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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
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higher-order oxygenated compounds (O4-O6) not detected in the parent MWO, increase
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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
36
Deepwater Horizon derived oil contamination deposited in a saltmarsh ecosystem from
37
9 to 48 mos post-spill, and identify highly oxidized Macondo well oil compounds that are
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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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Environmental Science & Technology
■ 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
49
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
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Recent studies address the toxicological impact of weathered oil contaminants not
71
detected by GC-based techniques4,
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techniques to identify molecular transformations that occur to petroleum hydrocarbons
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after environmental release.
28
and highlight the need for advanced analytical
74
Recent GC-based reports suggest that the level of hydrocarbons extracted from
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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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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
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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
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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
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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
114
to pre-spill oil, and we identify recalcitrant oxygen-containing compounds derived from
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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.
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Moderately oiled sites sampled at 9, 41 and 48 mos from seven moderately oiled
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locations, and reference sites collected and homogenized from seven reference
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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
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equal weight of sodium sulfate drying agent, loaded into a 30 x 100 mm cellulose
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thimble, and Soxhlet extracted with dichloromethane for 4 h, desolvated under dry
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nitrogen (N2) and weighed.41
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Bulk Elemental Analysis. Complete experimental methods can be found in the
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supporting material. Briefly, elemental analysis was performed on MWO and sediment
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extracts collected from heavily oiled sites at 9, 18, 24, 31, 36, 41, and 48 mos post spill
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on a Thermo Finnigan Elemental Analyzer (FLASH EA 112, San Jose, CA, USA). Due
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to sample limitations, moderately oiled and reference sites were not analyzed. Detailed
143
description can be found in Supporting Information.
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GC×GC-MS and GC×GC-FID. Comprehensive two-dimensional gas chromatagraphy
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(GC×GC) and
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collected from heavily oiled sites at 9, 18, 24, 31, 36, 41, and 48 mos post spill. Each
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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
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peak area of individual compound to that of 17α(H),21β(H)-hopane (herein refered to as
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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
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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
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toluene to make a stock solution (1 mg/ mL) that was further diluted with equal parts
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(vol: vol) methanol spiked with 2 % (by volume) formic acid for positive ion electrospray
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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
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preparation method, ionization source conditions, and detailed FT-ICR MS conditions
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can be found in Supporting Information.
elemental analysis were performed on MWO and sediment extracts
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■ RESULTS AND DISCUSSION
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Extraction of MWO from Saltmarsh Sediments. Table S-1 shows the total extracted
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mass of oil isolated from 20 g each of heavily oiled, moderately oiled, and reference
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sites.
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sediments occurs between 9 mos (26 wt%) and 48 mos (2.4 wt%), indicating oil removal
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from marshes with time. This suggests the majority of MWO deposition occurred in the
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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
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after 9 mos (0.470 g), compared to heavily oiled sites after 48 mos (0.482 g). This
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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
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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
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the DWH spill, where the removal of n-alkanes, isoprenoids, and two-ring PAHs were
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reported in beach samples collected within 18 mos of the spill.19,
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sediment extracts indicate the presence of weathered oil components, but detection is
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limited to compounds that are volatile below ~400 °C.27, 30
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Oil Depletion Estimated by GC×GC-FID Analysis. Each GC×GC-FID image was
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base-plane subtracted and normalized to the conserved biomarker C30-hopane43 to
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estimate degradation in sediment extracts.42, 44, 45 Figure 2 shows the calculated loss of
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total petroleum hydrocarbons (TPH) and chrysenes (C1-C3) normalized to C30 hopane
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for 9, 24, 36 and 48 mos. After 9 mos, ~45% of the parent MWO is removed, and after
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48 mos, ~63% of the TPHs have been removed. The percentage of total oil and
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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
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Between 36 and 48 mos, no significant weathering loss is observed, which indicates
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either oil is continually depleted up to 36 mos and then slows down, or C30-hopane
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begins to degrade with time. The long term fate of heavily degraded oil relies on reliable
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fingerprinting methods when the biomarker fidelity is questionable, which is the subject
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of this study.
209
For chrysenes, the extent of loss increases with degree of alkylation. Chrysene is
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depleted by 58% after 9 mos, but only 64% after 48 mos. However, ~88% of C3-
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chrysene is lost at 48 mos (Figure 2). The loss of alkyl-substituted chrysenes prior to
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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
(Insert Figure 2 here)
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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
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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
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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
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increases to 4.7% by weight after 24 mos, but remains relatively constant across the
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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
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oxidized transformation products that persist in the environment.19 Therefore, we focus
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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
235
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
238
inherent in crude oil have known toxicity to marine bacteria,47 phytoplankton,48
239
zooplankton,49 plants,50 fish,51, 52 and mammals53 at low concentrations (2.5 – 5 mg L-
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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
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(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
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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
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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
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Since APS
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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
(Insert Figure 3 here)
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
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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.
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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.
