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Four Years after the Deepwater Horizon Spill: Molecular Transformation of Macondo Well Oil in Louisiana Salt Marsh Sediments Revealed by FT-ICR Mass Spectrometry Huan Chen, Aixin Hou, Yuri E. Corilo, Qianxin Lin, Jie Lu, Irving A Mendelssohn, rui zhang, Ryan Patrick Rodgers, and Amy M McKenna Environ. Sci. Technol., Just Accepted Manuscript • DOI: 10.1021/acs.est.6b01156 • Publication Date (Web): 28 Jul 2016 Downloaded from http://pubs.acs.org on July 29, 2016

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Environmental Science & Technology

Four Years after the Deepwater Horizon Spill: Molecular Transformation of Macondo Well Oil in Louisiana Salt Marsh Sediments Revealed by FTICR Mass Spectrometry

5 6 7 8 9 10 11 12 13 14

Huan Chen†, Aixin Hou‡, Yuri E. Corilo†, Qianxin Lin§, Jie Lu┴, Irving A. Mendelssohn§, Rui Zhang‡, Ryan P. Rodgers†,┴, and Amy M. McKenna†,* †

National High Magnetic Field Laboratory, Florida State University ,1800 East Paul Dirac Dr., Tallahassee, FL 32310-4005 ‡

Department of Environmental Sciences, School of the Coast and Environment, Louisiana State University, Baton Rouge, LA 70803 USA. §

Department of Oceanography and Coastal Sciences, School of the Coast and Environment, Louisiana State University, Baton Rouge, LA 70803 USA.

15 16

┴Future Fuels Institute, Florida State University, 1800 East Paul Dirac Drive,

17 18

*To whom correspondence should be addressed. Tel.: +1 850 644 4809; Fax +1 850 644 1366. E-mail address: [email protected]

19

Re-Submitted to Environ. Sci. Technol. (es-2015-015659m)

20

■ ABSTRACT

21

Gulf of Mexico saltmarsh sediments were heavily impacted by Macondo Well Oil (MWO)

22

released from the 2010 Deepwater Horizon (DWH) oil spill. Detailed molecular-level

23

characterization of sediment extracts collected over 48 months post-spill highlights the

24

chemical complexity of highly polar, oxygen-containing compounds that remain

25

environmentally persistent. Electrospray ionization (ESI) Fourier transform ion cyclotron

26

resonance mass spectrometry (FT-ICR MS) combined with chromatographic pre-

27

fractionation correlates bulk chemical properties to elemental compositions of oil

28

transformation products as a function of time. Carboxylic acid incorporation into parent

29

MWO hydrocarbons detected in sediment extracts (corrected for mass loss relative to

30

C30 hopane), proceeds with an ~3-fold increase in O2 species after 9 months to a

31

maximum of ~5.5-fold after 36 months, compared to the parent MWO. More importantly,

Tallahassee, Florida 32310-4005, United States

ACS Paragon Plus Environment

July 5, 2016


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higher-order oxygenated compounds (O4-O6) not detected in the parent MWO, increase

33

in relative abundance with time, as lower order oxygenated species are transformed into

34

highly polar, oxygen-containing compounds (Ox, where x>3). Here, we present the first

35

molecular-level characterization of temporal compositional changes that occur in

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Deepwater Horizon derived oil contamination deposited in a saltmarsh ecosystem from

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9 to 48 mos post-spill, and identify highly oxidized Macondo well oil compounds that are

38

not detectable by routine GC-based techniques.

39 40 41 42 43 44 45

Keywords: Deepwater Horizon, petroleum, petroleomics, crude oil, Fourier transform, ion cyclotron resonance, gas chromatography, time series

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■ INTRODUCTION

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The explosion and sinking of the Deepwater Horizon (DWH) oil platform in the

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summer of 2010 released an judicially determined 3.1 million barrels of crude oil into the

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Gulf of Mexico ecosystem,1 the largest marine oil spill in United States’ history.2 Point-

50

source releases of anthropogenic pollution, such as oil spills, threaten coastal habitats3

51

and have been linked to immediate animal die-offs, altered animal behaviors,4,

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persistence of oil-derived compounds in coastal food webs.6, 7 The oil released from the

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Macondo Well impacted over 1000 linear miles of shoreline, and contaminated 463 total

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miles of saltmarsh (Louisiana: 436 miles), Mississippi: 21 miles) and Alabama: 6 miles).8

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Coastal salt marshes provide vital services to coastal ecosystems, including shoreline

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protection, carbon sequestration, and water quality enhancement, and generate

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revenue from fisheries, agriculture, and recreational tourism.6,

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particularly sensitive to oil contamination due to low wave action and high capacity of

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sediments to absorb organic contaminants,11 and accelerated shoreline erosion has

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been reported since the DWH event.6

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DWH-derived

compounds

that

reached

the

9, 10

shore

5

and

Salt marshes are

underwent

rapid

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biodegradation in salt marsh sediments,12-14 but the long-term impact of environmentally

63

persistent petroleum compounds and their weathering products remains unknown.15-17

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Conventional characterization of Deepwater Horizon contamination relies almost

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exclusively on gas chromatography-based techniques18-26 that only account for a

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fraction of the mass of pre-spill Macondo Well Oil (MWO) on a molecular basis.27 Abiotic

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and biotic weathering processes create oxygenated transformation products that

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account for 60~80% of extractable material19, which further challenge GC-based

69

characterization techniques due to increased polarity and decreased volatility.19, 20, 28, 29

70

Recent studies address the toxicological impact of weathered oil contaminants not

71

detected by GC-based techniques4,

72

techniques to identify molecular transformations that occur to petroleum hydrocarbons

73

after environmental release.

