Effects Of Oil Spill Research Articles

Application Comparison of the Lex Loci Delicti Commission Theory between the Oil Spill Case in the Gulf of Mexico and the Carbon Emissions Case in the Netherlands

The event of a disastrous oil spill from British Petroleum's offshore drilling installation on the 20th of April 2010 was caused by a leaking underwater pipeline, which polluted the waters of the Gulf of Mexico. Subsequently, there was the Carbon Emission Case in the Netherlands, which required Shell to reduce their carbon emissions by 45% by 2030 from the carbon emissions generated in 2019. Both events were deeply concerning and directly effected the citizens of the respective countries. In the first case, the spill of approximately 5,000 barrels or 210,000 gallons (795,000 liters) of crude oil spread extensively due to ocean currents where the contaminated area ended up covering 9,933 square kilometers of ocean (77 x 129km). This oil spill, which was a result of British Petroleum's negligence, lead to legal action taken against the company for violations of international environmental laws, due to environmental pollution. In the second case, Shell, was deemed to have contributed significantly to climate change in the Netherlands. The company was responsible for twice the amount of greenhouse gas emissions than the Netherlands. The research method employed in this journal uses a normative juridical research approach, focusing on legal norms within the decisions for Case MDL No. 2179 and the Verdict issued by the Haugue District Court. In this journal, the author concludes that both British Petroleum and Shell have been proven to commit unlawful acts against the international environment laws through environmental pollution.

Ecological risk assessment of a coastal area using multi-source remote sensing images and in-situ sample data

Healthy coastal area have high ecological service value. However, because of the uncontrolled utilization of marine resources and the discharge of pollutants, the ecological environments of many coastal areas are faced with ecological risks, such as oil spills and Enteromorpha blooms. Therefore, it is of great significance to monitor and assess the ecological risks in coastal areas. The remote sensing technique can be used to obtain frequent and wide-coverage images of the areas of interest, and has become an effective tool to monitor the ecological risks occurring in coastal areas. In this study, taking Jiaozhou Bay in China as the study area, an innovative ecological risk assessment framework was established using multi-source remote sensing images and in-situ sample data, which fully considers the potential harm of oil spills and Enteromorpha blooms on the ecology of the bay. Specifically, the oil spill risk for Jiaozhou Bay from 2017 to 2019 was identified by a deep learning based method from synthetic aperture radar (SAR) images, and the Enteromorpha bloom risk for the corresponding years was identified by a floating algae index (FAI) threshold method from multi-source optical images. Then, using habitat information and ground observation data about the marine species in the bay, environmental vulnerability maps were generated. Finally, a disaster-causing factors and disaster-bearing factors weighted risk assessment model was developed. The risk source monitoring results show that the occurrence frequency of oil spills in Jiaozhou Bay decreased from 2017 to 2019, while the outbreak intensity of Enteromorpha blooms generally became higher. The ecological risk assessment results reveal that the high risk areas of Jiaozhou Bay are mainly around the transportation regions and the ports, with a higher risk degree in the eastern and southern parts. To support our work, the well-trained oil spill detection network model and some information about the oil spill events that have occurred in Jiaozhou Bay are provided in this paper.

Novel oil spill indices for sentinel-2 imagery: A case study of natural seepage in Qaruh Island, Kuwait

Oil spills are a paramount and immediate challenge affecting marine ecosystems globally. Effective and timely monitoring tools, such as oil detection indices, offer a swift means to track oil spill spread across vast oceanic expanses. Moreover, these indices enhance data clarity, making it more conducive for machine learning and deep learning algorithms.This study leverages the natural seepage occurring around Qaruh Island, Kuwait as a unique context for the spectral analysis of oil spills using Sentinel-2 multispectral imagery due to repeated occurrences in the same region. This research evaluated 859 single band and 455 multichannel combinations to identify the most effective combinations in oil-water separability, employing the Jeffries-Matusita (JM) distance measure as a key metric. Bands 1, 2, 3, 8A, 11, and 12 consistently featured among the top-performing indices combinations B1−B11B1+B11;B1+B2B3+B11;B1+B2B3+B12;B1+B2B3+B8A affirming the significant effect of oil spills on visible, Near-Infrared (NIR), and Shortwave Infrared (SWIR) bands. Notably, the indices developed in this study outperformed those from prior research in terms of suitability to unsupervised classification algorithms. A significant conclusion of this study is that incorporating a higher number of bands in the analysis did not correlate with an increase in JM values, suggesting that the selection of specific, informative bands is more critical than the volume of input data. These findings underscore the indispensable role of Sentinel-2 imagery in environmental investigations and highlight the potential for focused, efficient analysis using strategic band combinations for effective oil spill detection.•This study identified optimized Sentinel-2 band combinations for oil-water separability, benefiting from naturally occurring spills around Qaruh Island.•The proposed indices outperformed the previous indices for oil spill visualization and clustering.•The new indices highlighted the critical role of specific band selection over the volume of input data for effective oil spill detection.

