Oiled Shorelines Research Articles

Predictive modeling of subsurface shoreline oil encounter probability from the Exxon Valdez oil spill in Prince William Sound, Alaska.

To better understand the distribution of remaining lingering subsurface oil residues from the Exxon Valdez oil spill (EVOS) along the shorelines of Prince William Sound (PWS), AK, we revised previous modeling efforts to allow spatially explicit predictions of the distribution of subsurface oil. We used a set of pooled field data and predictor variables stored as Geographic Information Systems (GIS) data to generate calibrated boosted tree models predicting the encounter probability of different categories of subsurface oil. The models demonstrated excellent predictive performance as evaluated by cross-validated performance statistics. While the average encounter probabilities at most shoreline locations are low across western PWS, clusters of shoreline locations with elevated encounter probabilities remain in the northern parts of the PWS, as well as more isolated locations. These results can be applied to estimate the location and amount of remaining oil, evaluate potential ongoing impacts, and guide remediation. This is the first application of quantitative machine-learning based modeling techniques in estimating the likelihood of ongoing, long-term shoreline oil persistence after a major oil spill.

Improving environmental assessments by integrating Species Sensitivity Distributions into environmental modeling: Examples with two hypothetical oil spills

A three dimensional (3D) trajectory model was used to simulate oil mass balance and environmental concentrations of two 795,000L hypothetical oil spills modeled under physical and chemical dispersion scenarios. Species Sensitivity Distributions (SSD) for Total Hydrocarbon Concentrations (THCs) were developed, and Hazard Concentrations (HC) used as levels of concern. Potential consequences to entrained water column organisms were characterized by comparing model outputs with SSDs, and obtaining the proportion of species affected (PSA) and areas with oil concentrations exceeding HC5s (Area⩾HC5). Under the physically-dispersed oil scenario ⩽77% of the oil remains on the water surface and strands on shorelines, while with the chemically-dispersed oil scenario ⩽67% of the oil is entrained in the water column. For every 10% increase in chemical dispersion effectiveness, the average PSA and Area⩾HC5 increases (range: 0.01–0.06 and 0.50–2.9km2, respectively), while shoreline oiling decreases (⩽2919L/km). Integrating SSDs into modeling may improve understanding of scales of potential impacts to water column organisms, while providing net environmental benefit comparison of oil spill response options.

Oil detection in the coastal marshes of Louisiana using MESMA applied to band subsets of AVIRIS data

We mapped oil presence in the marshes of Barataria Bay, Louisiana following the Deepwater Horizon oil spill using Airborne Visible InfraRed Imaging Spectrometer (AVIRIS) data. Oil and non-photosynthetic vegetation (NPV) have very similar spectra, differing only in two narrow hydrocarbon absorption regions around 1700 and 2300nm. Confusion between NPV and oil is expressed as an increase in oil fraction error with increasing NPV, as shown by Multiple Endmember Spectral Mixture Analysis (MESMA) applied to synthetic spectra generated with known endmember fractions. Significantly, the magnitude of error varied depending upon the type of NPV in the mixture. To reduce error, we used stable zone unmixing to identify a nine band subset that emphasized the hydrocarbon absorption regions, allowing for more accurate detection of oil presence using MESMA. When this band subset was applied to post-spill AVIRIS data acquired over Barataria Bay on several dates following the 2010 oil spill, accuracies ranged from 87.5% to 93.3%. Oil presence extended 10.5m into the marsh for oiled shorelines, showing a reduced oil fraction with increasing distance from the shoreline.