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■References
464 465 466 467 468 469 470 471 472 473 474 475 476 477 478 479 480 481 482 483 484 485 486 487 488 489 490 491 492 493 494 495 496 497 498 499 500 501 502 503 504 505 506 507
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16. Valentine, D. L.; Fisher, G. B.; Bagby, S. C.; Nelson, R. K.; Reddy, C. M.; Sylva, S. P.; Woo, M. A., Fallout plume of submerged oil from Deepwater Horizon. Proc. Natl. Acad. Sci. U. S. A. 2014, 111, (45), 15906-15911. 17. Ryerson, T. B.; Camilli, R.; Kessler, J. D.; Kujawinski, E. B.; Reddy, C. M.; Valentine, D. L.; Atlas, E.; Blake, D. R.; de Gouw, J.; Meinardi, S.; Parrish, D. D.; Peischle, J.; Seewald, J. S.; Warneke, C., Chemical Data Quantify Deepwater Horizon hydrocarbon flow rate and environmental distribution. Proc. Natl. Acad. Sci. U. S. A. 2012, 109, (50), 20246-20253. 18. White, H. K.; Hsing, P. Y.; Cho, W.; Shank, T. M.; Cordes, E. E.; Quattrini, A. M.; Nelson, R. K.; Camilli, R.; Demopoulos, A. W.; German, C. R.; Brooks, J. M.; Roberts, H. H.; Shedd, W.; Reddy, C. M.; Fisher, C. R., Impact of the Deepwater Horizon oil spill on a deep-water coral community in the Gulf of Mexico. Proc. Natl. Acad. Sci. U. S. A. 2012, 109, (50), 20303-20308. 19. 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, (16), 8799-8807. 20. Hall, G. J.; Frysinger, G. S.; Aeppli, C.; Carmichael, C. A.; Gros, J.; Lemkau, K. L.; Nelson, R. K.; Reddy, C. M., Oxygenated weathering products of Deepwater Horizon oil come from surprising precursors. Mar. Pollut. Bull. 2013, 75, (1-2), 140-149. 21. Turner, R. E.; Overton, E. B.; Meyer, B. M.; Miles, M. S.; McClenachan, G.; Hooper-Bui, L.; Engel, A. S.; Swenson, E. M.; Lee, J. M.; Milan, C. S.; Gao, H., Distribution and recovery trajectory of Macondo (Mississippi Canyon 252) oil in Louisiana coastal wetlands. Mar. Pollut. Bull. 2014, 87, (1–2), 57-67. 22. Carmichael, C. A.; Arey, J. S.; Graham, W. M.; Linn, L. J.; Lemkau, K. L.; Nelson, R. K.; Reddy, C. M., Floating oil-covered debris from Deepwater Horizon: identification and application. Environ. Res. Lett 2012, 7, 015301. 23. Lewan, M.; Warden, A.; Dias, R.; Lowry, Z.; Hannah, T.; Lillis, P.; Kokaly, R.; Hoefen, T.; Swayze, G.; Mills, C., Asphaltene content and composition as a measure of Deepwater Horizon oil spill losses within the first 80days. Org. Geochem. 2014, 75, 54-60. 24. 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), 1628-1637. 25. Looper, J. K.; Cotto, A.; Kim, B. Y.; Lee, M. K.; Liles, M. R.; Ni Chadhain, S. M.; Son, A., Microbial community analysis of Deepwater Horizon oil-spill impacted sites along the Gulf coast using functional and phylogenetic markers. Env. Sci. Process. Impact. 2013, 15, (11), 2068-2079. 26. Atlas, R. M.; Stoeckel, D. M.; Faith, S. A.; Minard-Smith, A.; Thorn, J. R.; Benotti, M. J., Oil Biodegradation and Oil-degrading Microbial Populations in Marsh Sediments Impacted by Oil from the Deepwater Horizon Well Blowout. Environ. Sci. Technol. 2015, 49, (14), 83568366. 27. McKenna, A. M.; Nelson, R. K.; Reddy, C. M.; Savory, J. J.; Kaiser, N. K.; Fitzsimmons, J. E.; Marshall, A. G.; Rodgers, R. P., Expansion of the analytical window for oil spill characterization by ultrahigh resolution mass spectrometry: Beyond gas chromatography. Environ. Sci. Technol. 2013, 47, (13), 7530-7539. 28. Incardona, J. P.; Vines, C. A.; Anulacion, B. F.; Baldwin, D. H.; Day, H. L.; French, B. L.; Labenia, J. S.; Linbo, T. L.; Myers, M. S.; Olson, O. P., Unexpectedly high mortality in Pacific herring embryos exposed to the 2007 Cosco Busan oil spill in San Francisco Bay. Proc. Natl. Acad. Sci. U. S. A. 2012, 109, (2), E51-E58.
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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
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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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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
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6
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% Loss Relative to MWO
9 mos 90
24 mos
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Figure 3
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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
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Figure 4 30
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No Species detected ≥ 0.5%
No Species detected ≥ 0.5%
20 10
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48 mos
O1
30 20
O2
10
DBE
30 20
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10 30 20 10
No Species detected ≥0.5%
O4
No Species detected ≥ 0.5%
O5
30 20 10 0
20 40 60 Relative Abundance (% total)
20 80 20
40
60
80 20
40
60
80
20
40
60 80 20 40 60 80 20 ACS Paragon Plus Environment
Carbon Number
40
60
80 20
40
60
80 20
40
60
80 20
40
60
80
Figure 5 28 Page 27 of
Environmental Science & Technology
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
MWO
Environmental Science & Technology Page 289 mos of 28
% Relative Abundance
18 mos
20
24 mos 31 mos 36 mos
15
41 mos 43 mos 48 mos
10 5
ACS Paragon Plus Environment 0
O1
O2
O3
O4
Heteroatom Class
O5
O6