28

and highlight the need for advanced analytical

74

Recent GC-based reports suggest that the level of hydrocarbons extracted from

75

salt marsh samples from Barataria Bay had reached background levels within 18 mos

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post-spill mostly due to biodegradation by indigenous microbial communities.6,

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12


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However, a more recent report found that oil residues remained detectable up to 36

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months in the top 2 cm of sediment of heavily oiled marshes and have been heavily

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degraded.26 GC-based techniques are limited to compounds with volatility below ~400

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°C to prevent column degradation. The formation of oxygenated transformation products

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through biodegradation/photo-oxidation decreases the applicability of GC-based

82

techniques due to the low volatility and high polarity of MWO oxidized products.

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The compositional complexity of crude oil challenges all analytical techniques,

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and the term “unresolved complex mixture” (UCM) describes the raised baseline hump

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observed in gas chromatograms of petroleum.30 Recent reports demonstrate the

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potential of using Fourier Transform Ion Cyclotron Resonance Mass Spectrometry (FT-

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ICR MS) to target heavily weathered petroleum compounds without boiling point

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limitations27, 31-33 FT-ICR MS routinely achieves ultrahigh resolving power (m/∆m50% =

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1,000,000 at m/z 500, in which ∆m50% is the mass spectral peak width at half-maximum

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peak height), sufficient to separate and identify more than 80,000 unique elemental

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compositions in a single mass spectrum for weathered oil29 and identify molecular-level

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transformations that occur during degradation.27, 29 Early environmental applications of

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FT-ICR MS report an increased abundance of high molecular weight (>200-300 Da),

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highly oxidized transformation products.34-37 Lemkau et. al applied ultrahigh resolution

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FT-ICR MS to catalogue compositional changes that occur to oil residues derived from

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the 2007 M/V Cosco Busan heavy fuel oil (HFO) spill in San Francisco Bay over 617

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days and observed an increased abundance of condensed aromatic, oxygen-containing

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compounds relative to the parent HFO.31,

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applied to elemental compositions derived from FT-ICR MS characterization of field

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samples identified a suite of recalcitrant polar petroleum markers that facilitate source

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identification of oil spilled from two possible storage tanks ruptured when the M/V Cosco

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Busan struck the San Francisco--Oakland Bay Bridge.33 More recently, FT-ICR MS

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characterization was applied to parent Deepwater Horizon oil,27 and identified unique

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ketone transformation products of weathered oil that reached Pensacola Beach in

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2010.32

38

Principal Component Analysis (PCA)

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More than four years after the Deepwater Horizon disaster, salt marsh sediments

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along the Gulf of Mexico coast remain contaminated with Macondo Well oil compounds.

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We combine comprehensive two-dimensional gas chromatography with mass

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spectrometry (GC×GC MS) and flame ionization detection (GC×GC-FID), and

110

electrospray ionization (ESI) FT-ICR mass spectrometry to Deepwater Horizon oil

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contamination extracted from the same location in northern Barataria Bay from 9 to 48

112

mos post spill and catalogue oxidation patterns that occur to oil compounds in salt

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marsh sediments. Highly polar (acidic), oxygen-containing hydrocarbons are compared

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to pre-spill oil, and we identify recalcitrant oxygen-containing compounds derived from

115

Deepwater Horizon oil degradation at the molecular level.

116 117

■ EXPERIMENTAL METHODS

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Sample Collection. Figure 1 shows a map of northern Barataria Basin of Louisiana,

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USA, approximately 8 km x 5 km (coordinates N 29.44060° - 29.47459°, W 89.88492° -

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89.94647°), with 21 sampling locations (seven each that received heavy oiling (Sites 1-

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7), moderate oiling (sites 8-14), and no observed oiling or reference (sites 15-21), based

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on the Shoreline Cleanup Assessment Technique (SCAT) Program (28 April 2010), field

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observations, and total petroleum hydrocarbon measurements.39, 40 No cleanup events

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at the sampling sites were noted during this period. Surface sediments (0-2 cm) were

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collected in pre-autoclaved glass jars and frozen (-80 °C) at Louisiana State University,

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LA. For each time point, all seven samples from reference, moderately, or heavily oiled

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sites were collected and homogenized respectively to obtain a composite sample.

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Heavily oiled sites were collected at 9, 18, 24, 31, 36, 41, 43 and 48 mos post-spill.

129

Moderately oiled sites sampled at 9, 41 and 48 mos from seven moderately oiled

130

locations, and reference sites collected and homogenized from seven reference

131

locations (Table S-1). The composite samples were shipped in EPA certified glass jars

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to the National High Magnetic Field Laboratory (Tallahassee, FL, USA) for analysis.

133 134

Sediment Extraction. Approximately 20 g of sediment were homogenized with an

135

equal weight of sodium sulfate drying agent, loaded into a 30 x 100 mm cellulose

136

thimble, and Soxhlet extracted with dichloromethane for 4 h, desolvated under dry

137

nitrogen (N2) and weighed.41

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Bulk Elemental Analysis. Complete experimental methods can be found in the

139

supporting material. Briefly, elemental analysis was performed on MWO and sediment

140

extracts collected from heavily oiled sites at 9, 18, 24, 31, 36, 41, and 48 mos post spill

141

on a Thermo Finnigan Elemental Analyzer (FLASH EA 112, San Jose, CA, USA). Due

142

to sample limitations, moderately oiled and reference sites were not analyzed. Detailed

143

description can be found in Supporting Information.

144

GC×GC-MS and GC×GC-FID. Comprehensive two-dimensional gas chromatagraphy

145

(GC×GC) and

146

collected from heavily oiled sites at 9, 18, 24, 31, 36, 41, and 48 mos post spill. Each

147

sample was analyzed with GC×GC coupled to a time-of-flight mass spectrometry (ToF-

148

MS) for the identification of petroleum hydrocarbons. GC×GC with a flame ionization

149

detector (GC×GC-FID) was used for the quantitation of the petroleum biomarkers. The

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fraction losses of total oil and individual compounds were calculated by nomalizing the

151

peak area of individual compound to that of 17α(H),21β(H)-hopane (herein refered to as

152

C30-hopane) and comparing to the corresponding values to MWO.42,

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experimental details and calculations are provided in Supporting Information.