Tactical Predictions of Shoreline Oiling Probability via Machine Learning Models and Satellite-Derived Surface Oil Analysis Products

ABSTRACT For significant oil spills in remote areas with complex shoreline geometry, apportioning Shoreline Cleanup Assessment Technique (SCAT) survey effort is a complicated and difficult task. Aerial surveys are often used to select shoreline areas for ground survey after an initial prioritization based upon anecdotal reports or trajectory models, but aerial observers may have difficulty locating cryptic surface shoreline oiling in vegetated or other complex environments. In dynamic beach environments, stranded shoreline oiling may be rapidly buried, making aerial observation difficult. A machine learning-based model is presented for estimating shoreline oiling probabilities via satellite-derived surface oil analysis products, wind summary data, and shoreline habitat type and geometry data. These inputs are increasingly available at spatial and temporal scales sufficient for tactical use, enabling model predictions to be generated within hours after satellite remote sensing products are available. The model was constructed using SCAT data from the Deepwater Horizon oil spill, satellite-derived surface oil analysis products generated during the spill by NOAA's National Environmental Satellite, Data, and Information Service (NESDIS) using a variety of satellite platforms of opportunity, and available shoreline geometry, character, and other preexisting data. The model involves the generation of set of spatial indices of relative over-water proximity of surface oil slicks based upon the satellite-derived analysis products. The model then uses boosted regression trees (BRT), a flexible and relatively recently developed modeling methodology, to generate calibrated estimates of probability of subsequent shoreline oiling based upon these indices, wind climatological data over the time period of interest, and other shoreline data. The model can be implemented via data preparation in any Geographic Information System (GIS) software coupled with the open-source statistical computing language, R. The model is entirely probabilistic and makes no attempt to reproduce the physics of oil moving through the environment, as do trajectory models. It is best used in concert with such models to make estimates at different spatial scales, or when time and data requirements make implementation of fine-scale trajectory modeling impractical for tactical use. The details of model development implementation and assessments of model performance and limitations are presented.

Quantifying Tradeoffs – Net Environmental Benefits of Dispersant Use

ABSTRACT Oil spill response often involves making decisions regarding dispersant usage; the potential tradeoffs of increasing exposure of water column biota to hydrocarbons in order to reduce surface and shoreline oiling needs to be carefully considered and justified. A modeling analysis using RPS ASA's Spill Impact Model Application Package (SIMAP) was performed to evaluate the likely water volume adversely affected by naturally- or chemically-dispersed oil, as well as the surface area impacted by floating oil, and summarized in guidance useful for response planners and decision-makers. Key inputs were varied: oil type, oil volume, environmental (e.g., wind speed, temperature) conditions, dispersant use, weathering state when dispersants are applied, and toxicity to aquatic biota. Model results, including water volume where acute toxic effects would occur and the area of water surface oiled (which would impact wildlife, as well as socioeconomic uses), are summarized in tabular form, as well as a software-tool for interpolation, to provide data for quantitative comparisons of tradeoffs. Findings show that for (effective) dispersant treatment of floating oil volumes up to 100,000 gal in a single location during a short period of time (<1 hr; e.g., by a dispersant plane sortie), the area of surface water where water column biota would be affected would be much less than that affected by floating oil thick enough to directly affect wildlife. Thus, even if large volumes of oil are dispersed, a net environmental benefit may be achieved due to reduction or prevention of exposure to floating and shoreline oil, especially if the dispersant applications are over a wide area or over time.

Shoreline Oiling Data Management for the Deepwater Horizon oil spill, Gulf of Mexico, USA: Implications for Data Management Standards for Future Spills of Significance