Overview of oil spills worldwide and impacts on marine megafauna

Oil spills have a significant impact on the environment, posing threats to various marine species. This review aims to gather information on various oil spills that have occurred worldwide and discuss their impact on marine megafauna (marine mammals, sea turtles, and seabirds), in order to provide useful insights that can be applied in decision-making during rescue and rehabilitation efforts. The publications were obtained from oil spill searches in databases such as Elsevier-Scopus, Scielo, JStor, and Google Scholar. Oil spills can cause lethal damage to marine biodiversity, affecting individuals of different ages and species. Although the acute effects of oil contamination on wildlife are evident, it is challenging to treat and recover from. Hydrocarbons can persist in the environment for a long time, leading to prolonged exposure of animals to the contaminants. In conclusion, this research demonstrates that the effects of oil spills on marine megafauna may not be observed in the short term, such as contamination through the bioaccumulation of compounds in the food chain. It is necessary to conduct systematic studies on local fauna at all developmental stages of oil activities, including seismic research, exploration, and oil distribution to address the impact of oil spills on marine megafauna.

The Impact Path of the Gulf of Mexico Oil Spill on Fisheries A Case of the Deepwater Horizon Oil Spill

Oil spills not only affect the Marine ecosystem, but also affect the economic benefits of human beings. Therefore, this paper studies the impact of the Deepwater Horizon Oil Spill (DWH) events on fisheries from the perspectives of demand and supply, which is helpful to understand the harm of oil spills, improve public awareness of environmental protection, and formulate effective prevention and control measures. On the supply side, oil spills have reduced fish numbers, polluted seawater, and reduced biodiversity. To clean up the spill, the government changed the water quality, which may have further killed some Marine life. On the demand side, consumers are concerned about fish pollution, which will have an impact on the health of consumers. Consumer demand is reduced, which in turn leads to a reduction in the income of local fishermen, and the demand of local fishermen is also reduced. Finally, this paper proposes to strengthen the management of the U.S. oil exploration access system, protect marine life, and install more guardrails.

Forecast modelling of vegetable oil spill events at Paranaguá Port, Brazil

The Port of Paranaguá serves as Brazil's primary outlet for soy oil exports, accounting for nearly 70\% of all shipments in 2021. While less common than mineral oil spills, vegetable oil spills can have similarly devastating environmental effects. This risk underscores the need for effective planning and management of activities involving vegetable oil handling in the region. To address this need, this study developed results based on a forecasting setup focused on describing the behaviour of soy oil spills in the estuarine complex of Paranaguá. The system uses the open TELEMAC-MASCARET three-dimensional numerical modelling system to solve oil movement equations, coupling the hydrodynamic module (Telemac-3d) with the oil module (ECOS). The system is automated through computational routines written in Python and the bash command language, enabling users to initiate simulations and generate dispersion maps to track soybean oil in hypothetical spill scenarios. The processing results were satisfactory, demonstrating the potential for this tool to contribute to minimising the impacts of soybean oil spills in the Bay of Paranaguá. This system can support better decision-making in response efforts, reduce environmental damage, and enhance the protection of local ecosystems.

Long-term effects of the Hebei Spirit oil spill on the prevalence and incidence of allergic disorders

