Oil Spill Source Research Articles

Sound uncertainty-based strategy for oil spill source identification

Oil spills are frequent and a major environmental threat, whether they are massive or small. Therefore, authorities and experts have developed analytical chemistry tools to identify spill sources and address these illegal acts by comparing oil patterns obtained by Gas Chromatography-Mass Spectrometry analysis of the spill (Sp) and suspected sources (SS) samples. Several methodologies have proposed different balances between data processing complexity and reliability. Supported by the accessibility and validity of Microsoft Excel spreadsheets, an alternative, accurate, and user-friendly tool was developed for spill source identification based on Monte Carlo Method (MCM) simulation of correlated oil components expressed by abundance ratio (DR). However, the statistical control of various DR and the degree of similarity of samples' compositions, at defined confidence levels, impact the probability of true and false composition equivalence claim of Sp and SS becoming a challenge to recognise the offender. This work not only compares the MCM and the conventional approaches allowing to highlight the limitations that result in evidence with greater uncertainty, but also offers a statistically sound strategy that manages the probabilities of a compositional equivalence claim assessing the ability to distinguish competing spill sources and reporting the most likely polluting source with reduced uncertainty. A decision chart proposed, based on objective and statistically sound criteria, indicates the performance of consecutive DR comparison trials if necessary. The target values established for the probability of compositional equivalence claim of the Sp and the first and second most likely SS (≥95.0 % and ≤0.50 %, respectively) provide to forensic experts’ sound evidence to be presented in court (likelihood ratio ≥190). This work represents a significant breakthrough in comparing complex chemical oil patterns.

A new ship tracing technology from oil spills based on multi-source data

Oil spill from ship can cause serious pollution to the Marine environment, but it is very difficult to find and confirm the troublemaker. In order to determine the oil spill ship, this paper proposes a new method to trace the source of ship oil spills and find the suspected ship that spills oil based on SAR imagery, AIS data and related marine environment data. First, we filter AIS data based on position of oil spill areas on remote sensing imagery and convert oil spill areas into trajectory points. Secondly, based on the Lagrangian particle motion model, a bidirectional drift model is proposed to calculate the average similarity between the forward and backward drift results. Finally, the most likely oil spill ship is determined according to the average similarity results. The results of the case study show that the method is effective and practical.

A review of oil spill dynamics: Statistics, impacts, countermeasures, and weathering behaviors

AbstractOil spills pose significant threats to marine and freshwater environments, impacting ecosystems and drinking water sources. The present review incorporated an up‐to‐date statistical analysis of the oil spills globally including the types and sources of oil spills and the main habitats affected by the past incidents. It presented immediate and long‐term effects on aquatic organisms and habitats highlighting the necessity for action to protect the aquatic environment. The paper also elucidated a range of effective remediation and cleanup methods, presenting a comprehensive toolkit to mitigate ecological damage. Noticeably, the review identified crucial knowledge gaps in the literature: (i) the absence of marine plastic pollution in studies on oil spill impacts and (ii) the absence of a modeling framework that considers the presence of microplastics in the spillage region and their impacts on the overall weathering rate. From synthesizing essential knowledge on oil spill dynamics and identifying the knowledge gap in the literature, this review aims to enhance understanding and guide future research.

Multi-USV cooperative oil spill source seeking via extremum seeking combined with information fusion

This paper addresses the issue of cooperative source seeking for oil spill pollution by multiple unmanned surface vehicles (USVs), where the oil spill plume propagation is modeled by a linear advection–diffusion equation in two-dimensional space. The main objective is to construct a cooperative source seeking scheme for a group of USVs in the framework of extremum seeking combined with information fusion to solve such cooperative source seeking problem. To do this, both a gradient-based control law and a formation control law are included in the cooperative source seeking scheme. The gradient-based control law that is constructed by extremum-seeking control combined with information fusion drives the multiple USVs to approach the oil spill source, where the gradient is estimated online via the extremum-seeking control and the fused concentration value that is derived via a linear H∞ filter from the local concentration measurements at the USV’s current position. In the source seeking process, the USVs driven by the formation control law based on the virtual structure method maintain a preset circular formation. The convergence performance of the cooperative source seeking scheme is analyzed rigorously by the Lyapunov method. Finally, extensive numerical simulations are included to validate the theoretical algorithm.

Forensic Geochemistry Reveals International Ship Dumping as a Source of New Oil Spill in Brazil's Coastline (Bahia) in Late 2023.