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Fourier Transform Ion Cyclotron Resonance Mass Spectrometry. Macondo well

155

crude oil was provided by BP oil company through the Gulf Coast Restoration

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Organization. All solvents were HPLC grade (Sigma-Aldrich Chemical Co., St. Louis,

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MO). Prior to mass spectral analysis, MWO and extracts were diluted in HPLC grade

158

toluene to make a stock solution (1 mg/ mL) that was further diluted with equal parts

159

(vol: vol) methanol spiked with 2 % (by volume) formic acid for positive ion electrospray

160

ionization (ESI) or 0.25 % (by volume) tetramethylammonium hydroxide (CAS no. 75-

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59-2, TMAH, 25 % by weight in methanol) for negative ion ESI FT-ICR MS. Sample

162

preparation method, ionization source conditions, and detailed FT-ICR MS conditions

163

can be found in Supporting Information.

elemental analysis were performed on MWO and sediment extracts

164 165

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43

Complete

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■ RESULTS AND DISCUSSION

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Extraction of MWO from Saltmarsh Sediments. Table S-1 shows the total extracted

169

mass of oil isolated from 20 g each of heavily oiled, moderately oiled, and reference

170

sites.

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sediments occurs between 9 mos (26 wt%) and 48 mos (2.4 wt%), indicating oil removal

172

from marshes with time. This suggests the majority of MWO deposition occurred in the

173

early months after the spill, and oil residues were removed or transformed with time.

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However, after 48 mos the total extracted oil is ~ 438 times greater than reference sites,

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indicating the long-term persistence of oil-like compounds in the marshes. Sediments

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that received moderate oiling contained approximately the same mass of oil residue

177

after 9 mos (0.470 g), compared to heavily oiled sites after 48 mos (0.482 g). This

178

suggests that residual MWO contamination is still present in salt marsh sediments four

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years after the spill in concentrations that exceed non-oiled reference sites, even though

180

the majority of the oil has been removed or degraded.

A 10-fold decrease in the total amount of oil extracted from heavily oiled

181 182

(Insert Figure 1 here)

183 184

Gas Chromatography of MWO and Sediment Extracts. Figure S-1 shows gas

185

chromatograms of MWO and petroleum residues collected from 9 to 48 mos at heavily

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oiled saltmarsh sites. In the first 9 mos, the complete loss of low molecular weight

187

aromatic hydrocarbons and normal saturated hydrocarbons (below ~nC20) through

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evaporation, water-washing and other weathering processes occurred relative to the

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MWO. After 9 mos, the appearance of an unresolved complex mixture occurs based on

190

GC analysis, and by 48 mos, few or almost no heavy alkanes are identifiable by GC

191

analysis above the UCM (Figure S-1), in agreement with previous GC-based studies on

192

the DWH spill, where the removal of n-alkanes, isoprenoids, and two-ring PAHs were

193

reported in beach samples collected within 18 mos of the spill.19,

194

sediment extracts indicate the presence of weathered oil components, but detection is

195

limited to compounds that are volatile below ~400 °C.27, 30

7


24

GC analysis of


196

Oil Depletion Estimated by GC×GC-FID Analysis. Each GC×GC-FID image was

197

base-plane subtracted and normalized to the conserved biomarker C30-hopane43 to

198

estimate degradation in sediment extracts.42, 44, 45 Figure 2 shows the calculated loss of

199

total petroleum hydrocarbons (TPH) and chrysenes (C1-C3) normalized to C30 hopane

200

for 9, 24, 36 and 48 mos. After 9 mos, ~45% of the parent MWO is removed, and after

201

48 mos, ~63% of the TPHs have been removed. The percentage of total oil and

202

individual compound losses assume that the C30-hopane is conserved across the

203

sampling time, although C30-hopane can be degraded under certain conditions.3-5

204

Between 36 and 48 mos, no significant weathering loss is observed, which indicates

205

either oil is continually depleted up to 36 mos and then slows down, or C30-hopane

206

begins to degrade with time. The long term fate of heavily degraded oil relies on reliable

207

fingerprinting methods when the biomarker fidelity is questionable, which is the subject

208

of this study.

209

For chrysenes, the extent of loss increases with degree of alkylation. Chrysene is

210

depleted by 58% after 9 mos, but only 64% after 48 mos. However, ~88% of C3-

211

chrysene is lost at 48 mos (Figure 2). The loss of alkyl-substituted chrysenes prior to

212

less alkylated analogs corresponds to photo-degradation rather than biodegradation.46

213

No obvious difference of Chrysene losses are observed from 9 to 48 mos.

214


215

Elemental Analysis of Heavily Contaminated Sediment Extracts. Bulk elemental

216

analysis of sediments that received heavy oiling identify global changes in weight

217

percent carbon, hydrogen, nitrogen, oxygen and sulfur (Table S-2) compared to parent

218

MWO. The total mass fraction of sulfur increases after 48 mos to 0.9% by weight

219

compared to 0.5% by weight in parent MWO. Nitrogen content remains constant from

220

parent MWO (0.3% by weight) to 48 mos (0.3% by weight). The most dramatic change

221

in bulk composition occurs in the oxygen content of field samples. The total mass

222

fraction for samples collected in January 2011 indicates a more than 7-fold increase in

223

oxygen (3.9% by weight) compared to the parent MWO (0.5% by weight) after 9 mos,

224

which corresponds to oxidative transformation products.19, 20, 31, 32, 38 The oxygen content

225

increases to 4.7% by weight after 24 mos, but remains relatively constant across the

226

time series. The significant increase of oxygen content indicates oxidative processes

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dominated oil weathering during the first few months after the spill, and produced

228

oxidized transformation products that persist in the environment.19 Therefore, we focus

229

on characterization of oxygen-containing compounds and molecular transformations

230

that occur as a function of time.