The Shoreline Cleanup Assessment Technique (SCAT) data management program for the Deepwater Horizon oil spill is, to our knowledge, the largest shoreline spill data management effort in history, still currently providing continuous data management of over 35,000 separate surveys covering over 22,000 survey-miles of shoreline and tens of millions of individual pieces of data. The program flexibly expanded the scope of coverage to support the changing requirements of survey and cleanup over the response, from surface and subsurface oiling survey data to treatment and administrative status, while maintaining backward compatibility and constant availability for planning and analysis. While we hope many of the tools and products developed will be of value in near-term future spill responses, we are less clear on the specific recommendations we can make to data managers during the next nationally significant spill in 10 or 20 years. The differing needs of each spill, varying levels of agency and industry personnel participation, and the inevitable and increasingly rapid change in software and information technology environments, all point to the need for a different way forward. We feel the most important contribution we can make is the recommendation of an open data standard for shoreline oiling and related data management, allowing interested parties in future responses to be assured of data interoperability, transparency, and data quality, while permitting required flexibility. We propose such a standard here. The proposed data standard does not compete with or supplant any existing vendor or solution, and is completely agnostic about physical spill environment, data collection methods, algorithms, software and computing environment. The standard requires only the most basic structured data so as to preserve the maximum flexibility for spill specific conditions and the unanticipated needs of future data collection. The core components are spatial geometry, temporal relationship, and database attribute and relationship requirements for storing and querying oiling, response, and administrative status via standard geometries over multiple time periods. We present generic entity-relationship diagrams and example core and expansion data structures that outline the proposed standard. In the same way that SCAT methodology protocols and terminology have been adopted across the spill response community by agency and industry, we suggest a core standard for storage and analysis of shoreline oiling and response data. This standard reflects, we hope, a root-level understanding of the purpose and scope of SCAT and related data, and imposes only the minimum uniformity required to be of use.

IPIECA/OGP GUIDE TO OILED SHORELINE OILING ASSESSMENT (SCAT) SURVEYS

This new IPIECA/OGP Guide explains why and how an effective oiled shoreline assessment program is necessary and appropriate to support the planning, decisions making and implementation process for a shoreline response for the initial response to the completion of treatment o cleanup operations. Some of the key elements of the Guide include:• how a SCAT Programme fits into the Shoreline Response Programme and is vertically and horizontally integrated within the response management organization;• how the key components of a shoreline assessment program are integrated into the data generation, decision process, and implementation and closure stages of a shoreline response• the importance of segmentation, as part of pre-spill planning when possible, to divide the shoreline into operational working units and as the foundation for a data base;• identification of the information needs, and expectations, of the decision makers and the flow of information from the documentation generated by the field teams, through the data base, to support the development of treatment options and constraints, treatment end points, and finally into the inspection and closure process;• types of data (maps, tables, reports etc.) that are generated;• lines of communication and support for field Operations regarding (a) guidelines for treatment techniques and strategies, (b) operational environmental, cultural and socioeconomic limitations, (c) treatment priorities, and (d) the application and understanding of Shoreline Treatment Recommendations (STRs) (the shoreline treatment “work orders”);• participants and design elements of a Shoreline Assessment Programme Plan and ;• checklists for the key participants of a SCAT Programme (SCAT Coordinator, Field Team Leads, SCAT-OPS Liaison, Logistics Coordinator, and SCAT Data Manager) for each of the initial (“reactive”) planning, and completion (“closure”) phases of a typical response operation. The SCAT process provides a strategy for completion without which a spill response would be unable to ensure a timely end, which may lead to misuse of resources and negative environmental impacts due to excessive treatment. Shoreline assessment surveys provide valuable information and support for decision makers, planners and operations, no matter the size of the spill, the scale of the response or the environmental setting, to effectively treat or clean oiled shorelines by accelerating recovery without causing additional harm to the environment.

Development and implementation of a shoreline oiling assessment (SCAT) programme for a Tier 3 OSRO

