Current practices and knowledge supporting oil spill risk assessment in the Arctic

EOS - Environment & Oil Spill Response. An analytic tool for environmental assessments to support oil spill response planning: Framework, principles, and proof-of-concept by an Arctic example

The Environment & Oil Spill Response tool (EOS), supports oil spill response planning and decision making. This tool is developed on a research basis, and is an index based, generic and open-source analytic tool, which environmentally can optimise the choice of oil spill response methods for a given spill situation and for a given sea area with respect to environment and nature. The tool is not linked to a particular oil spill simulation model, although it is recommended using oil spill simulation models to have detailed data available for the analysis. The EOS tool consists of an Excel workbook with formulas for calculations and scores followed by screening through decision trees. As case for the EOS tool proof-of-concept, the area of Store Hellefiskebanke, West Greenland, is used. The tool can be downloaded from the Aarhus University home page as a free-of-charge application and is accompanied by a handbook for guidance.

Potential for natural attenuation of crude oil hydrocarbons in benthic microbiomes near coastal communities in Kivalliq, Nunavut, Canada

Oil spilled in marine environments can settle to the seafloor through aggregation and sedimentation processes. This has been predicted to be especially relevant in the Arctic due to plankton blooms initiated by melting sea ice. These conditions exist in the Kivalliq region in Nunavut, Canada, where elevated shipping traffic has increased the risk of accidental spills. Experimental microcosms combining surface sediment and crude oil were incubated at 4 °C over 21 weeks to evaluate the biodegradation potential of seabed microbiomes. Sediments sampled near the communities of Arviat and Chesterfield Inlet were assessed for biodegradation capabilities by combining hydrocarbon geochemistry with 16S rRNA gene and metagenomic sequencing, revealing decreased microbial diversity but enrichment of oil-degrading taxa. Alkane and aromatic hydrocarbon losses corresponded to detection of genes and genomes that encode enzymes for aerobic biodegradation of these compounds, pointing to the utility of marine microbiome surveys for predicting the fate of oil released into Arctic marine environments.

Bayesian inference modeling to rank response technologies in arctic marine oil spills

Marine oil spills have a detrimental effect on aquatic systems. Yet, it is challenging to select appropriate technologies in the Arctic because of limited logistics support, inclement weather conditions, and remoteness, and limited research has been conducted in this direction. This article suggests a method to rank the oil response technologies, including mechanical recovery, chemical dispersant, and in-situ burning, for use in Arctic oil spill risk assessment and preparedness planning. The proposed Preference Learning based Bayesian Inference Modeling offers data-driven ranking of systems by learning a label function and considers factors such as ice covered sea areas, cold weather, and spill volume. A data generation system is developed to produce numerous oil spill scenarios, using a state-of-the-art engineering tool. Results demonstrate that the model, while simple, can efficiently and accurately select the best available technique, making it suitable primarily for marine pollution preparedness and response planning in strategic risk assessments.

Evaluation of machine learning techniques to select marine oil spill response methods under small-sized dataset conditions

Oil spill incidents can significantly impact marine ecosystems in Arctic/subarctic areas. Low biodegradation rate, harsh environments, remoteness, and lack of sufficient response infrastructure make those cold waters more susceptible to the impacts of oil spills. A major challenge in Arctic/subarctic areas is to timely select suitable oil spill response methods (OSRMs), concerning the process complexity and insufficient data for decision analysis. In this study, we used various regression-based machine learning techniques, including artificial neural networks (ANNs), Gaussian process regression (GPR), and support vector regression, to develop decision-support models for OSRM selection. Using a small hypothetical oil spill dataset, the modelling performance was thoroughly compared to find techniques working well under data constraints. The regression-based machine learning models were also compared with integrated and optimized fuzzy decision trees models (OFDTs) previously developed by the authors. OFDTs and GPR outperformed other techniques considering prediction power (> 30 % accuracy enhancement). Also, the use of the Bayesian regularization algorithm enhanced the performance of ANNs by reducing their sensitivity to the size of the training dataset (e.g., 29 % accuracy enhancement compared to an unregularized ANN).

The bibliometric analysis and visualization mapping of net environmental benefit analysis (NEBA)

This paper aims to determine the worldwide research trends on searching queries of "oil spill* and risk assessment*" and "net environmental benefit analysis" and its most productive authors and journals. A bibliometric approach was performed to analyze publications including highly cited papers and only papers that were published in the Dimensions database from 2000 to 2022, April was selected. The necessary data were extracted from the Dimensions database and processed using visualization and mapping software such as VOSviewer 1.6.17 and Tableau Public 2021.1. The findings identified significant study fields, co-cited authors, country contributions, productive journals, as well as the most cited authors' articles. This study contributes significantly to the relevant studies as one of the few that utilizes bibliometric analysis as a network visualization and mapping technique for the analysis of one of the primary oil spill response decision-making tools and risk assessment sciences. The findings of this study can assist the researcher perform their research more effectively by providing insight into journal selection, contributing authors, research trends, countries, and keywords. Further research is recommended in light of longer period data contained in oil spill response strategies, oil spill modeling, or oil spill risk subjects.