231 232

Acidity Increases in Field Samples Revealed by Aminopropyl Silica (APS)

233

Isolation. Bulk compositional changes indicate that oxygen content is increasing, but do

234

not identify the chemical functionality of oxygen transformation products. Since toxicity

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changes with chemical functionality, identification of acidic functional groups is critical to

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the long-term ecological impact of MWO in coastal areas. Previous studies identified

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ketone transformation products in MWO-affected beach sands, and naphthenic acids

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inherent in crude oil have known toxicity to marine bacteria,47 phytoplankton,48

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zooplankton,49 plants,50 fish,51, 52 and mammals53 at low concentrations (2.5 – 5 mg L-

240

1 54

241

water-solubility.55 Isolation and fractionation of crude oil compounds on aminopropyl

242

silica (APS) has been reported to identify acidic functional groups in parent MWO and

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selected field samples.56 Briefly, carboxylic acid-containing compounds interact via

244

strong hydrogen-bonding with APS. Non-acidic compounds elute with dichloromethane

245

(DCM) in fraction 1, and moderately acidic species elute with DCM-methanol in fraction

246

2. Carboxylic acids elute in fraction 3 with the addition of formic acid.56 Table 1 shows

247

fractional percent yields and total percent recovery for APS fractions for parent MWO

248

and field samples collected 9 mos, 36 mos and 48 mos postspill. Due to sample

249

limitation, we did not have enough extracted materials to run the separation in triplicates.

250

The previous published data show that the standard error of APS extraction is no

251

greater than 1.1% based on triplicate analysis.56 Parent MWO is a light, Louisiana oil

252

with high API° gravity (35.2)57, and low total acid number, and the majority of the

253

compounds (62%) recovered as nonpolar compounds (i.e., non-acids) in fraction 1 and

254

less than 1% elute in fraction 2 (0.7%) and fraction 3 (0.42%).15, 57 (Parent MWO is a

255

light crude with a high abundance of highly volatile, low molecular weight petroleum

256

hydrocarbons at atmospheric conditions, and approximately ~17% of MWO compounds

257

evaporated during the desolvation process determined independently. Therefore, the

),

and low molecular weight naphthenic acids are highly toxic47 due to increased

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total recovered yield for parent MWO includes the total mass lost through evaporation

259

under dry nitrogen plus the dry weight of each fraction.) After 9 mos, 3% of compounds

260

elute as moderately acidic species, and ~6% contain one or more carboxylic acid

261

moieties. Between 36 and 48 mos, moderately acidic compounds remain constant

262

between ~3.8-4%, and carboxylic acids increase slightly from ~8% to ~9% yield. This

263

could indicate secondary oxidation of moderately acidic compounds to create

264

compounds

265

characterization and future toxicity of heavily oxidized, acidic transformation products

266

will probe the long-term impact of these compounds to saltmarsh ecosystems.

that

contain

one

or more

carboxylic

acids.

Detailed

molecular

267 268 269

270 271 272 273 274 275 276

Table 1. Percent Recovery of Each Fraction and Total Percent Recovery for APS Acid Extractions on MWO and Selected Field Samples MWO 9 mos 36 mos 48 mos % of Fraction1 a

62.72

70.10

73.80

75.18

% of Fraction2 b

0.70

3.05

3.82

4.00

% of Fraction 3 c

0.42

6.88

8.30

9.44

Total % Recovery

63.84+17.12d

80.03

85.92

88.62

a. b. c.

d.

Fraction 1 denotes non-acid compounds eluted with 100% (v) DCM. Fraction 2 denotes non-acid compounds eluted with 50/50 (v/v) DCM: MeOH Fraction 3 denotes acid-containing compounds fraction eluted with 50/50/5 (v/v/v)DCM: MeOH: FA The % of volatile compounds in the unweathered MWO which was evaporated under dry nitrogen. The total percentage mass recovery of MWO reached 80.96% after taking this portion into consideration.

277 278

Acidic Speciation by Negative-ion ESI FT-ICR MS. Negative-ion electrospray

279

ionization selectively ionizes acidic species (e.g., carboxylic acids, pyrrolic nitrogen)

280

through deprotonation, and combined with FT-ICR mass spectrometry provides

281

elemental composition assignment to polar compounds in crude oil that are inaccessible

282

by conventional GC based techniques due to volatility limitations27,

283

separation shows that the acidity of the field samples increases, we focus on examining

284

the evolution of acidic species upon weathering by negative-ion ESI, which selectively

10


56, 58

Since APS

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285

targets

acidic

species.

Speciation

by

positive-ion

ESI,

which

targets

286

functionalities, shows very little change, and is provided in Supporting Information.

basic

287 288

Molecular Weight Distribution. Figure S-2 shows broadband negative-ion ESI FT-ICR

289

mass spectra for parent MWO and select field samples. Broadband MWO and field

290

samples span a similar molecular weight range (~m/z 250-950), with an increased

291

abundance of low molecular weight compounds between m/z 400-450 after 9 mos

292

relative to MWO. After 36 and 48 mos, low molecular weight compounds

293

(300 1,000,000) for each peak

317

identified at m/z 501 for each time point.

