Significance The Deepwater Horizon event led to an unprecedented discharge of ∼4.1 million barrels of oil to the Gulf of Mexico. The deposition of ∼4–31% of this oil to the seafloor has been quantified previously on a bulk basis. In this work, we assess the extent of degradation over 4 y postspill for each of 125 petroleum hydrocarbons that contaminated the seafloor. As expected, chemically simpler compounds broke down more quickly than complex compounds, but degradation rates also depended on environmental context: Breakdown often was faster before seafloor deposition than after and for oil trapped in small droplets than for oil in large particles. These results provide a basis to predict the long-term fate of seafloor oil.

Abstract The 2010 Deepwater Horizon disaster introduced an unprecedented discharge of oil into the deep Gulf of Mexico. Considerable uncertainty has persisted regarding the oil’s fate and effects in the deep ocean. In this work we assess the compound-specific rates of biodegradation for 125 aliphatic, aromatic, and biomarker petroleum hydrocarbons that settled to the deep ocean floor following release from the damaged Macondo Well. Based on a dataset comprising measurements of up to 168 distinct hydrocarbon analytes in 2,980 sediment samples collected within 4 y of the spill, we develop a Macondo oil “fingerprint” and conservatively identify a subset of 312 surficial samples consistent with contamination by Macondo oil. Three trends emerge from analysis of the biodegradation rates of 125 individual hydrocarbons in these samples. First, molecular structure served to modulate biodegradation in a predictable fashion, with the simplest structures subject to fastest loss, indicating that biodegradation in the deep ocean progresses similarly to other environments. Second, for many alkanes and polycyclic aromatic hydrocarbons biodegradation occurred in two distinct phases, consistent with rapid loss while oil particles remained suspended followed by slow loss after deposition to the seafloor. Third, the extent of biodegradation for any given sample was influenced by the hydrocarbon content, leading to substantially greater hydrocarbon persistence among the more highly contaminated samples. In addition, under some conditions we find strong evidence for extensive degradation of numerous petroleum biomarkers, notably including the native internal standard 17α(H),21β(H)-hopane, commonly used to calculate the extent of oil weathering.

On 20 April 2010, a blowout from the Macondo Well in the Gulf of Mexico (GOM) caused an explosion on the Deepwater Horizon (DWH) mobile offshore drilling unit that ultimately led to its sinking and the deaths of 11 crewmembers. From the time of the blowout until the well was capped on 15 July 2010, petroleum fluids flowed continuously from the Macondo Well, with environmental emission estimates of 4.1 million barrels of oil and 1.7 × 1011 g natural gas (1⇓–3). The spill was noteworthy not only for its volume but also for its distance offshore and its depth: Oil and gas entered the ocean at a water depth of ∼1,500 m and then partitioned between the deep ocean and the sea surface. This partitioning may have varied over time because of reservoir depressurization and deliberate interventions such as the shearing of the riser pipe and the application of chemical dispersant at the wellhead (4⇓–6). In all, approximately half of the oil ascended to the ocean surface (1, 7), where it was skimmed or flared by response teams, trapped in sinking particles by marine oil snow sedimentation and flocculent accumulation (8, 9), washed ashore, or left exposed to the canonical weathering processes of evaporation, biodegradation, and photooxidation (7, 10). The rest remained in the deep ocean. Because the DWH event was the first major spill to occur in the deep ocean, the processes determining the fate of this oil were largely unknown.