Consistent and reproducible shoreline oiling assessments are critical for making decisions regarding shoreline treatment options and strategies. Industry recognised protocols such as the long established SCAT technique are embedded in many national contingency planning frameworks and are now considered best practice. This paper will describe the OSRL project recently embarked on with Owens Coastal Consultants (OCC) to fully embed the SCAT protocol into OSRL's internal training and response procedures. OSRL has long employed many elements of SCAT in their shoreline response planning process but required a consolidated integration of standard SCAT methodology, process and data handling. Key deliverables for the OSRL SCAT “upgrade” are summarised: Internal training A 4 day SCAT Team Leader training course constructed to provide a solid grounding in SCAT process, shoreline response programmes / management, coastal processes, shoreline impacts and protection techniques. Field work forms an integral part of this course with 2 x ½ day shore based classes covering segmentation, response techniques, shoreline dynamics and operational considerations. SCAT competency to be included at all levels of OSRL personal development plans. External training Introduction of a joint OSRL/OCC 3-day SCAT training course to the OSRL technical training suite at global locations with the aim of establishing OSRL as a lead SCAT training organisation in strategic partnership with OCC. 2013 saw UK, USA and Australia as key course locations. Advocacy A continuing programme of external engagement and messaging of the OSRL SCAT development programme at multiple forums globally. SLA Integration The most important part of the programme is embedding the SCAT process and tools into OSRL's internal response procedures and toolkits for use in spills of all magnitude. Such efforts include the development of mangrove Shoreline Oiling Summary (SOS) forms, OSRL SCAT Manual and Field book, internal training courses, exercises, SCAT data management options and personnel development plans. The trained pool of SCAT expertise will eventually extend to around 70 individuals to support multiple roles ranging from Team Leads, Coordinators, SCAT/OPS Liaison, Logistics Support and Technical Advisors. OSRL staff will also support a larger pool of international expertise that OCC are coordinating for SCAT response functions. Summary The paper will describe in greater detail the design and implementation of the SCAT programme into OSRL's Service Level Agreement (SLA) for the benefit of its Members globally.

Incorporating dynamic factors to the Environmental Sensitivity Index (ESI) shoreline classification – Estonian and Spanish examples

Aps, R., Tõnisson, H, Anfuso, G., Perales, J.A., Orviku, K., Suursaar, Ü. 2014. Incorporating dynamic factors to the Environmental Sensitivity Index (ESI) shoreline classification - Estonian and Spanish examples. In: Green, A.N. and Cooper, J.A.G. (eds.), Proceedings 13th International Coastal Symposium (Durban, South Africa), Journal of Coastal Research, Special Issue No. 70, pp. 235–240, ISSN 0749-0208.Oil transportation is growing in the Baltic Sea area and especially in the Gulf of Finland where it will reach approximately 180–200 million tons a year by 2020. Growing oil transportation is considerably contributing to the risk of accidental spill-related shoreline oiling. This paper focuses on amending the Environmental Sensitivity Index (ESI) related shoreline classification to local conditions by dynamically changing the categorization of the shoreline in terms of its susceptibility to spilled oil caused by extreme meteorological events. This takes into consideration a number of natural physical factors. The paper presents the results of two European case studies: the Estonian shoreline of the Gulf of Finland (Baltic Sea), and the Spanish coast of the Gibraltar Strait. Susceptibility to spilled oil of some categories of the Estonian shoreline (sandy shores, till shores and gravel shores) occasionally changes over time from low to high sensitivity and back; especially conditioned to the influence of heavy storms. The studies carried out in Spain revealed a well recognizable indirect proportionality between foreshore slope and the tidal range. At many locations, the dynamic morphological characteristics of the beach appeared to be largely determined by contouring and specific conditions that are modifying the initial ESI related categorization of the sandy beaches concerned. The novelty of this work is in attempt to move from the standard ESI related, and locally adapted, static shoreline classification towards more dynamic shoreline monitoring based on characterization of the elements sensitive to oil pollution on shorelines.

Detection of Salt Marsh Vegetation Stress and Recovery after the Deepwater Horizon Oil Spill in Barataria Bay, Gulf of Mexico Using AVIRIS Data