In the present study, we applied forensic geochemistry to investigate the origin and fate of spilled oils like tarballs stranded at the beaches of Bahia, in northeastern Brazil, in September 2023, based on their fingerprints. Saturated and aromatic compounds were assessed by gas chromatography, and the oceanic surface circulation patterns were deciphered to determine the geographic origin of the spill. Contamination by petroleum represents an enormous threat to the unique, species-rich ecosystems of the study area. The geochemical fingerprint of the oil spilled in 2023 did not correlate with those of previous events, including the one in 2019, the one in early 2022 in Ceará, and an extensive spill across the Brazilian Northeast in late 2022. However, the fingerprint did correlate with crude oils produced by Middle Eastern countries, most likely Kuwait. The oil of the 2023 spill had a carbonate marine origin from early mature source rocks. These findings, together with the moderate weathering of the 2023 tarballs and the ocean circulation patterns at the time of the event, indicate that the oil was discharged close to the shore of Brazil, to the east or southeast of Salvador, by a tanker on an international route in the South Atlantic.

Iterative data-driven construction of surrogates for an efficient Bayesian identification of oil spill source parameters from image contours

Iterative data-driven construction of surrogates for an efficient Bayesian identification of oil spill source parameters from image contours

Transboundary Environmental Harm and the Increasing Risk of Oil Spills and Marine Debris in the Semi-Enclosed Arafura and Timor Seas Region

The Arafura and Timor Seas (ATS) region is highly productive and rich in marine resources. With the growing population and economic progress of the region, diverse sources of pollution, including nutrients, oil spills, marine debris, and pesticides, among others have become major concerns. This paper focuses on oil spills from offshore rigs and marine debris, such as plastics and derelict fishing gears, as primary regional concerns. As demonstrated by the historic Montara Wellhead Platform Incident of 2009, an oil spill seriously threatens the region. The once called Joint Petroleum Development Area is analyzed as an oil pollution hotspot in the region. Marine debris, including shoreline and ocean debris (particularly fishing-related debris), is analyzed through various reports and historic vessel traffic data. As a result, the Aru Sea is identified as a seafloor debris hotspot. The lack of scientific data on shoreline debris limits specific hotspot identification, but this study recognizes an increasing trend of marine debris beached on the shores of the ATS countries. The study results emphasize the need to ratify the International Convention on Oil Pollution Preparedness, Response and Co-operation 1990 by the ATS countries, and recommend establishing a regional platform for oil spill preparedness and creating a regional marine debris monitoring program. Collaboration with regional organizations for capacity building on marine debris and oil spill response is also suggested.

Combined use of SAR images and numerical simulations to identify the source and trajectories of oil spills in coastal environments

Remote sensing data and numerical simulation are important tools to rebuild any oil spill accident letting to identify its source and trajectory. Through these tools was identified an oil spill that affected Oaxacan coast in October 2022. The SAR images were processed with a standard method included in SNAP software, and the numerical simulation was made using Lagrangian transport model included in GNOME software. With the combining of these tools was possible to discriminate the look-alikes from true oil slicks; which are the main issue when satellite images are used. Obtained results showed that 4.3m3 of crude oil were released into the ocean from a punctual point of oil pollution. This oil spill was classified such as a small oil spill. The marine currents and weathering processes were the main drivers that controlled the crude oil displacement and its dispersion. It was estimated in GNOME that 1.6 m3 of crude oil was floating on the sea (37.2 %), 2.4 m3 was evaporated into the atmosphere (55.8 %) and 0.3 m3 reached the coast of Oaxaca (7 %). This event affected 82 km of coastline, but the most important touristic areas as well as turtle nesting zones were not affected by this small crude oil spill. Results indicated that the marine-gas-pump number 3 in Salina Cruz, Oaxaca, is a punctual point of oil pollution in the Southern Mexican Pacific Ocean. Further work is needed to assess the economic and ecological damage to Oaxacan coast caused by this small oil spill.

Tar pollution event (2021) at the Southeastern Levantine oligotrophic basin, short-term impacts and operational oceanography perspectives

The Levantine basin (LB) in the Southeastern Mediterranean Sea is a high-risk oil pollution hot spot owing to its dense maritime traffic and intense oil and gas exploration and exploitation activities. In February 2021 the Israeli LB shorelines were impacted by an exceptional tar pollution event (~550 tons; average distribution: ~3 kg tar m−1 front beach) of an unknown oil spill source. Here we report on the immediate numerical modelling assessment of the oil spill propagation and tar distribution; operational use of underwater gliders for tracking water column anomalies of dissolved polycyclic aromatic hydrocarbons (PAHs) and turbidity signals; the beached tar composition and amounts and the short-term response of the microbial population along the ~180 km shoreline. This pollution event emphasizes the need for improving the early warning systems for oil spills and implementing continuous operational monitoring at high-risk, ecologically sensitive and valuable resource areas like the Israeli LB waters.

