Quantitative oil spill risk from offshore fields in the Bohai Sea, China

Oil pollution risks on coastlines in the Eastern China Seas

As maritime transportation experiences continuous development, the escalating potential risk of oil spills necessitates thorough and detailed risk assessments. Realizing the inherent contingency and unpredictability of oil spill incidents, this study employs a 3D oil spill model combining with long-term hydro-meteorological data to evaluate the oil pollution risk (OPR) along the coastlines of the Eastern China Seas. Through simulations spanning four seasons over 21 years (2001-2021), diverse scenarios are captured. Specifically, surface oil spills in the Bohai Sea mainly spread along coastal currents but have a relatively limited diffusion range due to ocean dynamic conditions. Surface oil spills occurring in the Yellow Sea mainly threaten the ecological environments of the Korean Peninsula, Shandong Peninsula, and Subei Shoal, while those occurring in the East China Sea significantly impact the coastal areas of Zhejiang, Fujian, and Kyushu. Furthermore, the distribution of OPR exhibits clear and stable seasonal characteristics, with interannual variabilities less than 2%. Coastlines affected by the Kuroshio and its branches are at a higher risk year-round but with smaller interannual variabilities. Conversely, coastlines exhibiting large interannual variabilities are mainly distributed in regions that undergo significant seasonal changes in current and wind fields.

Multifactorial risk mapping of oil spill accidents for emergency response areas at regional, national and international scales

Quantification and mapping of oil spill risk are essential for emergency response and mitigation of marine accidents. Large-scale risk management involves geographical identification of hazards and sensitivities in coastal and offshore regions. In this study, a multifactorial oil spill risk model was developed on a national scale by determining the frequency (probability) and sensitivity (severity) of marine and coastal accidents. Seven accident frequency and 51 sensitivity factors were investigated within the Turkish Emergency Response Area (TERA) of 660,908 km2. Hydrographical, meteorological, oceanographical, and maritime conditions were analyzed to calculate accident frequency. The sensitive areas were mapped using the geographical distribution of ecologic, social, and economic assets. Using data analytics, digital maps of accident frequency, sensitivity and risk were produced in a GIS grid of 21,410 cells with 3NM resolution. Accident hotspots were identified from scalable frequency maps showing regions of high accident probability. Sensitivity factors were analyzed from environmental, social, and economic vulnerabilities. Using their geographic distribution, a sensitivity map was generated and hotspots were identified. Frequency and sensitivity indices were combined to obtain the grid-based high-resolution oil spill risk map on a scalable GIS platform. High-risk areas were identified for future research on oil spill simulations and emergency response plans. The methodology may help scientists and environmental experts develop regional, national, and global risk assessment tools. The outcomes within the TERA may serve as planning and decision support tools for lawmakers, environmental experts, and oil spill response professionals to manage oil pollution risk across the TERA.

Forecasting marine spill risk along the U.S. Pacific coasts

This study analyzes historical trends and forecasts of spill risks in coastal counties along the U.S. Pacific, including Alaska and Hawaii. The method calculates spill impact, which rises with size but diminishes with age and distance from the coast. Over the past two decades, spill risks in California and Washington have increased significantly. Coastal counties in Puget Sound and San Francisco Bay have seen the highest increases, surpassing 2000 levels by 79 % and 39 %, respectively. Alaska experienced a moderate rise, while Oregon and Hawaii had smaller but noteworthy increases. Ocean currents may reduce risk by 38 % on average. Most counties are expected to experience increasing spill risks, particularly in Southern California and Southwest Washington, which could see nearly a 50 % increase by 2033 compared to present levels. These findings can help coastal zone monitoring and inform policies for protecting coastal regions, regulating marine transportation and reducing spill vulnerability.