In the wake of the spill, water-column data shed light on the physical partitioning of the submerged oil. Many compounds containing <10 carbon atoms (e.g., natural gas, benzene and its alkylated analogs, cycloalkanes, and branched alkanes) dissolved in seawater to form deep, aqueous plumes (2, 6, 11⇓⇓⇓⇓–16); in the first weeks of the spill, dissolution is also expected to have influenced the distribution of two- and three-ring polycyclic aromatic hydrocarbons (PAHs), particularly naphthalene and its alkylated analogs, and to a lesser extent fluorene, phenanthrene, and anthracene and their alkylated analogs. Hydrocarbons that remained undissolved became trapped in the deep ocean in a suspension of small (less than ∼100 μm) droplets of liquid oil that lacked the buoyant force to rise through the water column. These droplets remained concentrated close to the well’s coordinates (2, 11, 12, 15), but modeling suggests that droplet size drove further vertical partitioning, with droplets >50 µm mixing upwards by August 2010 and smaller droplets remaining suspended in the deep ocean (7, 17, 18). Some suspended oil was eventually deposited to the seafloor, likely via oil–mineral aggregates or microbial flocs (8, 19, 20), with intense contamination within ∼5 km of the well (21⇓⇓⇓⇓–26). Surficial sediments near the well were found to carry >1,000-fold–elevated concentrations of dioctyl sodium sulfosuccinate (4), an active ingredient of the chemical dispersant applied at the wellhead, and to exhibit a radiocarbon deficit consistent with oil deposition (27). We recently identified a 3,200-km2 deposition footprint stretching southwest from the wellhead (28). This footprint, marked by substantial heterogeneity in the oil mass of deposited particles, was estimated to account for ∼4–31% of the submerged oil (28).

Superimposed on these changes in physical distribution, hydrocarbons trapped in the deep ocean were subject to biologically mediated loss processes (i.e., biodegradation) (12, 16, 18, 29⇓–31). For sparingly soluble hydrocarbons, biodegradation is expected to serve as the primary cause of weathering in the deep ocean because other key weathering processes (e.g., evaporation, photooxidation) depend on atmospheric and solar exposure. Although hydrocarbon recalcitrance to biodegradation is expected to scale roughly with molecular mass and steric complexity (32), the rates at which specific hydrocarbons are metabolized vary based on myriad environmental variables: temperature, salinity, pressure, oxygen concentration, pH, solar exposure, availability of nutrients and other sources of organic matter (33), water availability, access to substrate, solid-phase interactions, competition, predation, and inhibition (34). Although early reports addressed the degradation of some low- to moderate-molecular-mass compounds in the water column (12, 14, 16), the degradation rates of the petroleum hydrocarbons constituting Macondo oil after seafloor deposition are unknown. However, it is these rates, and the factors that control them, that will largely determine the long-term fate and biological impacts of the spill on the GOM seafloor.

In this work we address the fate of oil that was deposited on the floor of the deep ocean following the DWH event. We use publicly available data from the Natural Resource Damage Assessment (NRDA) process to identify samples contaminated by oil from the Macondo Well conservatively and to analyze the rate and extent of biodegradation for 125 hydrocarbon compounds spanning 4 y postspill. Based on the results, we identify key factors that modulated biodegradation, finding that a dependence on the intensity of contamination overlaid the expected trends in chemical structure and complexity.