The British Petroleum Deepwater Horizon Oil Spill in the Gulf of Mexico was the biggest oil spill in US history. To assess the impact of the oil spill on the saltmarsh plant community, we examined Advanced Visible Infrared Imaging Spectrometer (AVIRIS) data flown over Barataria Bay, Louisiana in September 2010 and August 2011. Oil contamination was mapped using oil absorption features in pixel spectra and used to examine impact of oil along the oiled shorelines. Results showed that vegetation stress was restricted to the tidal zone extending 14 m inland from the shoreline in September 2010. Four indexes of plant stress and three indexes of canopy water content all consistently showed that stress was highest in pixels next to the shoreline and decreased with increasing distance from the shoreline. Index values along the oiled shoreline were significantly lower than those along the oil-free shoreline. Regression of index values with respect to distance from oil showed that in 2011, index values were no longer correlated with proximity to oil suggesting that the marsh was on its way to recovery. Change detection between the two dates showed that areas denuded of vegetation after the oil impact experienced varying degrees of re-vegetation in the following year. This recovery was poorest in the first three pixels adjacent to the shoreline. This study illustrates the usefulness of high spatial resolution airborne imaging spectroscopy to map actual locations where oil from the spill reached the shore and then to assess its impacts on the plant community. We demonstrate that post-oiling trends in terms of plant health and mortality could be detected and monitored, including recovery of these saltmarsh meadows one year after the oil spill.

Investigation of the kinetics of oil–suspended particulate matter aggregation

The process of oil–suspended particulate matter aggregation (OSA) has been recognized by the oil spill remediation community to enhance the natural cleansing of oiled shorelines. A laboratory study was conducted to investigate the kinetics of OSA formation under various mixing intensities using the standard reference material 1941b and Arabian heavy crude oil. The results showed that formation of OSAs increased exponentially with mixing time and reached a maximum within 5h. The maximum oil trapping efficiency increased from 24% to 47%, and the required shaking time decreased from 4.5 to 1.2h as the sediment concentration and mixing energy increased. The maximum oil-to-sediment ratio reached 0.24–0.68g oil/g sediment within 5h. Most of the formed OSAs were solid OSAs and single droplet OSAs with low mixing energies, and multi-droplet OSAs with high mixing energies. The sizes of the dispersed oil droplets and OSAs were also investigated.

Extent and Degree of Shoreline Oiling: Deepwater Horizon Oil Spill, Gulf of Mexico, USA

The oil from the 2010 Deepwater Horizon spill in the Gulf of Mexico was documented by shoreline assessment teams as stranding on 1,773 km of shoreline. Beaches comprised 50.8%, marshes 44.9%, and other shoreline types 4.3% of the oiled shoreline. Shoreline cleanup activities were authorized on 660 km, or 73.3% of oiled beaches and up to 71 km, or 8.9% of oiled marshes and associated habitats. One year after the spill began, oil remained on 847 km; two years later, oil remained on 687 km, though at much lesser degrees of oiling. For example, shorelines characterized as heavily oiled went from a maximum of 360 km, to 22.4 km one year later, and to 6.4 km two years later. Shoreline cleanup has been conducted to meet habitat-specific cleanup endpoints and will continue until all oiled shoreline segments meet endpoints. The entire shoreline cleanup program has been managed under the Shoreline Cleanup Assessment Technique (SCAT) Program, which is a systematic, objective, and inclusive process to collect data on shoreline oiling conditions and support decision making on appropriate cleanup methods and endpoints. It was a particularly valuable and effective process during such a complex spill.

우리나라 실정에 적합한 해안오염평가기술 요소에 관한 연구

When the shorelines were contaminated by oil, oiled shorelines were assessed systematically by SCAT and guideline of cleanup activities and shorelines treatment endpoints based on SCAT were established and operated in case of well developed countries like USA and Canada. However, shorelines cleanup assessment technique are not established clearly in our country. In this study, we studied on the shorelines cleanup assessment technique suitable for Korean shorelines feature. That is, composition of SCAT organization, classification of shorelines and division of oiled shorelines by segment that are elements of SCAT were studied, and we suggest the measures related to above elements suitable for shorelines feature of our country.