Tracking of oil spill extended targets based on random point pattern and GLMB

In the marine environment, oil spill surfaces exhibit complex drifting and spreading behavior, which makes it difficult to obtain the number of oil spill sources, as well as important parameters such as the location, shape, drifting speed and expansion rate of oil spill surfaces. Moreover, due to external factors such as sea winds, tides, and currents, multiple oil slicks may overlap and merge, making the accurate tracking of multiple oil spill surfaces even more difficult. To address the aforementioned issues, the proposed an oil spill extended target tracking method based on random point pattern and the Generalized Label Multi-Bernoulli (GLMB) filter. Firstly, to address the challenge of solving the parameters for the mixture distribution, the Expectation-Maximum (EM) algorithm of point pattern is introduced to obtain two types of parameters: cardinality distribution and feature distribution; Secondly, the GLMB filtering method is utilized to track the centroid drift trajectory of the oil spill while simultaneously recording information about the shape and concentration of the oil spill surface. Theoretical and simulation experiments demonstrate that the algorithm is capable of accurately estimating the parameters and state of the oil spill, with a tracking error precision of 0.001°(equivalent to 3.6′′ of Earth’s longitude and latitude). The final tests in the real water environment in the laboratory show that the tracking error of the oil spill surface is 0.4 cm, which proves the effectiveness and practicality of the algorithm.

A century-long record of polycyclic aromatic hydrocarbon deposition in the Old Yellow River Estuary, China

Polycyclic aromatic hydrocarbons (PAHs) are potential geochemical indicators for assessing the impact of human activities and can be used to reconstruct historical human activities. This study collected a 108 cm sediment core from the 5th lobe of the Yellow River Delta for the first time and analyzed the historical distribution characteristics of PAHs in this area. The results showed that the sedimentation history of the core was from 1908 to 2014. The average value of PAHs was 28.93 ng/g. Biomass and coal combustion sources were the main sources of PAHs in the low-value areas, while oil spill sources were the main sources in the significantly higher PAHs areas in the 1960s, mid-1980s, late 1990s, and late 2010s, which was consistent with the development history of Shengli Oilfield. Compared with global estuaries, the historical industrial activity intensity in this area was weaker.

Distribution and main sources of oil spills in the Persian Gulf based on satellite monitoring with synthetic aperture radar

ABSTRACT The Persian Gulf is characterized by a huge number of offshore oil and gas platforms, large number of many oil terminals, and busy shipping lines for supporting oil transportation. In this regard, developing various methods for assessing the oil pollution of the Gulf, including remote sensing, is extremely important. For the first time, synthetic aperture radar (SAR) images of the European Sentinel-1A and Sentinel-1B satellites were used routinely to monitor the entire Gulf in 2017–2019. To effectively analyse the SAR images and their detected dark patches, a monitoring method based on manual detection and all contextual information available using web-GIS approach, was used. This involved the creation of a dedicated geoportal with oceanographic, physical – geographical, industrial and navigational information on the water basin, including the offshore oil and gas infrastructure. Using this approach, as well as data from automatic ship identification system, most oil spills were detected, recognized and mapped. The summary oil spill distribution maps and main statistical results of the monitoring are presented and discussed. It is shown that the main sources of oil pollution in the Persian Gulf (oil slicks/spills from 0.5 to about 700 km2) are (in decreasing order) oil production, oil transportation, and local shipping.

Physicochemical Characteristics and Heavy Metals Assessment in Water and Sediments of Obodo Oilfield in Warri South Local Government Area of Delta State, Nigeria

This study investigated the physicochemical characteristics and heavy metals levels in water and sediments of Obodo Oilfield in Warri South Local Government Area of Delta State using standard laboratory-approved APHA and ASTM methods. Results indicated traces of heavy metals present in the water and sediments. Temperature and TDS in the water samples were within the DPR established limits while TSS, Chemical Oxygen Demand, Salinity and Biochemical Oxygen Demand were higher than the control and well above the DPR established limits. The heavy metals present in the soil were all still within the permissible DPR limits, except for Cadmium which was higher than the control and DPR established limit. The results showed that the water and soil within the environment may have been considerably polluted and degraded by the operations of oil and gas production in the region. The study recommends that the activities of the oil and gas production companies be checked to ensure they are operating within the environmental standard regulations of the country and that the Government and necessary bodies should be proactive in checkmating illegal bunkering activities as they have become the major source of oil spills in the region.