The Hebei Spirit oil spill accident occurred in December 2007, approximately 10 km off the coast of Taean, South Korea, a location notably close to residential areas. Crude oil substances have been detected in various environmental mediums since the accident, yet previous studies have primarily focused on the acute effects of oil exposure due to the short latency period of allergic diseases. Therefore, this study evaluated the long-term effects of oil spill exposure on allergic disorders. Our study included adult residents who had participated in the Health Effects Research on Hebei Spirit Oil Spill (HEROS) study up to five years post-incident, which was a prospective cohort to monitor the health status of Taean residents. We used two indicators to assess oil spill exposure, namely the distance from the initial contaminated coastline to each participant's residence and the number of days participants had engaged in oil clean-up work. Current symptoms such as asthma, allergic rhinitis, atopic dermatitis, allergic conjunctivitis, and multimorbidity were considered allergic disorders. In the baseline survey, the prevalence of asthma, allergic rhinitis, atopic dermatitis, allergic conjunctivitis, and allergic multimorbidity symptoms was associated with both exposure indicators; however, these associations were not observed in the two consecutive surveys. Significant longitudinal associations between oil spill exposure indicators and the four allergic disorders, as well as multimorbidity incidences, were observed during a five-year follow-up period. Our results suggest that oil spill exposure can affect acute and long-term allergic symptoms in residents near the accident site.

Application of whole-cell bioreporters for ecological risk assessment and bioremediation potential evaluation after a benzene exceedance accident in groundwater in Lanzhou, China

Oil spill events challenge human health and ecosystem safety, which are priority concerned issues for sustainable development. There is then an increasing demand of tools for ecological risks assessment at contaminated sites. In this study, we introduced two whole-cell bioreporters, ADPWH_alk and ADPWH_recA, to measure the available n-alkanes and the genotoxicities of total petroleum hydrocarbons in soils and groundwater which were contaminated by the Benzene Exceedance Accident in Lanzhou, China. Comparing to traditional chemical analysis methods, the whole-cell bioreporter method could provide risk assessment on cell level within a shorter time and a less cost, which is economical and environment friendly. The highest contents of available alkanes in soil and groundwater were 18,737 mg/kg and 308.4 mg/L, respectively. In addition, the available n-alkanes significantly (p < 0.01) correlated to chemical analysis of total n-alkanes. The highest genotoxicity level was found in soil and groundwater samples with lower TPHs concentration (4338.0 mg/kg and 1.4 mg/L Mitomycin C equivalent), suggesting the significant impacts of geochemical variables and alkane availability on the ecological risks of petroleum contamination. Combining chemical analysis and whole-cell bioreporter results, bioremediation strategies were suggested for groundwater and soils with higher n-alkane availability and lower ecological risks, whereas chemical oxidation were suggested for other contaminated sites. For the first time, we mapped the distribution of available n-alkanes and petroleum toxicities in a large scale soil-groundwater system using whole-cell bioreporters, showing their huge potential for rapid contaminant detection and fast risk assessment.

Monitoring of Oil Spill Risk in Coastal Areas Based on Polarimetric SAR Satellite Images and Deep Learning Theory

Healthy coasts have a high ecological service value. However, many coastal areas are faced with oil spill risks. The Synthetic Aperture Radar (SAR) remote sensing technique has become an effective tool for monitoring the oil spill risk in coastal areas. In this study, taking Jiaozhou Bay in China as the study area, an innovative oil spill monitoring framework was established based on Polarimetric SAR (PolSAR) images and deep learning theory. Specifically, a DeepLabv3+-based semantic segmentation model was trained using 35 Sentinel-1 satellite images of oil films on the sea surface from maritime sectors in different regions all over the world, which not only considered the information from the PolSAR images but also meteorological conditions; then, the well-trained framework was deployed to identify the oil films in the Sentinel-1 images of Jiaozhou Bay from 2017 to 2019. The experimental results show that the detection accuracies of the proposed oil spill detection model were higher than 0.95. It was found that the oil films in Jiaozhou Bay were mainly concentrated in the vicinity of the waterways and coastal port terminals, that the occurrence frequency of oil spills in Jiaozhou Bay decreased from 2017 to 2019, and that more than 80 percent of the oil spill events occurred at night, mainly coming from the illegal discharge of waste oil from ships. These data indicate that, in the future, the PolSAR technique will play a more important role in oil spill monitoring for Jiaozhou Bay due to its capability to capture images at night.