Spectroscopic remote sensing of the distribution and persistence of oil from the Deepwater Horizon spill in Barataria Bay marshes

We applied a spectroscopic analysis to Airborne Visible/InfraRed Imaging Spectrometer (AVIRIS) data collected from low and medium altitudes during and after the Deepwater Horizon oil spill to delineate the distribution of oil-damaged canopies in the marshes of Barataria Bay, Louisiana. Spectral feature analysis compared the AVIRIS data to reference spectra of oiled marsh by using absorption features centered near 1.7 and 2.3μm, which arise from CH bonds in oil. AVIRIS-derived maps of oiled shorelines from the individual dates of July 31, September 14, and October 4, 2010, were 89.3%, 89.8%, and 90.6% accurate, respectively. A composite map at 3.5m grid spacing, accumulated from the three dates, was 93.4% accurate in detecting oiled shorelines. The composite map had 100% accuracy for detecting damaged plant canopy in oiled areas that extended more than 1.2m into the marsh. Spatial resampling of the AVIRIS data to 30m reduced the accuracy to 73.6% overall. However, detection accuracy remained high for oiled canopies that extended more than 4m into the marsh (23 of 28 field reference points with oil were detected). Spectral resampling of the 3.5m AVIRIS data to Landsat Enhanced Thematic Mapper (ETM) spectral response greatly reduced the detection of oil spectral signatures. With spatial resampling of simulated Landsat ETM data to 30m, oil signatures were not detected. Overall, ~40km of coastline, marsh comprised mainly of Spartina alterniflora and Juncus roemerianus, were found to be oiled in narrow zones at the shorelines. Zones of oiled canopies reached on average 11m into the marsh, with a maximum reach of 21m. The field and airborne data showed that, in many areas, weathered oil persisted in the marsh from the first field survey, July 10, to the latest airborne survey, October 4, 2010. The results demonstrate the applicability of high spatial resolution imaging spectrometer data to identifying contaminants in the environment for use in evaluating ecosystem disturbance and response.

Experimental Study on Formation of Oil-SPM Aggregates

When oil spills in the coastal environment, the spilled oil may interact with the suspended particulate matter in the water column to form oil-SPM aggregates (OSAs). This process has been recognized to enhance natural cleansing of oiled shorelines. This laboratory study was conducted using SPM samples with different particle size distribution and mineral composition, two crude oil samples, filtered natural seawater, and a reciprocating shaker. The sediment-to-oil ratio was kept constant to 1 in all the experiments. The oil trapped in negatively buoyant OSAs was measured using an Infrared Oil Content Analyzer. Results showed that OSA formation increased with the decrease of the sediment size, the maximum oil trapped in settled OSAs was 182 mg oil/ g sediment when OSAs were formed with kaolinite and CST180 crude oil.

From Exxon to BP: Has Some Number Become Better than No Number?

On March 23, 1989, the Exxon Valdez ran aground in Alaska's Prince William Sound and released over 250,000 barrels of crude oil, resulting in 1300 miles of oiled shoreline. The Exxon spill ignited a debate about the appropriate compensation for damages suffered, and among economists, a debate concerning the adequacy of methods to value public goods, particularly when the good in question has limited direct use, such as the pristine natural environment of the spill region. The efficacy of stated preference methods generally, and contingent valuation in particular, is no mere academic debate. Billions of dollars are at stake. An influential symposium appearing in this journal in 1994 provided arguments for and against the credibility of these methods, and an extensive research program published in academic journals has continued to this day. This paper assesses what occurred in this academic literature between the Exxon spill and the BP disaster. We will rely on theoretical developments, neoclassical and behavioral paradigms, empirical and experimental evidence, and a clearer elucidation of validity criteria to provide a framework for readers to ponder the question of the validity of contingent valuation and, more generally, stated preference methods.

