Oil spill trajectory modelling and environmental vulnerability mapping using GNOME model and GIS

Mapping the shoreline risk assessment of oil spill in the eastern region of Qeshm channel

The northern shores of the Strait of Hormuz constitute one of the most diverse shorelines in the Persian Gulf, characterized by both utility and environmental richness. Situated in the Qeshm channel, which hosts the largest mangrove habitat, major industries, and commercial port, these shores are subject to the occurrence of oil spills, posing potential substantial harm. This study employs General NOAA Operational Modeling Environment (GNOME) and numerical modeling to assess the potential risks to shorelines from hypothetical oil spills, considering the distinctive features of the shores and their environmental sensitivity. The results indicate that high-risk levels are not excessively prevalent overall and are confined to approximately 24 km. The shape of the channel and hydrodynamic conditions highlight the eastern sector of the Bandar Abbas urban area as particularly susceptible to oil spill entrapment. The findings indicate that high-risk areas are predominantly located away from industrial-oil shores and primarily consist of muddy shores. Therefore, internal strategies of Oil Spill Contingency Plan (OSCP) of companies are deemed insufficient and necessitate comprehensive planning initiatives.

A multi-criteria simulation-optimization coupling approach for effective emergency response in marine oil spill accidents

Effective marine oil spill responses are vital to reduce environmental, societal, and economic damage. This study developed a Multi-Criteria Emergency Response System (MC-ERS) to comprehensively evaluate response efficiency, operational costs, and environmental losses. The proposed system integrates dynamic multiphase simulation of oil weathering and oil cleanup processes and further provides effective planning for multi-stage resource allocation through system optimization. The developed weight-sum model improved the performance of response operations by reducing the complexity of multi-criteria decision-making. Particle Swarm Optimization (PSO) was chosen as the foundational optimization algorithm due to its efficiency in rapid convergence and suitability for complex problems. From extensive comparisons of PSO variants across benchmark functions and inertia strategies, the C-PSO algorithm was developed, demonstrating enhanced optimization performance for MC-ERS. The developed modelling system performance was demonstrated and evaluated through a representative case study. The optimization plan coordinated resource allocation from onshore warehouses to harbors and spill sites, balancing oil recovery efficiency, costs, and ecological losses. Optimized results indicate an oil recovery of up to 76.50% in five days. Additionally, the system cuts costs by 3.45% and environmental losses by 15.75%. The findings enhance the efficiency of marine oil spill emergency response and provide support for such incidents.

Modeling study on oil spill transport in the Great Lakes: The unignorable impact of ice cover

The rise in oil trade and transportation has led to a continuous increase in the risk of oil spills, posing a serious worldwide concern. However, there is a lack of numerical models for predicting oil spill transport in freshwater, especially under icy conditions. To tackle this challenge, we developed a prediction system for oil with ice modeling by coupling the General NOAA Operational Modeling Environment (GNOME) model with the Great Lakes Operational Forecast System (GLOFS) model. Taking Lake Erie as a pilot study, we used observed drifter data to evaluate the performance of the coupled model. Additionally, we developed six hypothetical oil spill cases in Lake Erie, considering both with and without ice conditions during the freezing, stable, and melting seasons spanning from 2018 to 2022, to investigate the impacts of ice cover on oil spill processes. The results showed the effective performance of the coupled model system in capturing the movements of a deployed drifter. Through ensemble simulations, it was observed that the stable season with high-concentration ice had the most significant impact on limiting oil transport compared to the freezing and melting seasons, resulting in an oil-affected open water area of 49 km2 on day 5 with ice cover, while without ice cover it reached 183 km2. The stable season with high-concentration ice showed a notable reduction in the probability of oil presence in the risk map, whereas this reduction effect was less prominent during the freezing and melting seasons. Moreover, negative correlations between initial ice concentration and oil-affected open water area were consistent, especially on day 1 with a linear regression R-squared value of 0.94, potentially enabling rapid prediction. Overall, the coupled model system serves as a useful tool for simulating oil spills in the world's largest freshwater system, particularly under icy conditions, thus enhancing the formulation of effective emergency response strategies.