Discussion Dissimilarity Fingerprinting Advances Deep-Sea Oil Spill Forensics. Although a Macondo fingerprint for use in oily samples has been developed recently (48), the MDI fingerprint developed for this work represents a significant forensic advance for the study of the DWH spill in sediments. Our approach is independently supported by the good spatial agreement found between the deposition footprint as defined by the MDI and the footprint as previously defined by hopane (28) and natural abundance radiocarbon (27) anomalies. The MDI offers an advantage over these methods in its ability to distinguish between seeped and spilled oil in individual samples: Among sediment samples that do not meet our MDI threshold, a distinct and coherent fingerprint emerges at greater distances from the Macondo Well and lower depths in the sediment column, likely representing weathered oil that originated in natural seeps. This sensitivity suggests that comparable dissimilarity approaches may be useful for analysis of future spills. In light of the degradation of biomarkers described above, it is reasonable to ask on what timescale a biomarker-based fingerprint can remain diagnostic. Starting with Macondo oil, we calculated the projected time-course changes in the ratios used to calculate MDI (SI Appendix, Fig. S13). We find that in sediments with low contamination the MDI as described here should remain useful for ∼5.4 y; it should remain useful for ∼10 y in moderately contaminated sediments and for ∼5 y in highly contaminated sediments. Notably, the biomarkers whose loss causes the MDI to drift over time differ across contamination levels: Steranes dominate the loss of discrimination at low contamination levels, hopanes at moderate contamination levels, and triaromatic steranes at high contamination levels (SI Appendix, Fig. S13B). Although the MDI’s useful lifetime might be extended by relaxing the threshold to account for drift or by modifying the chosen set of biomarker ratios (45), these changes would likely come at the cost of increasing false positives. Pseudoreplicates Can Address Uncertainties in Weathering. Although Monte Carlo methods are common in other fields, they have not typically been used in oil-spill assessment. Here, we used ensembles of pseudoreplicates with added noise in the time coordinate to address a major uncertainty in the dataset: For the oiled particle(s) collected in each sediment sample, how much time elapsed between wellhead emission and sample collection? Although many spills are contained far more quickly than the DWH event, no oil spill is without its uncertainties. We can increase our confidence in our analyses of these events and set bounds on the range of possible outcomes by modeling the uncertainties explicitly. Hopane Is Not Always Conserved. For more than 20 y, hopane has been widely used as a conservative internal standard (36, 37) for quantification of oil weathering after spills. Indeed, we have previously treated hopane as conservative and have used the seafloor hopane anomaly as a basis to calculate the corresponding contamination burden as ∼4–31% of the oil from the deep plume (28). The analysis we present here supports the conclusion that hopane does not behave uniformly as a conservative biomarker in Macondo oil deposited to the seafloor but rather undergoes significant biodegradation at low and moderate contamination levels. Two-thirds of the surficial samples identified by the MDI fall into the low-contamination class, and for these samples only 39% of hopane remained at 4 y postexplosion. An additional 19% of samples fall into the moderate-contamination class; in these samples, 64% of hopane remained after 4 y. However, hopane is relatively persistent (95% remaining after 4 y) in the highly contaminated samples, supporting its use a conservative marker in heavily contaminated environments. These results add to other studies (39, 40, 49, 50) that redefine views on hopane’s fidelity and utility as an internal standard. In light of the research community’s crucial public role in assessing the damage wrought by past and future spills, this mounting evidence strongly suggests that best practices are due for revision. Although the use of some internal standard is essential, hopane should not be assumed to be the best choice for timescales of months to years but rather should be assessed for utility on a case-by-case basis. In this spirit, we have updated our previous hopane-based estimate of seafloor oil contamination from the DWH event (28). Working within the same 3,200-km2 study area considered in that study (28), we applied the most robust kriging model identified there [empirical Bayesian kriging (EBK) model EBK-C] to (i) n-C38 concentrations and (ii) projections of original hopane concentration. The resulting interpolated deposition footprints are in good agreement, accounting for, respectively, ∼13.7 and <14.7% of the oil from the deep plume. The comparatively small disparity between these estimates and the previous EBK-C estimate of ∼12% (28) likely results from the freshness of samples used in interpolation (collected ≤1.5 y postexplosion) and from the recalcitrance of hopane in heavily contaminated samples. Multiple Factors Control Biodegradation of Macondo Oil. The contamination-level bins used in the present work were chosen empirically, based on exploratory analysis of the fraction-remaining data. It is noteworthy, then, that these bins correspond neatly to the level of contamination expected from the different particle-size classes suggested by previous modeling work (28). Contamination with <400 ng/g hopane is consistent with the deposition of a single oiled particle from the smallest predicted size class (∼0.024 g oil); contamination with ≥750 ng/g hopane is consistent with the deposition of more than one particle of the larger classes. We observed more scatter in the fraction-remaining data in the 400–750 ng/g hopane bin than in either the <400 ng/g or the ≥750 ng/g hopane bins; this moderate-contamination level can arise either from two or three particles of the smallest size class or from one of the particles in the low tail of the second size class. The observed kinetic heterogeneity therefore might reflect a mixture of light- and heavy-contamination–like behaviors across different samples. Alternatively, particles in this concentration range may represent two populations deposited on the seafloor with different histories. The effect of contamination level on the biodegradation rate reported here is consistent with reports from other environmental settings [e.g., the boulder armoring that protected oil from biodegradation following the Exxon Valdez disaster (51), beach sands (52), and bioremediation studies as reviewed previously (53)]. Notably, however, previous examples of this phenomenon have all involved larger spatial scales and higher concentrations. The contamination effect we observe suggests that a similar phenomenon also operates on the approximately millimeter scale and within oil volumes of ∼0.01–1 mL (28). Contra Hazen et al. (12), and consistent with independent metatranscriptomic evidence (54), we find clear evidence for