OIL DETECTION IN A COASTAL MARSH WITH POLARIMETRIC SAR

Abstract. The NASA UAVSAR was deployed June 2010 to support Deep Water Horizon oil spill response activities specifically, oil detection and characterization, oil extent mapping in wetlands, coastal resource impact detection, and ecosystem recovery. The UAVSAR platform demonstrated enhanced capability to act rapidly and provide targeted mapping response. Our research focused on the effectiveness of high spatial resolution and fully polarimetric L-band Synthetic Aperture Radar (PolSAR) for mapping oil in wetlands, specifically within Barataria Bay in eastern coastal Louisiana. Barataria Bay contained a numerous site observations confirming spatially extensive shoreline oil impacts, multiple oil spill UAVSAR collections, and a near anniversary 2009 collection. PolSAR oil detection relied on decomposition and subsequent classifications of the single look complex (SLC) calibrated radar cross sections representing the complex elements of the scattering matrix. Initial analyses results found that shoreline marsh structural damage as well as oil on marsh plants and sediments without canopy structural damage were exhibited as anomalous features on post-spill SLC scenes but were not evident on the pre-spill SLC scene collected in 2009. Pre-spill and post-spill Freeman-Durden (FD) and Cloude-Pottier (CP) decompositions and the Wishart classifications seeded with the FD and CP classes (Wishart-FD) also highlighted these nearshore features as a change in dominate scatter from pre-spill to post-spill. SLC analyses also indicated penetration of oil ladened waters into interior marshes well past the immediate shorelines; however, these post-spill SLC analyses results could not be validated due to the lack of observational data and possible flooding in the pre-spill SLC scene.

Gulf spill two years out

Summary Two years on, the national spotlight seems to have turned away from the Gulf oil spill, but a massive assessment of the environmental impacts is quietly under way. As Cyrus Martin reports, several recent observations, and a study of deepwater coral communities, suggest we may not be out of the woods yet.

Impact of the Deepwater Horizon Oil Spill on Bioavailable Polycyclic Aromatic Hydrocarbons in Gulf of Mexico Coastal Waters

An estimated 4.1 million barrels of oil and 2.1 million gallons of dispersants were released into the Gulf of Mexico during the Deepwater Horizon oil spill. There is a continued need for information about the impacts and long-term effects of the disaster on the Gulf of Mexico. The objectives of this study were to assess bioavailable polycyclic aromatic hydrocarbons (PAHs) in the coastal waters of four Gulf Coast states that were impacted by the spill. For over a year, beginning in May 2010, passive sampling devices were used to monitor the bioavailable concentration of PAHs. Prior to shoreline oiling, baseline data were obtained at all the study sites, allowing for direct before and after comparisons of PAH contamination. Significant increases in bioavailable PAHs were seen following the oil spill, however, preoiling levels were observed at all sites by March 2011. A return to elevated PAH concentrations, accompanied by a chemical fingerprint similar to that observed while the site was being impacted by the spill, was observed in Alabama in summer 2011. Chemical forensic modeling demonstrated that elevated PAH concentrations are associated with distinctive chemical profiles.

Unexpectedly high mortality in Pacific herring embryos exposed to the 2007 Cosco Busan oil spill in San Francisco Bay

In November 2007, the container ship Cosco Busan released 54,000 gallons of bunker fuel oil into San Francisco Bay. The accident oiled shoreline near spawning habitats for the largest population of Pacific herring on the west coast of the continental United States. We assessed the health and viability of herring embryos from oiled and unoiled locations that were either deposited by natural spawning or incubated in subtidal cages. Three months after the spill, caged embryos at oiled sites showed sublethal cardiac toxicity, as expected from exposure to oil-derived polycyclic aromatic compounds (PACs). By contrast, embryos from the adjacent and shallower intertidal zone showed unexpectedly high rates of tissue necrosis and lethality unrelated to cardiotoxicity. No toxicity was observed in embryos from unoiled sites. Patterns of PACs at oiled sites were consistent with oil exposure against a background of urban sources, although tissue concentrations were lower than expected to cause lethality. Embryos sampled 2 y later from oiled sites showed modest sublethal cardiotoxicity but no elevated necrosis or mortality. Bunker oil contains the chemically uncharacterized remains of crude oil refinement, and one or more of these unidentified chemicals likely interacted with natural sunlight in the intertidal zone to kill herring embryos. This reveals an important discrepancy between the resolving power of current forensic analytical chemistry and biological responses of keystone ecological species in oiled habitats. Nevertheless, we successfully delineated the biological impacts of an oil spill in an urbanized coastal estuary with an overlapping backdrop of atmospheric, vessel, and land-based sources of PAC pollution.