the source of oil spills. Mar. Pollut. Bull. 2009, 58, 114-117. (56) Natter, M.; Keevan, J. Wang, Y.; Keimowitz, A. R.; Okeke, B. C.; Son, A.; Lee, M. Level and degradation of Deepwater Horizon spilled oil in coastal marsh sediments and pore-water. Environ. Sci. Technol. 2012, 46, 5744-5755. DOI 10.1021/es300058w (57) Chmura, G. L.; Aharon, P.; Socki, R. A.; Abernethy, R. An inventory of 13C abundances in coastal wetlands of Louisiana, USA: vegetation and sediments. Oecologia. 1987, 74, 264-271. (58) Brodie, C. R. Evidence for bias in C/N, δ13C and δ15N values of aquatic and terrestrial organic materials due to acid pre-treatment methods. Pages News. 2011, 19, 2, 65-67.

36 ACS Paragon Plus Environment

Page 36 of 38

Page 37 of 38

Environmental Science & Technology

650 651 652 653 654 655 656 657 658 659 660 661 662 663 664 665 666 667 668 669 670 671 672 673 674 675 676 677 678 679 680 681 682 683 684 685 686 687 688 689 690 691 692

(59) Sharp, Z. Principles of Stable Isotope Geochemistry; Prentice Hall: Upper Saddle River, New Jersey, USA, 2007. (60) Stuiver, M.; Pollach, H. A. Reporting of 14C data. Radiocarbon. 1977, 19(3), 355-363. (61) Parnell, A. C.; Inger, R.; Bearhop, S; Jackson, A. L. Source partitioning using stable isotopes: coping with too much variation. PLoS One. 2010, 5, e9672. DOI 10.1371/journal.pone.0009672 (62) Haines, E. B. Stable carbon isotope ratios in the biota, soils and tidal water of a Georgia salt marsh. Estuar. Coast. Mar. Sci. 1976, 4, 609–616. (63) Smith, B. N.; Epstein, S. Two categories of 13C/12C ratios for higher plants. Plant Physiol. 1971, 47, 380–384. (64) Burns, K. A.; Garrity, S. D.; Jorissen, D.; MacPherson, J.; Stoelting, M.; Tierney, J.; Yelle-Simmons, L. The Galeta oil spill. II. Unexpected persistence of oil trapped in mangrove sediments. Estuar. Coast. Shelf S. 1994, 38, 349-364. (65) Mortazavi, B.; Horel, A.; Beazley, M. J.; Sobecky, P. A. Intrinsic rates of hydrocarbon biodegradation in Gulf of Mexico intertidal sandy sediments and its enhancement by organic substrates. J. Hazard. Mater. 2013, 244-245, 537-544. DOI 10.1016/j.jhazmat.2012.10.038 (66) Short, J. W.; Irvine, G. V.; Mann, D. H.; Maselko, J. M.; Pella, J. J.; Lindeberg, M. R.; Payne, J. R.; Driskell, W. B.; Rice, S. D. Slightly weathered Exxon Valdez oil persists in Gulf of Alaska beach sediments after 16 years. Environ. Sci. Technol. 2007, 41, 1245–1250. DOI 10.1021/es0620033 (67) Kvenvolden, K. A.; Hostettler, F. D.; Carlson, P. R.; Rapp, J. B.; Threlkeld, C. N.; Warden, A. Ubiquitous tar balls with a California-source signature on the shorelines of Prince William Sound, Alaska. Environ. Sci. Technol. 1995, 29, 2684-2694. (68) Elango, V.; Urbano, M.; Lemelle, K. R.; Pardue, J. H. Biodegradation of MC252 oil in oil:sand aggregates in a coastal headland beach environment. Front. Microbiol. 2014, 5, 161. DOI 10.3389/fmicb.2014.00161 (69) Gros, J.; Reddy, C. M.; Aeppli, C.; Nelson, R. K.; Carmichael, C. A.; Arey, J. S. Resolving biodegradation patterns of persistent saturated hydrocarbons in weathered oil samples from the Deepwater Horizon disaster. Environ. Sci. Technol. 2014, 48, 3, 16281637. DOI 10.1021-es4042836 (70) Behar, F. H.; Albrecht, P. Correlations between carboxylic acids and hydrocarbons in several crude oils. Alteration by biodegradation. Org. Geochem. 1984, 6, 597-604. (71) Jaffe, R.; Gallardo, M. T. Application of carboxylic acid biomarkers as indicators of biodegradation and migration of crude oils from the Maracaibo Basin, western Venezuela. Org. Geochem. 1993, 20, 7, 973-984. (72) Meredith, W.; Kelland, S.-J.; Jones, D. M. Influence of biodegrdadation on crude oil acidity and carboxylic acid decomposition. Org. Geochem. 2000, 31, 1059-1073. (73) Watson, J. S.; Jones, D. M.; Swannell, R. P. J.; van Duin, A. C. T. Formation of carboxylic acids during aerobic biodegradation of crude oil and evidence of microbial oxidation of hopanes. Org. Geochem. 2002, 33, 1153-1169.

37 ACS Paragon Plus Environment

Environmental Science & Technology

693 694 695 696 697 698 699 700 701 702

(74) Hall, G. J.; Frysinger, G. S.; Aeppli, C.; Carmichael, C. A.; Gros, J.; Lemkau, K. L.; Nelson, R. K.; Reddy, C. M. Oxygenated products of Deepwater Horizon oil come from surprising precursors. Mar. Pollut. Bull. 2013, 75, 140-149. DOI 10.1016/j.marpolbul.2013.07.048. (75) Lemkau, K. L.; McKenna, A. M.; Podgorski, D. C.; Rodgers, R. P.; Reddy, C. M. Molecular evidence of heavy-oil weathering following the M/V Cosco Busan spill: insights from fourier transform ion cyclotron resonance mass spectrometry. Environ. Sci. Technol. 2014, 48, 3760-3767. DOI 10.1021/es403787u (76) Keeling, C. D. The concentration and isotopic abundances of atmospheric carbon dioxide in rural areas. Geochim. Cosmochim. Acta. 1958, 13, 322–334.

703 704

705

706

707

Acknowledgements

708

The authors thank Dr D Finklestein (Hobart and William Smith Colleges) and Dr A

709

Schimmelmann (Indiana University) for their assistance in field work and experimental

710

design. We also thank all who assisted with sample collection and preparation. Analyses

711

were funded by NSF grants EAR-1058517 and EAR-1045845 to BER and by the

712

Consortium for Advanced Research on Transport of Hydrocarbon in the Environment

713

(CARTHE). MAP was partially funded by Louisiana Sea Grant (NOAA) awarded to Dr

714

N Gasparini and by CARTHE. Dr C Taylor (Tulane University) is acknowledged for

715

donating a portion of her Macondo oil for this study.

38 ACS Paragon Plus Environment

Page 38 of 38