318 319

Heteroatom Class Distribution for MWO. When combined with Kendrick mass

320

sorting, FT-ICR MS provides sub-ppm mass measurement accuracy sufficient for

321

elemental composition assignment34. Molecular formulae can be grouped into

322

heteroatom classes (e.g., nitrogen, sulfur, oxygen) based on relative abundance to

323

elucidate global compositional trends that occurred field samples compared to parent

324

MWO. Figure 3 shows the heteroatom class distribution for species >0.5% relative

325

abundance for the MWO and field samples (9 to 48 mos) based on triplicate analysis

326

and normalized to the most abundant peak in each mass spectrum. Compounds

327

containing a single nitrogen atom (N1) correspond to pyrrolic nitrogen in negative-ion

328

ESI, and comprise the most abundant class (~35%) in parent MWO, followed by

329

hydrocarbons (HC,~10%), O1 (~5%) and N1O1 (~5%) as previously reported.27 The N1

330

class decreases to ~4% after 9 mos, and ~1% after 36 mos. Similarly, the hydrocarbon

331

class (HC), which corresponds to five-member ring hydrocarbons (e.g., fluorene)

332

decrease in abundance over time (~5% at 9 mos to ~2% at 41 mos) and are not

333

detected after 43 mos.

334 335


336 337

Increased Abundance of Oxygen Classes in Field Samples. The rapid decline in

338

relative abundance of nonpolar hydrocarbon (HC) and pyrrolic nitrogen (N1) classes

339

(Figure 3) is matched by a dramatic increase in species that contain oxygen.

340

Heteroatom classes that contain one or more oxygen atoms are highlighted in Figure S-

341

3. Field samples contain higher weight percent oxygen than MWO, which could suggest

342

numerous oxygen functionalities (i.e., ketones, aldehydes, carboxylic acids) that create

343

polyfunctional transformation products, as previously reported32. The most abundant

344

class in the 9 mos sample correspond to carboxylic acids (O2) followed by O1, O3 and

345

O4 classes. Compounds with one oxygen (O1) correspond to phenolic compounds, and

346

decrease in relative abundance after 9 mos, with no species detected above 0.5%

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relative abundance after 43 mos. The increase in O2 species (corrected for mass loss

348

relative to C30 hopane), proceeds over 36 months, with an increase of ~3-fold after 9

349

months to a maximum of ~5.5-fold after 36 months, but decreases to ~3-fold after 48

350

months as compared to the parent MWO. Higher order oxygen classes (O2 – O4)

351

increase in abundance concurrent with a decreased abundance of low heteroatom-

352

containing compounds (e.g., hydrocarbons, N1 and O1) between 9 and 36 mos,59 and

353

corresponds to oxidation of O1 compounds (e.g., alcohols, aldehyde intermediates) to

354

form carboxylic acids through biodegradation.31-33 Between 41 and 48 mos, O2 - O3

355

classes decrease and O4 – O6 increase in abundance. This is in accordance with the

356

results revealed by APS separation that filed samples are becoming more acidic over

357

time (Table 1), indicating secondary oxidation of moderately acidic compounds to

358

create compounds that contain one or more carboxylic acids.

359 360

Hydrogen Deficiency (DBE) versus Carbon Number for Acidic Species in Field

361

Samples. Graphical images of hydrogen deficiency displayed as double bond

362

equivalents (DBE, the number of rings plus double bonds to carbon, calculated from

363

elemental composition CcHhNnOoSs) versus carbon number allow rapid visualization of

364

compositional changes between samples for all members of a heteroatom class

365

simultaneously.60 Figure 4 shows isoabundance-contoured plots of DBE versus carbon

366

number for O1 – O5 classes derived from negative-ESI FT-ICR MS of parent MWO and

367

field samples collected at 9 and 48 mos. Compounds that contain one oxygen atom (O1)

368

correspond to phenolic compounds and decrease in abundance after 9 mos (Figure S-

369

3). Within the O2 and O3 classes, a decrease of ~7 DBE occurs across a similar carbon

370

number range (C20 – C70), and indicates oxidation of aliphatic chains to form carboxylic

371

acids that results in the formation of low DBE compounds not observed in parent MWO.

372

Between 9 and 31 mos, the DBE distribution decreases by 1-2 DBE, and compounds

373

with fewer than 3 oxygen atoms (0.5% relative abundance) for moderately and heavily oiled sites collected at 9, 41 and

405

48 mos. The relative abundance of O2 species in moderately after 9 mos nearly doubles

406

compared to heavily oiled sites from the same time point, with the O2 class at 12%

407

(heavily oiled) to 26% (moderately oiled), concurrent with an increased abundance of

408

higher order oxygen species (O3-O6). After 41 mos, the relative abundance of O2 14


Page 15 of 28


409

compounds in moderately oiled sediments was nearly 30% compared to 20% in heavy

410

contamination. Increased oil contamination decreases microbial activity; therefore,

411

biodegradation occurs more rapidly at moderately oiled sites,62 in agreement with FT-

412

ICR MS results. The materials extracted from the homogenized composites collected

413

from non-oiled reference sites shown in Figure 1 (7 sites) resemble typical natural

414

organic matter (Figure S-5) and provide a background to assess oil contamination.63, 64

415 416

This study represents the first temporal characterization of MWO transformation

417

products at the molecular level. Here, we identify persistent MWO transformation

418

products and catalogue compositional changes that occur to parent MWO in Barataria

419

Bay saltmarsh sediments up to 4 years after the Deepwater Horizon oil spill. Highly

420

polar, acidic oxygenated transformation products derived from biodegradation of

421

Macondo Well oil in coastal salt marshes span a wide range of chemical functionalities,

422

and remain environmentally persistent. The increased abundance of highly polar

423

compounds of low volatility is ideally suited for FT-ICR MS can address the complexity

424

of these highly polar, multifunctional oxidized transformation products at the molecular

425

level. Compositional images of DBE versus carbon number indicate that degradation

426

processes convert nonpolar, saturated compounds into highly polar, carboxylic acid

427

compounds that appear over time, and subsequent oxidation converts lower order

428

oxygen compounds (O1-O3) to higher order oxygen compounds (O4-O6) after 36 mos.