the expected relationship between chemical size and complexity and biodegradation rate. This relationship is clearest in the aliphatic and aromatic compounds analyzed and is most obscure among the biomarkers. The observed rates of diasterane biodegradation are particularly variable, consistent with previous observations in salt marshes (46). This variability is also consistent with previous observations (45, 47), and the observed concentration dependence provides a framework for interpreting such variable sterane deficits. The robust distinction between the two phases of loss for samples with low and moderate contamination suggests that controls on weathering differed before and after deposition. We hypothesize that this effect arises from a relatively rapid microbial response to freshly suspended oil droplets followed by a marked reduction in microbial metabolism after droplets aggregated and settled to the sea floor, where biodegradation might be limited by insufficient access to a terminal oxidant or nutrients. Among highly contaminated samples, predeposition biodegradation could be limited either by the faster deposition of larger particles, limiting their exposure to in-plume weathering conditions, or by larger particles’ low surface area:volume ratio, limiting bioavailability. In the latter case, particles might spread upon deposition, allowing biodegradation to proceed. Two limitations of the biphasic kinetic model should be emphasized. First, the distribution of deposition times, i.e., of breakpoints between phases, is not known. We chose to fix the breakpoint uniformly at t = 160 d postexplosion because that represents the earliest date from which we have Macondo-contaminated sediment samples. The modal breakpoint could be earlier, and, as noted above, could differ for different particle-size classes. Second, the first phase of degradation is characterized only by its modeled endpoints, i.e., source oil and the earliest sediment samples. Complex kinetics could lurk in the first phase; we can make claims only about the total extent of biodegradation before seafloor deposition, not about the time-dependence of biodegradation in this window. Stout and Payne (25) have recently argued that the predominant signals in DWH sediment chemistry data are distance-related: The farther from the well an oily particle was deposited, the greater is the extent of biodegradation. They hypothesize that biodegradation proceeds more rapidly in suspension than after sedimentation, so that hydrocarbons in oily particles that were carried further (and thus remained in suspension longer) are systematically more degraded than those in particles deposited closer to the wellhead. This model is consistent with our finding that the majority of pseudoreplicates are best fit by a two-phase biodegradation model, with faster degradation before deposition. In light of the variability of currents in the region (29) and the unknown deposition history of oiled particles in different samples, our analysis does not account explicitly for distance from the wellhead; the breakpoint between the first and second phase of biodegradation is treated as constant for all samples. Thus, if a distance signal exists, it should be detectable in the residuals of our fits: Macondo-contaminated samples collected farther from the wellhead should have systematically more negative residuals (i.e., greater degradation than the model predicts, occurring during the longer-than-average time to deposition) than Macondo-contaminated samples collected closer to the wellhead. To check, we examined the relationship between model residuals and distance from the wellhead, limiting the analysis to pseudoreplicates with at least moderate support (ΔBIC ≥2) for the best-fit model. We found a significant negative slope in all contamination bins for aliphatic and aromatic compounds. The more recalcitrant biomarkers show a smaller negative slope at low contamination levels, a negligible negative slope at moderate contamination levels, and a negligible positive slope at high contamination levels (SI Appendix, Fig. S14). This result is consistent with our observation that two-phase kinetics dominate for aliphatic and aromatic compounds but not for biomarkers: The length of time spent in suspension should matter more when the difference between pre- and postdeposition rates is larger. An additional nuance is that the distance effect is weakest whenever predeposition biodegradation is either very fast or very slow. This diminution in distance effect could reflect a Goldilocks effect: For labile compounds in small particles, even those deposited closest to the well remained in suspension for multiple degradation half-lives, whereas for recalcitrant compounds in large particles, even those deposited farthest were in suspension for only one or two. Both cases should damp the distance signal. Implications for Response Efforts in Future Deep Spills. Future spill-response efforts may be informed by two key findings from the present work: first, that biodegradation is much faster in suspension than after deposition for most compounds studied; and second, that contamination level is a key control on degradation rates. These findings suggest that the lasting benthic impact of deep-sea spills may be minimized by measures that drive oil to stay suspended in smaller droplets for longer—an intended mode of action of the 2.9 × 106 L of chemical dispersant applied directly at the wellhead during the spill. While it is not known to what extent dispersant drove oil into microdroplets that biodegraded while remaining suspended in the ocean’s interior, the identification of the dispersant’s active ingredient in the deep ocean intrusion layers (6) and in benthic oil deposits (4) suggests that the dispersant did remain in suspension with the oil. Furthermore, roller-tank experiments with Macondo oil (19) demonstrated that dispersant delayed the formation of marine snow, perhaps through a direct influence on the surface-layer properties of oil particles or an effect on the microbial release of aggregation-promoting exudates. Together with the present findings, these observations suggest that subsea dispersant application contributes to a net acceleration of biodegradation. However, other lines of evidence cloud this picture. A recent study questions the efficacy of the subsea dispersant application in modulating droplet size (55), and the variable impacts of dispersant on biodegradation are at the center of an ongoing debate (56, 57). The effect of dispersant itself on the benthos is not well understood, but components of dispersant have been found to persist in sediments and in fragile deep-sea coral communities on a scale of years (4). Decisions regarding the use of dispersant in future spills thus need to weigh not only endpoint hydrocarbon concentration but also context: The net environmental impact of years-long exposure to high local concentrations of undispersed sediment-bound oil may or may not be more severe than the combined effects of short-term exposure of the deep water column to microdroplets of oil and dispersant and long-term exposure of sediments to their residues.