Distribution and abundance of oil-degrading bacteria in seawater of the Yellow Sea and Bohai Sea, China

Petroleum hydrocarbons are widespread in seawater. As an important sea area in northern China, the content and distribution of petroleum hydrocarbons in seawater need our attention because of the high toxicity and lasting polluting effects on the ecological environment of the Yellow Sea and Bohai Sea. In addition, there are few reports comparing the diversity of oil-degrading bacteria before and after enrichment. Therefore, we collected surface seawater from 10 sites in the Yellow Sea and Bohai Sea in the autumn of 2020 to study the distribution characteristics of total petroleum hydrocarbons (TPH) and the diversity of oil-degrading bacteria. The concentration of TPH was 81.65 μg/L-139.55 μg/L at ten sites in the Bohai Sea and the Yellow Sea, which conformed to the China Grade II water quality standard (GB3097-1997). Moreover, the pristine/phytane (PR/PH) value of most sites was close to 1, indicating that the area was obviously polluted by exogenous petroleum hydrocarbons. We found that oil-degrading bacteria in the seawater of the Yellow Sea and the Bohai Sea had a good degradation effect on C11-C14 short chain alkanes (degradation rate of 59.19-73.22 %) and C1-C4 phenanthrene (degradation rate of 48.19-60.74 %). In terms of the diversity of oil-degrading bacteria, Gammaproteobacteria and Alphaproteobacteria dominated the enriched bacterial communities. Notably, the relative abundance of Alcanivorax changed significantly before and after enrichment. We proposed that surface seawater in the Bohai Sea and Yellow Sea could form oil-degrading bacteria mainly composed of Alcanivorax, which had great potential for oil pollution remediation.

Quantitative ecological risk assessment of oil spills: The case of the Fernando de Noronha Archipelago

The upward trend in maritime oil transport increases the risk of oil spills, which have the potential to cause considerable damage to the marine environment. Therefore, a formal approach to quantify such risks is required. In mid-2010, a conservative Quantitative Ecological Risk Assessment based on population modeling, was performed in the Fernando de Noronha Archipelago. In this research, we enhance a previous assessment using the following models: (i) a Lagrangian approach to perform oil spill simulations, and (ii) the estimated frequency of accidents aggregating databases and expert opinions through a Bayesian-based method. Then, we quantify ecological risks as probabilities of half loss (i.e., 50 % population size decline) of a representative species of the archipelago's ecosystem. The results are summarized into risk categories to be straightforwardly communicated to the general public and provide reliable information that can aid decision-makers in coping with these events.

Biodegradation of oil-contaminated aqueous ecosystem using an immobilized fungi biomass and kinetic study

Remediation of environmental oil pollution with the usage of fungal organisms has proven to be a successful cleanup bioremediation method for organic contaminants. To investigate the breakdown of oil pollutants in water environments, biosurfactant-producing fungi have been isolated from oil-polluted soil samples. 16s rRNA sequencing technique was performed to identify the fungal organism and phylogenetic tree has been constructed. A variety of biosurfactant screening tests have demonstrated the better biosurfactant producing ability of fungi. The emulsion's stability, which is essential for the biodegradation process, was indicated by the emulsification index of 68.48% and emulsification activity of 1.3. In the isolated biosurfactant, important functional groups such as amino groups, lipids, and sugars were found according to thin layer chromatography analysis with a maximum retention value of 0.85. A maximum oil degradation of around 64% was observed with immobilized beads within 12 days. The half-life, and degradation removal rate constant of 20.21 days and 0.03 day^-1, respectively, have been determined by the degradation kinetic analysis. GCMS analysis confirmed the highly degraded hydrocarbons such as nonanoic acid and pyrrolidine. The immobilized fungi exhibit better oil biodegradability in aqueous solutions.

Risk assessment of marine oil spills using dynamic Bayesian network analyses

Oil spills are serious threats to the marine ecosystem. Especially when an oil spill is faced with extreme weather, the consequences might be more severe. Until now, no such researches focus on the risk of these extreme scenarios. This paper proposes a novel dynamic assessment method to quantify the risk of oil spills in extreme winds based on dynamic Bayesian networks (DBNs). The physical models of advection, spreading, evaporation, and dispersion are transformed into DBNs, and the vulnerability model is established according to coastline types and socio-economic resources. By integrating all the sub-models, the overall DBN to quantify the dynamic risk of oil spills occurring in extreme winds is obtained. The proposed method is demonstrated by the Laizhou Bay. The developed model is validated by a three-axiom-based approach. Temporal and spatial dynamics of risk caused by oil spills in potential locations could be calculated. Based on the developed DBN, the risk of the Laizhou Bay coast caused by oil spills in annual extreme wind speeds corresponding to different mean recurrence intervals is studied. In addition, the effects of the occurrence time of annual extreme winds are also researched.