429

Bulk fractionation on aminopropyl silica attributes the increased oxygen content

430

obtained from elemental analysis of field samples to an increase of moderately acidic

431

and carboxylic acid moieties over time. Van Krevelen diagrams indicate that initial

432

oxidation during the first 9 mos was non-selective across a wide range of O:C ratios,

433

and shifts aromatic hydrocarbon degradation after 41 mos. Oil weathering pattern

434

revealed by GC×GC-FID analysis and FT-ICR MS indicate both photo-oxidation and

435

biodegradation contribute to the molecular modification of weathered oil in surface

436

layers of saltmarsh sediments. Moderately oiled sites undergo rapid microbial

437

degradation compared to the heavily oiled sites, and indicate that heavy oil

438

contamination hinders microbial activity.

15



Page 16 of 28

439

■Future Work

440

Sediment samples in this study were split in half and preserved for microbial analysis at

441

Louisiana State University. The chemical data presented here will be correlated with the

442

soil microbial community structure and function to provide molecular level insight on

443

how the oil contamination perturbed the indigenous microbial community, and how the

444

microbes responded to the perturbation. In addition, future studies will apply

445

methodologies to Deepwater Horizon oil residues deposited in coastal marshes, buried

446

in tidal beach sediments, and washed ashore as aggregated “tar balls” to further probe

447

the chemical diversity of oxygen compounds formed through MWO degradation.

448

Microcosm studies will also be compared to “real world” samples to disentangle biotic

449

and abiotic modification and the long-term fate of MWO.

450

■ASSOCIATED CONTENT

451

Supporting Information.

452

Additional methods, figures and tables, as noted in the text, are provided. This material

453

is available free of charge via the Internet at http://pubs.acs.org.

454

■ACKNOWLEDGEMENTS

455 456 457 458 459 460 461 462

Work supported by NSF Division of Materials Research through DMR-11-57490, The Gulf of Mexico Research Initiative to the Deep-C Consortium and to Louisiana State University through Ocean Leadership subaward SA 13-30/GoMRI-013, and the State of Florida. The authors thank Nathan K. Kaiser, John P. Quinn, and Greg T. Blakney for their continued assistance with instrumental maintenance and data analysis, Jacqueline M. Jarvis and Rebecca L. Beasley for technical assistance, as well as Alan G. Marshall, Steven M. Rowland and David C. Podgorski for helpful discussions.

16


Page 17 of 28


463

■References

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29. McKenna, A. M.; Williams, J. T.; Putman, J. C.; Aeppli, C.; Reddy, C. M.; Valentine, D. L.; Lemkau, K. L.; Kellerman, M. Y.; Savory, J. J.; Kaiser, N. K.; Marshall, A. G.; Rodgers, R. P., Unprecedented ultrahigh resolution FT-ICR mass spectrometry and parts-per-billion mass accuracy enable direct characterization of nickel and vanadyl porphyrins in petroleum from natural seeps. Energy Fuels 2014, 28, 2454-2464. 30. Frysinger, G. S.; Gaines, R. B.; Xu, L.; Reddy, C. M., Resolving the unresolved complex mixture in petroleum-contaminated sediments. Environ. Sci. Techn. 2003, 37, (8), 1653-1662. 31. 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, (7), 3760-3767. 32. Ruddy, B. M.; Huettel, M.; Kostka, J. E.; Lobodin, V. V.; Bythell, B. J.; McKenna, A. M.; Aeppli, C.; Reddy, C. M.; Nelson, R. K.; Marshall, A. G., Targeted petroleomics: analytical investigation of Macondo well oil oxidation products from Pensacola Beach. Energy Fuels 2014, 28, (6), 4043-4050. 33. Corilo, Y. E.; Podgorski, D. C.; McKenna, A. M.; Lemkau, K. L.; Reddy, C. M.; Marshall, A. G.; Rodgers, R. P., Oil spill source identification by principal component analysis of electrospray ionization Fourier transform ion cyclotron resonance mass spectra. Anal. Chem. 2013, 85, (19), 9064-9069. 34. Rodgers, R. P.; Schaub, T. M.; Marshall, A. G., Petroleomics: MS Returns to Its Roots. Anal. Chem. 2005, 77, (1), 20 A-27 A. 35. Rodgers, R. P.; Blumer, E. N.; Freitas, M. A.; Marshall, A. G., Jet Fuel Chemical Composition, Weathering, and Identification as a Contaminant at a Remediation Site, Determined by Fourier Transform Ion Cyclotron Resonance Mass Spectrometry. Anal. Chem. 1999, 71, 5171-5176. 36. Hughey, C. A.; Minardi, C. S.; Galasso-Roth, S. A.; B., P. G.; Mapolelo, M. M.; Rodgers, R. P.; Marshall, A. G.; Ruderman, D. L., Napthenic acids as indicators of crude oil biodegradation in soil based on semi-quantitative electrospray ionization Fourier transform ion cyclotron resonance mass spectrometry. Rapid Commun. Mass Spectrom. 2008, 22, 3968-3976. 37. Rodgers, R. P.; Blumer, E. N.; Freitas, M. A.; Marshall, A. G., Complete compositional monitoring of the weathering of transportation fuels based on elemental compositions from Fourier transform ion cyclotron resonance mass spectrometry. Environ. Sci. Technol. 2000, 34, 1671-1678. 38. Lemkau, K. L.; Peacock, E. E.; Nelson, R. K.; Ventura, G. T.; Kovecses, J. L.; Reddy, C. M., The M/V Cosco Busan spill: Source identification. Mar. Pollut. Bull. 2010, 60, (11), 2123-2129. 39. Lin, Q.; Mendelssohn, I. A., Impacts and recovery of the Deepwater Horizon oil spill on vegetation structure and function of coastal salt marshes in the northern Gulf of Mexico. Environ. Sci. Technol. 2012, 46, (7), 3737-43. 40. Michel, J.; Owens, E. H.; Zengel, S.; Graham, A.; Nixon, Z.; Allard, T.; Holton, W.; Reimer, P. D.; Lamarche, A.; White, M.; Rutherford, N.; Childs, C.; Mauseth, G.; Challenger, G.; Taylor, E., Extent and degree of shoreline oiling: Deepwater Horizon oil spill, Gulf of Mexico, USA. PLoS One 2013, 8, (6), e65087. 41. ASTM D5369-93(2008)e1, Standard Practice for Extraction of Solid Waste Samples for Chemical Analysis Using Soxhlet Extraction. In ASTM International: West Conshohocken, PA, 2008.