Mapping pollution dynamics: utilizing GNOME to model oil spill trajectories in tanker terminals

The aim of this study is to uncover the multifaceted environmental threats posed by Oil Spill Water Pollution (OSWP) originating from tanker terminals situated in the Qeshm and Hormozgan regions of Iran. In this region, water pollution arises from diverse sources, mostly from ruptured pipelines, corroded valves, unforeseen accidents, and aging facilities. The Qeshm Canal and Qeshm Tanker Terminal emerged as pivotal sites for investigation within this study. The focus is directed towards pinpointing vulnerable areas at risk of water contamination and delving into the intricate pathways and impacts associated with oil spills. Utilizing the sophisticated modeling capabilities of the National Oceanic and Atmospheric Administration's (NOAA) GNOME model, the research explores various scenarios extrapolated from seasonal atmospheric and oceanic data through 2022. The findings show the OSWP hazard zones located northeast of Qeshm. Notably, the wind and currents greatly affect how OSWPs are destined and dispersed. This underscores the intricate interplay between environmental factors and spill dynamics. In essence, this study not only sheds light on the imminent environmental threats posed by OSWP but also underscores the critical need for proactive measures and comprehensive strategies to mitigate the adverse impacts on marine ecosystems and coastal communities.

Oil spill environmental sensitivity mapping of Rio de Janeiro, Brazil

The current case study focuses on the Environmental Sensitivity Index (ESI) mapping of Guanabara Bay, Rio de Janeiro, Brazil - a region at risk from petroleum sector pollution. By mapping 981.5 km of coastline and classifying it in 10 oil sensitivity indices, we integrated biotic resources, socioeconomic attributes, and geoenvironmental diversity into a georeferenced database. Results reveal a high oil sensitivity of the bay, with approximately 89 % of the mapped coast scoring ESI 8 and ESI 10. These scores comprise, respectively, estuarine and solid substrate habitats that are sheltered from wave action. Notably, numerous manufacturing and oil handling plants, along with intensive urbanization, also contribute to the bay's oil sensitivity. Additionally, the rich biotic diversity in the study area, particularly in protected areas housing 79 conservation units, further amplifies its environmental vulnerability. This study aims to serve as a reference for detailed ESI mapping of coastal areas in tropical rainy zones with significant environmental diversity, industrial development, and a dense population.

A hybrid Monte Carlo simulation risk model for oil exploration projects

A new 3-D Hybrid Monte Carlo Simulation (MCS) Risk Model is proposed in this study. The wind, wave, current, climate change, and tsunami sub-models of the Three-Dimensional Hydrodynamic Transport and Water Quality Model HYDROTAM-3D are interrelated with MCS, to obtain probability distributions for the simulation of environmental conditions. This is the only model that can incorporate the tsunami, storm, and sea level rise risks in oil exploration projects. The spill risk index (SRI) of 50 blue barrels spilled due to a blowout from the rig/port during fuel supply was circa 1 ton/ship as Tier I with an average annual occurrence probability of 1.0 × 10-6. The discharge of 4000 bbls for 6 h was modeled, resulting in the SRI of 546 metric tons from the riser blowout with SRI = 0.2 per meter, indicating a Tier II risk. The mean arrival time of this spill was found by MCS as 145 min.

Combined oil spill modelling and shoreline sensitivity analysis for contingency planning in the Irish Sea

Offshore oil spills often result in severe environmental and socio-economic consequences. This work focuses on a busy, yet poorly studied part of NW Europe, the Irish Sea, to assess the impact of future oil spills on the nearby coast. By integrating numerical models and shoreline sensitivity analyses for two confined areas, Liverpool Bay and Milford Haven, this work acknowledges wind direction and speed as principal controls on the movement of oil under winter/storm conditions and in shallow waters. Ocean currents play a secondary role, but are significant in deeper waters and in low-wind summer conditions. The temporal elements used in the modelling thus stress that when the spill occurs is just as important as where. As a corollary, the fate of spilled oil is determined in this work for distinct scenarios and types. Response strategies are recommended to minimise the impact of future spills on coastal populations.

Combined effects of chemical dispersant and suspended minerals on the dispersion process of spilled oil

The dispersion process of spilled oil is an important concern for the effective disposal of oil spills. The dispersed oil concentration and oil droplets size distribution were studied through a wave tank test under the application of chemical dispersant and suspended minerals. The results indicated that dispersant and minerals increased the dispersed oil concentration and the effect of dispersant was more significant, and they had a synergistic effect on oil dispersion. When dispersant and minerals were applied together, the volume mean diameter of oil droplets decreased in the first 30 min, then increased and reached a maximum value at 90-120 min, and decreased again. Moreover, suspended minerals could inhibit the coalescence of oil droplets. This study can afford data support for oil spill emergency response that occurs in inshore or estuaries.