Exploration of Super-Gravity Rapid Dissolution Method of Polymer for Offshore Oil Repellent

The long dissolution time and large dispensed volumes of oil repellent polymers in offshore oil fields lead to a great increase in the volume and number of dissolution and maturation tanks in the polymer formulation system. However, there is limited space and load-bearing capacity at the offshore platform and only a small space is available for the dispensing system. To further optimize the polymer dispensing system and reduce its floor space, the super-gravity technology may be considered as a way to speed up the dissolution of the polymer. The mechanism of super-gravity rapid dissolution was investigated by establishing mathematical models and with indoor experiments. The effects of filler pore size and super-gravity factor on polymer dissolution time and solution viscosity were investigated using the super-gravity rapid dissolution device, then combined with established graded forced stretching devices for field magnification experiments. The results indicated that the super-gravity method can substantially shorten the polymer dissolution time. The basic dissolution time of the polymer AP-P4 was shortened by 35 min compared with the conventional formulation method after use of the super-gravity rapid dissolution device. The optimal process conditions for the preparation of polymer solution by the super-gravity rapid dissolution device were selected as the optimal super-gravity factor range of 1031~1298.

Climate Change Impacts on Coastal and Offshore Petroleum Infrastructure and the Associated Oil Spill Risk: A Review

Climate change has been observed worldwide in recent decades, posing challenges to the coastal and offshore oil and gas infrastructure. It is crucial to identify how climate change affects these infrastructures and the associated oil spill risk. This paper provides an analysis of the vulnerability of coastal and offshore oil and gas infrastructure in response to climate change. The paper examines oil spill incidents worldwide and addresses climate change’s possible influences on oil spill risk. Moreover, available oil spill modeling and decision support tools for oil spill response are reviewed considering climate change. The paper signals the need for emerging decision and modeling tools considering climate change effects, which can help decision-makers to evaluate the risk on time and provide early warnings to adapt or prevent the unforeseen impacts on the oil industry partially resulting from global warming, including oil spill accidents.

Oil Spill Environmental Risk Assessment and Mapping in Coastal China Using Automatic Identification System (AIS) Data

The rapid expansion in shipping traffic, oil tankers, and oil field exploration in coastal and marine areas has, inevitably, resulted in the occurrence of many oil spill accidents. Oil spill accidents, which cause serious socio-economic, health, and environmental risks in coastal and marine areas, are a global concern. An oil spill pollution risk distribution map, combining multiple spill sources, is an effective tool by which to identify high-risk areas, which may help decision-makers in adopting contingency response and integrated coastal management. However, the assessment of oil spill distribution and risk assessment has been restricted, due to their heavy dependence on laboratory experiments and model simulations lacking reliable shipping data, which often derive inaccurate mapping results. This study combines the automatic identification system (AIS) and other data to precisely quantify the spatial extent of accident risk in coastal China. Based on oil quantity, oil spill rate, and accident probability, the ship, oil storage tank, submarine pipeline, and oil platform accidents spill risk index is analyzed. Next, combined with the sensitive degree of a coastal area, considering environmental and social issues, the oil spill environmental risk index is calculated. The oil spill pollution risk level is classified into five categories based on the oil spill pollution risk index, namely the low-risk zone, relatively low-risk zone, moderate-risk zone, relatively high-risk zone, and high-risk zone. The relatively high oil spill environmental risk concentration zone is located in the Bohai Sea, inter-border area between the Yellow Sea and Bohai Sea, the Yangtze River estuary, south of the Taiwan Strait, and the Pearl River estuary. The high-risk zone in the Bohai Sea is 36,018 km2 in area, with an average risk value of 32.23, whereas the high-risk area in the Pearl River estuary is only 14,007 km2. The high-risk area proportions in Tianjin are 23.5%, while those in Fujian, Hainan, Jiangsu, and Guangxi are very low. The low-risk area proportion in Hainan Province is 62%, while the value in Tianjin is only 2.9%. This study will be helpful in assisting decision-makers in mapping the influence area of oil spills and adopting the important strategies and effective management and conservation countermeasures for ship accidents in the coastal areas of China.