Environmental Impacts and Challenges Associated with Oil Spills on Shorelines

Oil spills are of great concern because they impose a threat to the marine ecosystem, including shorelines. As oil spilled at sea is transported to the shoreline, and after its arrival, its behavior and physicochemical characteristics change because of natural weathering phenomena. Additionally, the fate of the oil depends on shoreline type, tidal energy, and environmental conditions. This paper critically overviews the vulnerability of shorelines to oil spill impact and the implication of seasonal variations with the natural attenuation of oil. A comprehensive review of various monitoring techniques, including GIS tools and remote sensing, is discussed for tracking, and mapping oil spills. A comparison of various remote sensors shows that laser fluorosensors can detect oil on various types of substrates, including snow and ice. Moreover, current methods to prevent oil from reaching the shoreline, including physical booms, sorbents, and dispersants, are examined. The advantages and limitations of various physical, chemical, and biological treatment methods and their application suitability for different shore types are discussed. The paper highlights some of the challenges faced while managing oil spills, including viewpoints on the lack of monitoring data, the need for integrated decision-making systems, and the development of rapid response strategies to optimize the protection of shorelines from oil spills.

Natural attenuation of oil in marine environments: A review

Natural attenuation is an important process for oil spill management in marine environments. Natural attenuation affects the fate of oil by physical, chemical, and biological processes, which include evaporation, dispersion, dissolution, photo-oxidation, emulsification, oil particle aggregation, and biodegradation. This review examines the cumulative knowledge regarding these natural attenuation processes as well as their simulation and prediction using modelling approaches. An in-depth discussion is provided on how oil type, microbial community and environmental factors contribute to the biodegradation process. It describes how our understanding of the structure and function of indigenous oil degrading microbial communities in the marine environment has been advanced by the application of next generation sequencing tools. The synergetic and/or antagonist effects of oil spill countermeasures such as the application of chemical dispersants, in-situ burning and nutrient enrichment on natural attenuation were explored. Several knowledge gaps were identified regarding the synergetic and/or antagonistic effects of active response countermeasures on the natural attenuation/biodegradation process. This review highlighted the need for field data on both the effectiveness and potential detrimental effects of oil spill response options to support modelling and decision-making on their selection and application.

Coastline in-situ burning of oil spills in the Arctic. Studies of the environmental impacts on the littoral zone community

In-situ burning (ISB) has been an oil combat technique studied since the 1950s. However, burning of the oil on the sea surface along the coastline, coastline ISB (cISB), is novel and was tested for the first time in the Arctic along a rocky coast in the summer 2017. A light crude oil was burned and effects of the cISB operation on the littoral zone communities investigated. The impact on macroalgal vegetation and associated fauna was analysed in three littoral zone levels. The analyses revealed limited effects on the littoral community, and that variation between sample plots and years in macroalgal biomass and coverage, as well as fauna biomass and abundance was higher than the impact from cISB. Therefore, it is concluded that cISB in the Arctic along a rocky shore may be an oil spill response option with relatively low environmental side effects for the specific oil type used.

Influence of dispersant application on the toxicity to sea urchin embryos of crude and bunker oils representative of prospective oil spill threats in Arctic and Sub-Arctic seas

This study deals with the toxicity assessment of crude and bunker oils representative of prospective oil spill threats in Arctic and Sub-Arctic seas (NNA: Naphthenic North-Atlantic crude oil; MGO: Marine Gas Oil; IFO: Intermediate Fuel Oil 180), alone or in combination with a third-generation dispersant (Finasol OSR52®). Early life stages of sea urchin, Paracentrotus lividus, were selected for toxicity testing of oil low-energy water accommodated fractions. A multi-index approach, including larval size increase and malformation, and developmental disruption as endpoints, was sensitive to discriminate from slight to severe toxicity caused by the tested aqueous fractions. IFO (heavy bunker oil) was more toxic than NNA (light crude oil), with MGO (light bunker oil) in between. The dispersant was toxic and further on it enhanced oil toxicity. Toxic units revealed that identified PAHs were not the main cause for toxicity, most likely exerted by individual or combined toxic action of non-measured compounds.