Conclusions Our compound-specific analysis confirms expected chemical structure trends in biodegradation rates but holds several surprises: First, that biomarkers, including hopane, are subject to substantial biodegradation after deposition; second, that biodegradation patterns differ markedly depending on the extent of contamination; and third, that biodegradation was typically much faster in the short window while oil particles remained suspended than it was subsequently on the deep seafloor. These results provide a basis for predicting the ongoing biodegradation of Macondo oil on the floor of the Gulf of Mexico, inform the ongoing debate about the merits of subsea dispersant use, and argue for caution when using hopane as an internal standard for oil-spill research at long timescales.

Acknowledgments We thank Elizabeth Porta (Alpha Analytical) for useful advice, Deborah French-McCay (Applied Science Associates) for preparation and coordination of NRDA cruises, and the crew and scientists of the 18 NRDA cruises whose sediment samples we analyzed. This work was supported, in part, by National Science Foundation Grants OCE-1333162, OCE-0961725, EAR-0950600, and OCE-1046144 (to D.L.V.) and OCE-1333148 (to C.M.R.) and by Simons Foundation Grant 385324 (to D.L.V.).

Footnotes Author contributions: S.C.B., C.M.R., C.A., and D.L.V. designed research; S.C.B. and G.B.F. performed research; S.C.B., G.B.F., and D.L.V. analyzed data; and S.C.B., C.M.R., C.A., G.B.F., and D.L.V. wrote the paper.

The authors declare no conflict of interest.

This article is a PNAS Direct Submission.

Data deposition: All raw data analyzed in this article are publicly available via the Natural Resource Damage Assessment website (https://dwhdiver.orr.noaa.gov/explore-the-data/). The cleaned and filtered dataset, together with all analysis code used in the paper and a README file describing the use of the code, has been bundled with all necessary R packages to make a functional research compendium. This compendium has been deposited with Figshare, with the DOI 10.6084/m9.figshare.4001262.

This article contains supporting information online at www.pnas.org/lookup/suppl/doi:10.1073/pnas.1610110114/-/DCSupplemental.