THE IMPACT OF OIL SPILLS ON THE ECONOMY AND THE ENVIRONMENT

&lt;p&gt;This paper critically assesses the multifaceted consequences of oil spills, particularly emphasizing their ramifications on the environment and the economy. With globalization intensifying reliance on maritime transport—accounting for nearly 90% of global trade—the potential for oil spills and their subsequent repercussions have become an alarming concern. Such spills can inflict enduring damage on marine ecosystems and lead to substantial economic setbacks in industries like fishing, tourism, and maritime operations. The enormity of the challenge extends beyond immediate environmental and economic impacts; it necessitates an interdisciplinary comprehension spanning environmental science, economics, legislation, and technology. Furthermore, oil spills underscore the need for international collaboration, as their consequences can breach national boundaries. This systematic literature review methodically analyzes existing research on the topic, employing databases like PubMed, Scopus, ScienceDirect, and Google Scholar. Through a rigorous filtering process, the review synthesizes empirical studies, theoretical analyses, government reports, and field assessments. The endeavor is to delineate prevailing themes, methodologies, conclusions, and lacunae in the extant literature, aiming to bridge the gap between economic growth imperatives and environmental sustainability challenges.&lt;/p&gt;&lt;p&gt;&lt;strong&gt; &lt;/strong&gt;&lt;/p&gt;&lt;p&gt;&lt;strong&gt;JEL&lt;/strong&gt;: Q53, Q57, L91, Q35, F18, Q58, O13, Q22&lt;/p&gt;&lt;p&gt; &lt;/p&gt;&lt;p&gt;&lt;strong&gt; Article visualizations:&lt;/strong&gt;&lt;/p&gt;&lt;p&gt;&lt;img src="/-counters-/soc/0039/a.php" alt="Hit counter" /&gt;&lt;/p&gt;

Oil Spill Detection Using Otical Sensors: A Multi-Temporal Approach

Oil pollution is one of the most destructive consequences due to human activities in the marine environment. Oil wastes come from many sources and take decades to be disposed of. Satellite based remote sensing systems can be implemented into a surveillance and monitoring network. In this study, a multi-temporal approach to the oil spill detection problem is investigated. Change Detection (CD) analysis was applied to MODIS/Terra and Aqua and OLI/Landsat 8 images of several reported oil spill events, characterized by different geographic location, sea conditions, source and extension of the spill. Toward the development of an automatic detection algorithm, a Change Vector Analysis (CVA) technique was implemented to carry out the comparison between the current image of the area of interest and a dataset of reference image, statistically analyzed to reduce the sea spectral variability between different dates. The proposed approach highlights the optical sensors’ capabilities in detecting oil spills at sea. The effectiveness of different sensors’ resolution towards the detection of spills of different size, and the relevance of the sensors’ revisiting time to track and monitor the evolution of the event is also investigated.

Déjà vu: New oil spill poses cumulative risks to protected coastal environments in the South Atlantic

In 2022, new oil spills appeared again on tropical beaches; this time, they were concentrated on the Brazilian semiarid coast. This equatorial region was already impacted by the 2019/2020 event, but the impact of this new spill and its risks have not yet been discussed in literature. This article aims to provide the first data on this latest oil spill event as well as the cumulative risks presented by the two oil spills. The 2022 spill was mainly composed of fragments smaller than 0.15 m, with ∼ 11.6 m3 of oil collected. Oil was detected across the Equatorial coastline, over an extension of ∼ 342 km. The oil started arriving on the east coast of the Ceará State on January 25 and drifted westward, reaching new sites, until February 16. The 2022 spill reached 14 municipalities, 15 marine protected areas (MPAs), and 84 beaches. Geospatial analysis of this event—overlapped with data from the most extensive spill ever recorded in the tropical oceans (2019/2020)—indicates that 8 MPAs and 73.5 % of the beaches have been affected for a second time. The repeat of such an oil incident suggests that improved detection and mitigation strategies are necessary, along with management systems in the event of future pollution occurrences.

New links between invariant dynamical structures and uncertainty quantification

This paper proposes a new uncertainty measure, appropriate for quantifying the performance of transport models in assessing the origin or source of a given observation. It is found that in a neighborhood of the observation the proposed uncertainty measure is related to the invariant dynamical structures of the model. The paper illustrates the implementation of the proposed definition to quantify the performance of ocean data sets in the context of a real oil spill event in the Eastern Mediterranean in 2021.