Decision support tools for oil spill response (OSR-DSTs): Approaches, challenges, and future research perspectives

Marine oil spills pose a significant threat to ocean and coastal ecosystems. In addition to costs incurred by response activities, an economic burden could be experienced by stakeholders dependent on coastal resources. Decision support tools for oil spill response (OSR-DSTs) have been playing an important role during oil spill response operations. This paper aims to provide an insight into the status of research on OSR-DSTs and identify future directions. Specifically, a systematic review is conducted including an examination of the advantages and limitations of currently applied and emerging decision support techniques for oil spill response. In response to elevated environmental concerns for protecting the polar ecosystem, the review includes a discussion on the use of OSR-DSTs in cold regions. Based on the analysis of information acquired, recommendations for future work on the development of OSR-DSTs to support the selection and implementation of spill response options are presented.

Quantifying the consequence of applying conservative assumptions in the assessment of oil spill effects on polar cod (Boreogadus saida) populations

In order to assess the potential impact from oil spills and decide the optimal response actions, prediction of population level effects of key resources is crucial. These assessments are usually based on acute toxicity data combined with precautionary assumptions because chronic data are often lacking. To better understand the consequences of applying precautionary approaches, two approaches for assessing population level effects on the Arctic keystone species polar cod (Boreogadus saida) were compared: a precautionary approach, where all exposed individuals die when exposed above a defined threshold concentration, and a refined (full-dose-response) approach. A matrix model was used to assess the population recovery duration of scenarios with various but constant exposure concentrations, durations and temperatures. The difference between the two approaches was largest for exposures with relatively low concentrations and short durations. Here, the recovery duration for the refined approach was less than eight times that found for the precautionary approach. Quantifying these differences helps to understand the consequences of precautionary assumptions applied to environmental risk assessment used in oil spill response decision making and it can feed into the discussion about the need for more chronic toxicity testing. An elasticity analysis of our model identified embryo and larval survival as crucial processes in the life cycle of polar cod and the impact assessment of oil spills on its population.

Impacts of Oil Spills on Arctic Marine Ecosystems: A Quantitative and Probabilistic Risk Assessment Perspective

Oil spills resulting from maritime accidents pose a poorly understood risk to the Arctic environment. We propose a novel probabilistic method to quantitatively assess these risks. Our method accounts for spatiotemporally varying population distributions, the spreading of oil, and seasonally varying species-specific exposure potential and sensitivity to oil. It quantifies risk with explicit uncertainty estimates, enables one to compare risks over large geographic areas, and produces information on a meaningful scale for decision-making. We demonstrate the method by assessing the short-term risks oil spills pose to polar bears, ringed seals, and walrus in the Kara Sea, the western part of the Northern Sea Route. The risks differ considerably between species, spatial locations, and seasons. Our results support current aspirations to ban heavy fuel oil in the Arctic but show that we should not underestimate the risks of lighter oils either, as these oils can pollute larger areas than heavier ones. Our results also highlight the importance of spatially explicit season-specific oil spill risk assessment in the Arctic and that environmental variability and the lack of data are a major source of uncertainty related to the oil spill impacts.

Dispersant application increases adverse long-term effects of oil on shrimp larvae (Pandalus borealis) after a six hour exposure

The application of chemical dispersants is one option of oil spill response (OSR). Here, Northern shrimp (Pandalus borealis) larvae were experimentally exposed for short periods (6 h and 1 h) to a realistic concentration of chemically dispersed oil (CDO) (~10 mg L^-1 THC), mechanically dispersed oil (MDO) (~7 mg L^-1 THC), and dispersant only (D). A control (C) with seawater served as reference. Short-term effects on survival and feeding were examined right after exposure and longer-term consequences on survival, feeding, growth and development following 30 days of recovery. Both exposure durations provoked long lasting effects on larval fitness, with 1 h exposure leading to minor effects on most of the selected endpoints. The 6 h exposure affected all endpoints with more adverse impacts after exposure to CDO. This study provides important data for assessing the best OSR option relevant to NEBA (Net Environmental Benefit Analysis).

Exposure to chemically-dispersed oil is more harmful to early developmental stages of the Northern shrimp Pandalus borealis than mechanically-dispersed oil

Knowledge of key species sensitivity for oil spill response (OSR) options is needed to support decision-making and mitigate impact on sensitive life stages of keystone species. Here, Northern shrimp (Pandalus borealis) larvae were exposed for 24 h to a gradient (H-High, M-Medium: 10 times dilution and L-Low: 100 times dilution) of mechanically- (MDO) (H < 6 mg/L total hydrocarbon content) and chemically- (CDO) dispersed oil (Slickgone NS, H < 20 mg/L total hydrocarbon content), followed by a recovery period. Larval mortality, feeding rate and development were evaluated. Overall, the results show that 24 h exposure to field-realistic concentrations of CDO lead to lower survival, reduced feeding rate and slower larval development in P. borealis larvae compared to MDO. These effects persisted during recovery, indicating a higher vulnerability with dispersant use and the need for longer observation periods post-exposure to fully evaluate the consequences for sensitive life-stages from OSR.