Pseudomonas veronii strain 7-41 degrading medium-chain n-alkanes and polycyclic aromatic hydrocarbons

Pollution of the environment by crude oil and oil products (represented by various types of compounds, mainly aliphatic, mono- and polyaromatic hydrocarbons) poses a global problem. The strain Pseudomonas veronii 7-41 can grow on medium-chain n-alkanes (C₈-C₁₂) and polycyclic aromatic hydrocarbons such as naphthalene. We performed a genetic analysis and physiological/biochemical characterization of strain 7-41 cultivated in a mineral medium with decane, naphthalene or a mixture of the hydrocarbons. The genes responsible for the degradation of alkanes and PAHs are on the IncP-7 conjugative plasmid and are organized into the alk and nah operons typical of pseudomonads. A natural plasmid carrying functional operons for the degradation of two different classes of hydrocarbons was first described. In monosubstrate systems, 28.4% and 68.8% of decane and naphthalene, respectively, were biodegraded by the late stationary growth phase. In a bisubstrate system, these parameters were 25.4% and 20.8% by the end of the exponential growth phase. Then the biodegradation stopped, and the bacterial culture started dying due to the accumulation of salicylate (naphthalene-degradation metabolite), which is toxic in high concentrations. The activity of the salicylate oxidation enzymes was below the detection limit. These results indicate that the presence of decane and a high concentration of salicylate lead to impairment of hydrocarbon degradation by the strain.

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.

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.

DSS-OSM: An Integrated Decision Support System for Offshore Oil Spill Management

The marine ecosystem, human health and social economy are always severely impacted once an offshore oil spill event has occurred. Thus, the management of oil spills is of importance but is difficult due to constraints from a number of dynamic and interactive processes under uncertain conditions. An integrated decision support system is significantly helpful for offshore oil spill management, but it is yet to be developed. Therefore, this study aims at developing an integrated decision support system for supporting offshore oil spill management (DSS-OSM). The DSS-OSM was developed with the integration of a Monte Carlo simulation, artificial neural network and simulation-optimization coupling approach to provide timely and effective decision support to offshore oil spill vulnerability analysis, response technology screening and response devices/equipment allocation. In addition, the uncertainties and their interactions were also analyzed throughout the modeling of the DSS-OSM. Finally, an offshore oil spill management case study was conducted on the south coast of Newfoundland, Canada, demonstrating the feasibility of the developed DSS-OSM.

Assessing the coastal sensitivity to oil spills from the perspective of ecosystem services: A case study for Canada's pacific coast

Coastal environment is one of the most important ecological and socioeconomic areas. However, increasing energy demand and economic development lead to a continuous gas and oil exploration, production, and traffics, which notably raise the risk of oil spill accidents in coastal areas. Sensitivity assessment aiming to determine the coastal features that would be severely impaired by spill incidents is a crucial part of the response planning. In this study, an innovative framework for coastal sensitivity mapping that incorporated ecosystem service (ES) valuation and multidimensional assessment was proposed. Sensitivity was computed by valuing physical, biological, and social-economical indicators from ES perspective and separating each indicator into specific coastal domains. For different ES typologies, provisioning services contributed most to the overall ES value followed by culture services, supporting services, and regulating services. For ES value in different coastal domains, the highest value was recorded in the water column followed by water surface, shoreline, and seabed. However, the shoreline ranked highest regarding the ES value per ha. Sensitivity assessment revealed that sensitive areas differed in different domains, both in distribution and extent. Compared with the scoring method, the ES valuation method showed more coincidence with Ecologically and Biologically Significant Areas (EBSA), representing a more precise and practical approach for sensitivity assessment. A three-dimensional (3D) oil spill model was also applied to generate maps of oil contamination probability in shoreline, water surface, and water column. The obtained results highlighted the significance of incorporating different coastal domains into oil spill responses, and the urgent demand to broaden and deepen our understanding of ecological processes across the vertical coastal zones.