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42. Aeppli, C.; Nelson, R. K.; Radović, J. R.; Carmichael, C. A.; Valentine, D. L.; Reddy, C. M., Recalcitrance and degradation of petroleum biomarkers upon abiotic and biotic natural weathering of Deepwater Horizon oil. Environ. Sci. Technol. 2014, 48, (12), 6726-6734. 43. Prince, R. C.; Elmendorf, D. L.; Lute, J. R.; Hsu, C. S.; Haith, C. E.; Senius, J. D.; Dechert, G. J.; Douglas, G. S.; Butler, E. L., 17α(H)-21β(H)-hopane as a conserved internal marker for estimating the biodegradation of crude oil. Environ. Sci. Technol. 1994, 28, (1), 142-145. 44. Venosa, A.; Suidan, M.; King, D.; Wrenn, B., Use of hopane as a conservative biomarker for monitoring the bioremediation effectiveness of crude oil contaminating a sandy beach. J. Ind. Microbiol. Biotechnol. 1997, 18, (2-3), 131-139. 45. Fingas, M., Handbook of Oil Spill Science and Technology. John Wiley & Sons: 2014. 46. Prince, R.C.; Garrett, R.M.; Bare, R.E.; Grossman, M.J.; Townsend, T.; Suflita, J.M.; Lee, K.; Owens, E.H.; Sergy, G.A.; Braddock, J.F., The roles of photooxidation and biodegradation in long-term weathering of crude and heavy fuel oils. Spill Science & Technology Bulletin 2003, 8, (2), 145-156. 47. Frank, R.A.; Kavanagh, R.; Kent Burnison, B.; Arsenault, G.; Headley, J.V.; Peru, K.M.; Van Der Kraak, G.; Solomon, K.R., Toxicity assessment of collected fractions from an extracted naphthenic acid mixture. Chemosphere 2008, 72, (9), 1309-1314. 48. Leung, S.S.C.; MacKinnon, M.D.; Smith, R. E., Aquatic reclamation in the Athabasca, Canada, oil sands: naphthenate and salt effects on phytoplankton communities. Environ. Toxicol. Chem. 2001, 20, (7), 1532-1543. 49. Frank, R. A.; Fischer, K.; Kavanagh, R.; Burnison, B. K.; Arsenault, G.; Headley, J. V.; Peru, K. M.; Kraak, G. V. D.; Solomon, K. R., Effect of Carboxylic Acid Content on the Acute Toxicity of Oil Sands Naphthenic Acids. Environ. Sci. Technol. 2008, 43, (2), 266-271. 50. Kamaluddin, M.; Zwiazek, J. J., Naphthenic acids inhibit root water transport, gas exchange and leaf growth in aspen (Populus tremuloides) seedlings. Tree Physiol. 2002, 22, (17), 12651270. 51. Young, R.; Orr, E.; Goss, G.; Fedorak, P., Detection of naphthenic acids in fish exposed to commercial naphthenic acids and oil sands process-affected water. Chemosphere 2007, 68, (3), 518-527. 52. Peters, L.E.; MacKinnon, M.; Van Meer, T.; van den Heuvel, M. R.; Dixon, D., Effects of oil sands process-affected waters and naphthenic acids on yellow perch Perca flavescens and Japanese medaka embryonic development. Chemosphere 2007, 67, (11), 2177-2183. 53. Rogers, V.V.; Wickstrom, M.; Liber, K.; MacKinnon, M.D., Acute and subchronic mammalian toxicity of naphthenic acids from oil sands tailings. Toxicol. Sci. 2002, 66, (2), 347355. 54. Dokholyan, B.; Magomedov, A., The effect of sodium naphthenate on the viability and physiological and biochemical indices of fish. Voprosy Ikhtiologii 1984, 23, (6), 1013-1019. 55. Stanford, L.A.; Kim, S.; Klein, G.C.; Smith, D.F.; Rodgers, R.P.; Marshall, A.G., Identification of Water-Soluble Heavy Crude Oil Organics. Acidic and Basic NSO Compounds in Fresh Water and Sea Water by Electrospray Ionization Fourier Transform Ion Cyclotron Resonance Mass Spectrometry. Environ. Sci. Technol. 2007, 41, 2696-2702. 56. Rowland, S. M.; Robbins, W. K.; Corilo, Y. E.; Marshall, A. G.; Rodgers, R. P., Solid-Phase Extraction Fractionation To Extend the Characterization of Naphthenic Acids in Crude Oil by Electrospray Ionization Fourier Transform Ion Cyclotron Resonance Mass Spectrometry. Energy Fuels 2014, 28, (8), 5043-5048.