The Potential Impact of Oil Spills in Coastal Waters on Water Supply in Trinidad

Oil exploration poses an inherent risk to water resources and water quality, exemplified by oil spills resulting from broken pipelines, underwater blowouts and oil transport vessel accidents. In these instances, as vulnerable to spilled oil, water is usually the first casualty, resulting in oil contaminated water. In an effort to ensure the sustainability of freshwater resources resilience in Small Island Developing States, (SIDS), desalination is increasingly used to provide potable water. Thus, oceanic oil spills are of significant relevance to the provision of a guaranteed supply of potable water. Trinidad and Tobago, an oil-producing (SIDS), with considerable oil and gas activities on land and in shallow coastal waters; can become increasingly stressed from oil spills, possibly leading to halting seawater intakes in the desalination process. A real-life seawater surface oil spill in the Gulf of Paria, south-west coast of Trinidad, not far from the largest desalination plant in the Caribbean, is investigated using numerical mathematical modelling to model the spill’s movement underwater. The trajectory plots produced and analysed, indicated that depending on key parameters of the oil and the current ambient conditions, an oil plume can travel significantly long horizontal distances underwater before destabilising. Inferences suggested that oily underwater and existing ambient conditions can potentially affect the desalination equipment. Hence, oil spill modelling is necessary to determine oil trajectory and further inform the decision-making process in determining the best location for constructing desalination plants so as to minimise disruption to the island’s domestic freshwater supply in oil spill events.

Does corporate governance matter in the cleanup of reported oil spills? Evidence from Nigeria

PurposeThis study aims to examine whether corporate governance mechanisms – board size, board independence and CEO duality – influence the actions of oil companies operating in Nigeria to clean up oil spills from their facilities.Design/methodology/approachBoth binary logistic regression (linear) and random-effects logistic regression models were used to test three hypotheses using a unique data set of 1,262 oil spill events involving 24 oil companies from 2017 to 2019.FindingsThe study found that board size and board independence are positively related to oil spill cleanup.Practical implicationsPrivate oil companies in Nigeria should encourage larger and more independent boards in their corporate governance (CG) structures, as these boards may be more effective in serving the interests of stakeholders by bringing diverse knowledge and experience to the boards. Similarly, regulators should extend the enforcement of CG codes to private firms.Originality/valueTo the best of the authors’ knowledge, this is the first study that investigates the influence of CG attributes on oil spill cleanup.

Assessing the risk of oil spill impacts and potential biodiversity loss for coastal marine environment at the turn of the COVID-19 pandemic event

The Tuscan Archipelago, with its great environmental and economic importance, is one of the highest oil spill density areas in the Western Mediterranean. In this study, an interdisciplinary approach, based on numerical applications and experimental methods, was implemented to quantify the risk of oil spill impact along the rocky shores of this archipelago in relation to the maritime activities. The risk, defined as a combination of the hazard and the damage, was quantified for the biennial 2019–2020 in order to account for the effects generated by the COVID-19 pandemic restrictions on the local maritime traffic. A high-resolution oceanographic and particle tracking model was applied to simulate the trajectories of possible oil spill events and to quantify the hazard of impacts on the coast of numerical particles, daily seeded in correspondence of those marine sectors that are characterised by relevant traffic of vessels. The damage, expressed as the product of exposure and vulnerability, was estimated following an extensive sampling approach aimed at quantifying the ecological status of the rocky shores in four selected islands of the Tuscan Archipelago. Results revealed and quantified the direct relationship between the temporary reduction of the maritime traffic due to the pandemic restrictions, and the probability of suffering damage from oil spill impact along the archipelago's rocky shores, which was highly context-dependent.

The influence of ocean acidification and warming on responses of Scylla serrata to oil pollution: An integrated biomarker approach.

Anthropogenic activities primarily combustion of fossil fuel is the prime cause behind the increased concentration of CO2 into the atmosphere. As a consequence, marine environments are anticipated to experience shift towards lower pH and elevated temperatures. Moreover, since the industrial revolution the growing demand for petroleum-based products has been mounting up worldwide leading to severe oil pollution. Sundarbans estuarine system (SES) is experiencing ocean warming, acidification as well as oil pollution from the last couple of decades. Scylla serrata is one of the most commercially significant species for aquaculture in coastal areas of Sundarbans. Thus, the prime objective of this study is to delineate whether exposure under ocean warming and acidification exacerbates effect of oil spill on oxidative stress of an estuarine crab S. serrata. Animals were separately exposed under current and projected climate change scenario for 30days. After this half animals of each treatment were exposed to oil spill conditions for 24h. Oxidative stress status superoxide dismutase (SOD), catalase (CAT), glutathione S-transferase (GST), lipid peroxidation (LPO level) and DNA damage (Comet assay) were measured. Augmented antioxidant and detoxification enzyme activity was noted except for SOD but failed to counteract LPO and DNA damage. The present results clearly highlighted the detrimental combined effect of OWA and pollution on oxidative stress status of crabs that might potentially reduce its population and affect the coastal aquaculture in impending years.