Review on the contamination and remediation of polycyclic aromatic hydrocarbons (PAHs) in coastal soil and sediments

The rapid economic and population growth in coastal areas is causing increasingly serious polycyclic aromatic hydrocarbons (PAHs) pollution in these regions. This review compared the PAHs pollution characteristics of different coastal areas, including industrial zones, commercial ports, touristic cities, aquacultural & agricultural areas, oil & gas exploitation areas and megacities. Currently there are various treatment methods to remediate soils and sediments contaminated with PAHs. However, it is necessary to provide a comprehensive overview of all the available remediation technologies up to date, so appropriate technologies can be selected to remediate PAHs pollution. In view of that, we analyzed the characteristics of the remediation mechanism, summarized the remediation methods for soil or sediments in coastal areas, which were physical repair, chemical oxidation, bioremediation and integrated approaches. Besides, this review also reported the development of new multi-functional green and sustainable systems, namely, micro-nano bubble (MNB), biochar, reversible surfactants and peracetic acid. While physical repair, expensive but efficient, was regarded as a suitable method for the PAHs remediation in coastal areas because of land shortage, integrated approaches would produce better results. The ultimate aim of the review was to ensure the successful restructuring of PAHs contaminated soil and sediments in coastal areas. Due to the environment heterogeneity, PAHs pollution in coastal areas remains as a daunting challenge. Therefore, new and suitable technologies are still needed to address the environmental issue.

Game analysis of nuclear wastewater discharge under different attitudes: Seeking a potential equilibrium solution

Marine pollution is an increasingly dangerous problem, affecting people across the world. Japan's decision on 13 April 2021 to discharge nuclear wastewater into the sea has aroused the close attention of interest-related countries. To resolve conflicts among various countries and achieve the harmonious development of the marine and economic environment, we employ the static game, the rank-dependent expected utility (RDEU) game, and the sequential game to comprehensively analyze the equilibrium strategies of discharge country and interest-related countries under different situations. Our analysis reveals that in the static game and sequential game where interest-related countries make decisions first, the discharge behavior of the discharge country should be restricted from the perspective of the internal and external benefits of the discharge country. In addition, when integrating changes in emotion into the game, it can be found that the most expected emotional state to prevent the discharge country from discharging nuclear wastewater for interest-related countries is to remain pessimistic. Overall, this study provides important implications for inter-state relations and environmental protection.

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.

A Mini Review: Application Progress of Magnetic Graphene Three-Dimensional Materials for Water Purification

Marine oil pollution, colored counterattacks, and heavy metal ions in the water will cause serious environmental problems and threaten human health. The three-dimensional material prepared by graphene, as a new nanomaterial, has a large specific surface area and surface chemical activity. Various impurities in the water can be absorbed, which is very suitable as a water purification material. Depositing Fe₃O₄ and other magnetic materials on graphene three-dimensional materials can not only increase recyclability but increase hydrophobicity. Therefore, magnetic graphene three-dimensional materials have a high potential for use in water purification. This article reviews the research progress and adsorption mechanism of magnetic graphene materials for water purification. Finally, the future research prospects of magnetic graphene materials have prospected.