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57. 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, (16), 6709-6715. 58. Hughey, C. A.; Rodgers, R.P.; Marshall, A.G.; Qian, K.; Robbins, W.K., Identification of acidic NSO compounds in crude oils of different geochemical origins by negative ion electrospray Fourier transform ion cyclotron resonance mass spectrometry. Org. Geochem. 2002, 33, (7), 743-759. 59. Mapolelo, M.M.; Rodgers, R.P.; Blakney, G. T.; Yen, A. T.; Asomaning, S.; Marshall, A. G., Characterization of naphthenic acids in crude oils and naphthenates by electrospray ionization FT-ICR mass spectrometry. Int. J. Mass Spectrom. 2011, 300, (2-3), 149-157. 60. McLafferty, F.W.; Turecek, F., Interpretation of Mass Spectra. 4th ed. ed.; University Science Books: Mill Valley, CA, 1993; p 371. 61. Kim, S.; Kramer, R.W.; Hatcher, P.G., Graphical method for analysis of ultrahigh-resolution broadband mass spectra of natural organic matter, the van Krevelen diagram. Anal. Chem. 2003, 75, (20), 5336-5344. 62. Leahy, J.G.; Colwell, R.R., Microbial degradation of hydrocarbons in the environment. Microbiological reviews 1990, 54, (3), 305-315. 63. Kujawinski, E.B.; Freitas, M.A.; Zang, X.; Hatcher, P.G.; Green-Church, K.B.; Jones, R.B., The application of electrospray ionization mass spectrometry (ESI MS) to the structural characterization of natural organic matter. Org. Geochem. 2002, 33, (3), 171-180. 64. Schmidt, F.; Elvert, M.; Koch, B. P.; Witt, M.; Hinrichs, K.-U., Molecular characterization of dissolved organic matter in pore water of continental shelf sediments. Geochim. Cosmochim. Acta 2009, 73, (11), 3337-3358. FIGURE LEGENDS Figure 1. Map of northern Barataria Basin of Louisiana, USA, approximately 8 km x 5 km (coordinates N 29.44060° - 29.47459°, W 89.88492° - 89.94647°), with 21 sampling locations (seven each that received heavy oiling (Sites 1-7), moderate oiling (sites 814), and no observed oiling or reference (sites 15-21), based on the Shoreline Cleanup Assessment Technique (SCAT) Program (28 April 2010), field observations, and total petroleum hydrocarbon measurements. No cleanup events at the sampling sites were noted during this period. Figure 2. Calculated losses of total petroleum hydrocarbon and chrysenes relative to MWO based on the conservation of hopane for field samples extracted from 9, 24, 36 and 48 months after the DWH spill (total, eq1; Chrysene eq2;). The C1, C2, C3 indicates the number of alky carbons on the parent molecule. Figure 3. Heteroatom class distribution of major species (>1% relative abundance) derived from negative ESI FT-ICR mass spectra of parent MWO Macondo well oil and oil contaminants over 48 mos post-spill with a TMAH-modified solvent system. Bars indicate standard errors (N = 3) Figure 4. Negative ESI-derived isoabundance-contoured plots of double bond equivalents (DBE), versus carbon number for the O1 – O5 classes for parent MWO and

21



690 691 692 693 694 695 696 697 698

Page 22 of 28

field samples collected from 9 to 48 mos post-spill. Each compositional image is normalized to the most abundant species within that heteroatom class for each mass spectrum. Relative abundance weighted average carbon numbers and DBE values for each sample are listed in Table 1. Figure 5. Van Krevelen diagrams for the O1 –O8 classes of the acidic polar species in the parent MWO and field samples collected at heavily contaminate sites analyzed by negative ion ESI FT-ICR MS.

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Page 23 of 28


Bay Chene Fleur

Figure 1

Wilkinson Bay 21

17

18

20 19 16 15

10

11

14 12 13

7

5

8 1

Heavily Oiled

9 2

Moderately Oiled Reference

4

6

Bay Jimmy

3

Barataria ACS ParagonBay Plus Environment 1Km


% Loss Relative to MWO

9 mos 90

24 mos

80

36 mos

Page 24 of 2 28 Figure

48 mos

70 60 50 40 30 20 10 0


TPH

Chrysene

C1-Chrysenes

C2-Chrysenes C3-Chrysenes

Page 25 of 28

Figure 3


a)

40

MWO

18 mos

30

24 mos 31 mos 36 mos

20

41 mos 43 mos

O4S1

O2S1

O6

O5

O4

O3

O2

O1

N1O4

N1O3

N1O2

N1O1

N1

0

O3S1

48 mos

10

HC

% Relative Abundance

9 mos

MWO

b)

9 mos

25 % Relative Abundance

18 mos 24 mos

20

31 mos 36 mos

15

41 mos 43 mos

10

48 mos

5 0

O1

O2

O3

O4


Heteroatom Class

O5

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Figure 4 30

MWO

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24 mos

31 mos

36 mos

41 mos

43 mos

No Species detected ≥ 0.5%


20 10

Page 26 of 28

48 mos

O1

30 20

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30 20

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O4


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20 40 60 Relative Abundance (% total)

20 80 20

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60

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20

40

60 80 20 40 60 80 20 ACS Paragon Plus Environment

Carbon Number

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80 20

40

60

80 20

40

60

80 20

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Figure 5 28 Page 27 of


2.0

(a). MWO

(e). 36 mos

(b). 9 mos

(f). 41 mos

(c). 24 mos

(g). 43 mos

(d). 31 mos

(h). 48 mos

1.5 1.0 0.5 0.0 2.0 1.5 1.0 0.5

H/C

0.0 2.0 1.5 1.0 0.5 0.0 2.0 1.5 1.0 0.5 0.0 0.0

0.1

0.2

0.3

0.4

0.0

O/C Relative Abundance (% total) ACS Paragon Plus Environment

0.1

0.2

0.3

0.4

25

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Environmental Science & Technology Page 289 mos of 28

% Relative Abundance

18 mos

20


15


10 5

ACS Paragon Plus Environment 0

O1

O2

O3

O4

Heteroatom Class

O5

O6

4 Years after the Deepwater Horizon Spill ... - ACS Publications

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