Remote sensing reveals unprecedented sublethal impacts of a 40-year-old oil spill on mangroves

Oil spills cause long-lasting mangrove loss, threatening their conservation and ecosystem services worldwide. Oil spills impact mangrove forests at various spatial and temporal scales. Yet, their long-term sublethal effects on trees remain poorly documented. Here, we explore these effects based on one of the largest oil spills ever recorded, the Baixada Santista pipeline leak, which hit the mangroves of the Brazilian southeastern coast in 1983. Historical, Landsat-derived normalized difference vegetation index (NDVI) maps over the spilled mangrove reveal a large dieback of trees within a year following the oil spill, followed by a eight-year recolonization period and a stabilization of the canopy cover, however 20–30% lower than initially observed. We explain this permanent loss by an unexpected persistence of oil pollution in the sediments based on visual and geochemical evidence. Using field spectroscopy and cutting-edge drone hyperspectral imaging, we demonstrate how the continuous exposure of mangrove trees to high levels of pollution affects their health and productivity in the long term, by imposing permanent stressful conditions. Our study also reveals that tree species differ in their sensitivity to oil, giving the most tolerant ones a competitive advantage to recolonize spilled mangroves. By leveraging drone laser scanning, we estimate the loss of forest biomass caused by the oil spill to be 9.8–91.2 t ha−1, corresponding to 4.3–40.1 t C ha−1. Based on our findings, we encourage environmental agencies and lawmakers to consider the sublethal effects of oil spills on mangroves in the environmental cost of these accidents. We also encourage petroleum companies to use drone remote sensing in monitoring routines and oil spill response planning to improve mangrove preservation and impact assessment.

Long-Wave Infrared Polarization-Based Airborne Marine Oil Spill Detection and Identification Technology

In this paper, infrared polarization detection information acquisition technology is proposed, and the polarization characteristics of oil spills are modeled and studied. A set of long-wave infrared polarization detection equipment for oil spills is designed and built, and modeling research on oil spill polarization characteristics is carried out to accurately detect and identify oil spill types and for the faster processing of oil spill events. Oil spill accuracy is increased by defining the polarization maintenance method of the polarization optical system and reducing the polarization measurement error brought on by the imaging system. As a result, a higher than 3% contrast exists between the polarization degree image and the corrected infrared intensity image. Outdoor tests using oil, palm oil, crude oil, gasoline, and diesel oil spill types are carried out in a controlled environment to collect data on the polarization of various oil species. According to the findings, each oil species’ infrared polarization contrast with seawater is typically greater than its infrared intensity contrast. However, the polarization data of saltwater, diesel, and palm oil, which are difficult to identify in intensity data, show a noticeable difference, further proving the viability of utilizing polarization to discern oil spills.

Advances to the CROSERF protocol to improve oil spill response decision making

The Chemical Response to Oil Spills: Ecological Effects Research Forum (CROSERF) created a standardized protocol for comparing the toxicity of physically dispersed oil versus chemically dispersed oil to address environmental concerns related to the proposed use of dispersants in the early 2000s. Since then, many revisions have been made to the original protocol to diversify the intended use of the data generated, incorporate emerging technologies, and to examine a wider range of oil types including non-conventional oils and fuels. Under the Multi-Partner Research Initiative (MPRI) for oil spill research under Canada's Oceans Protection Plan (OPP), a network of 45 participants from seven countries representing government, industry, non-profit, private, and academic sectors was established to identify the current state of the science and formulate a series of recommendations to modernize the oil toxicity testing framework. The participants formed a series of working groups, targeting specific aspects of oil toxicity testing, including: experimental conduct; media preparation; phototoxicity; analytical chemistry; reporting and communicating results; interpreting toxicity data; and appropriate integration of toxicity data to improve oil spill effects models. The network participants reached a consensus that a modernized protocol to assess the aquatic toxicity of oil should be sufficiently flexible to address a broad range of research questions in a ‘fit-for-purpose’ manner, where methods and approaches are driven by the need to generate scientifically-defensible data to address specific study objectives. Considering the many needs and varied objectives of aquatic toxicity tests currently being conducted to support and inform oil spill response decision making, it was also concluded that the development of a one size fits all approach would not be feasible.