Integrated environmental vulnerability to oil spills in sensitive areas

As the typical range of influence of oil spills surrounds urbanised and economically active areas, it is likely that fragile regions may not be part of the most vulnerable zones. This premise is remediated in this paper with the adoption of a vulnerability approach based on the integration of static and dynamic information, such as oil pollution susceptibility. Susceptibility is a poorly consolidated term and is often used as synonym for environmental sensitivity; it is considered here to be the distribution areas of oil slicks. To test the proposed approach, an integrated estimation of environmental vulnerability is carried out for an environmentally sensitive area in the south of Brazil by merging static data inherent to the medium with information of a dynamic nature related to trajectory, behaviour and the fate of oil at sea. Moreover, the oil pollution intensity and environmental sensitivity data in susceptible areas are addressed. Subsequently, the environmental vulnerability is estimated by integrating hazard maps, concentrations and losses of the mass of the oil slick, oil beaching time and the littoral sensitivity index hierarchy. Results will prove to be useful to highlight critical areas for which the highest levels of severity are expected, which can lead to improvements in decision-making processes to support oil-spill prevention, as well as improve response readiness, especially in developing countries that have historically under-protected their sensitive regions.

Selection of oil spill response method in Arctic offshore waters: A fuzzy decision tree based framework

A fuzzy decision tree (FDT) based framework was developed to facilitate the selection of suitable oil spill response methods in the Arctic. Hypothetical oil spill cases were developed based on six identified attributes, while the suitability of three spill response methods (mechanical containment and recovery, use of chemical dispersants, and in-situ burning) for each spill case was obtained based on expert judgments. Fuzzy sets were used to address the associated uncertainties, and FDTs were then developed through generating: i) one decision tree for all three response methods (FDT-AP1) and ii) one decision tree for each response method and the development of linear regression models at terminal nodes (FDT-LR). The FDT-LR approach exhibited higher prediction accuracy than the FDT-AP1 approach. A maximum of 100% accurate predictions could be achieved for testing cases using it. On average, 75% of suitable oil spill response methods out of 10,000 performed iterations were predicted correctly.

Estimating offshore exposure to oil spill impacts based on a statistical forecast model

A statistical oil spill risk forecast model in support of emergency response and environmental risk assessment is presented by combing the deterministic model, probabilistic strategy and frequency estimation. When applied to evaluate various potential spill sources (oil port, fairway, anchorage and pipeline) in the Zhoushan offshore area, the model provides the probability of slick spatial position, oil slick thickness, and exposure duration of floating slick. An oil spill risk map is generated after integrating multiple spill sources, which is a powerful tool for identifying high-risk areas and developing contingency plan. Impact scope and damage degree vary among different sources because of special local topographical, hydrological, and meteorological conditions, where generally exists high pollution intensity of point-source and wide range of line-source. Huge Changjiang River runoff prevents coastal sea in the north from being contaminated by spilled oil from the southern Zhoushan offshore area.

Variability of sea ice area in the Bohai Sea from 1958 to 2015

With the backdrop of continuous global change, it is beneficial to create consistent long-term records of sea ice area on regional scales for ice disaster prevention and risk mitigation. In this study, a piecewise multiple nonlinear regression model was developed to reconstruct long-term daily sea ice area dataset in the Bohai Sea from 1958 to 2015 by linking the related meteorological data and the satellite-derived ice area. The validation analysis show that related meteorological status corresponding to physical process had stable skill of predictive ability, which was able to account for 81% of the observational variance under consideration of sea ice state, freezing and melting phases. The reconstructed daily sea ice area dataset was further used to study the interannual and seasonal variability of sea ice area. The annual maximum ice area (AMIA) and the annual average ice area (AAIA) in the Bohai Sea exhibited a decreasing trend with fluctuation of -0.33 ± 0.18% yr^-1 and -0.51 ± 0.16% yr^-1 over the period of 1958-2015, respectively. The most obvious change of the Bohai Sea ice area occurred in time scale of ~30 years. The whole study period could be divided into slight increasing stage (1958-1980), significant decreasing stage (1980-1995), and moderate increasing stage (1995-2015). In most years, the annual changes of sea ice area showed an unimodal variation and the freezing period (~65 days) was longer than the melting phase (~40 days) due to the relatively higher freezing rate. In addition, high correlations between AAIA and Arctic Oscillation (AO) index (r = -0.60, p < .01) and North Atlantic Oscillation (NAO) index (r = -0.69, p < .01) from 1958 to 2015 suggested AO and NAO are the primary large-scale climate factors driving the sea ice variability in the Bohai Sea.