НЕФТЯНОЕ ЗАГРЯЗНЕНИЕ ОМАНСКОГО ЗАЛИВА ПО ДАННЫМ РАДИОЛОКАЦИОННОГО МОНИТОРИНГА ИЗ КОСМОСА

The results of satellite radar monitoring oil pollution in the Gulf of Oman carried out in the period from January 2017 to April 2020 are analyzed. Synthetic aperture radar (SAR) images from the European satellites Sentinel-1A and Sentinel-1B and a geoinformation approach were used for this that makes it possible to fairly unambiguously determine oil spill causes and their sources. During the monitoring 2584 oil spill patches was detected on 730 SAR images whose total area is about 4972 km2. It is shown that the main oil spill source in the Gulf of Oman is intensive shipping by sea, including the tanker fleet, and the United Arab Emirates waters and the approaches to the Strait of Hormuz turned out to be the most polluted waters of the gulf.

Spatial variation of coastal wetland vulnerability to oil spill stress in the Bohai Sea

Due to their position at the land–sea interface, coastal wetlands are extremely vulnerable to oil spills. However, few studies have focused on the vulnerability of coastal wetlands to oil spill hazards. In this study, we developed a spatial vulnerability approach and assessment based on the vulnerability scoping diagram in the Chinese Bohai Sea, where oil spill events are serious and frequent, and aimed to assess the spatial heterogeneity of the vulnerability of coastal wetlands under oil spill stress by integrating various indicators for exposure, sensitivity, and adaptive capacity into a composite index. This study normalized and aggregated data across sub-indices and combined related information with a geographic information system (GIS) model. The weighted results indicated that oil spill sources, as well as the natural environment in which the wetlands were located, dominated the degree of vulnerability of various coastal wetlands. The vulnerability assessment results suggest that there are obvious spatial variations among the different wetlands surrounding the Bohai Sea and each wetland had a different level of vulnerability, and highlights the need to enhance adaptive capacity to reduce vulnerability. This paper provides a quantitative assessment method for determining the spatial variation of coastal wetland vulnerability under oil spill stress, which can be used to better understand potential oil spill risks in coastal wetlands to support spill prevention and improve response readiness in the future.

Chemometric techniques in oil spill identification: A case study in Dalian 7.16 oil spill accident of China

Chemometric methods have unique advantages regarding comprehensive consideration of multiple parameters and the classification of samples or variables. Classification of oil spill sources was carried out by using chemometric techniques, such as Repeatability Limit, hierarchical cluster analysis (HCA), Student's t-test and Principal component analysis (PCA) Biplot. In addition, this paper takes the fingerprint identification of a Dalian “7.16″ oil spill accident as an example to illustrate the effectiveness of chemometric techniques in oil identification. PCA scores plot (explaining 82.77% of variance accounted for three PCs) showed that samples belong to four clusters and result of HCA method further confirmed that. The residual oil in Jinshatan Beach and Haibei Square may be caused by the explosion of Dalian “7–16” oil pipeline accident. The use of chemometric techniques is significant in providing independent validation for classifying the types of spilled oil in the investigation of oil spill pollution. The results will be of great significance to improve the accuracy and efficiency of oil spill identification based on oil fingerprint.

Estimates of the economic damages of an oil spill on the coast of Muara Gembong, Bekasi Regency, West Java, Indonesia

Coastal Muara Gembong is included in the Environmental Strategic Area, and the Natural Resources Strategic Area based on the Bekasi Regency Regional Spatial Plan 2011-2031. The Java Sea as the northern boundary of Bekasi Regency, one of the busy shipping routes originating from Tanjung Priok to Jayapura and Tanjung Priok to Surabaya, is the main source of oil spills that can occur around the coastal area of Muara Gembong. The coastal area of Muara Gembong has been affected by the Pertamina oil spill since July 21, 2019. The purpose of this study is to estimates the economic damages due to oil spills at Muara Gembong mangrove ecosystem. The economic damages are calculated by including two components, namely compensable value and recovery costs. Compensable value obtained by assessing natural resource damage, i.e. mangrove ecosystem, includes both the value of direct benefits and indirect benefits, which is IDR 497,519,413,897.09. The value of the recovery cost is IDR 40,611,959,689.98. So, the economic losses due to the oil spill on the Muara Gembong mangrove ecosystem is IDR 538,131,373,587.08. Along with these results, the government must also immediately be able to identify the impacts and calculate the value of losses or economic impacts to optimize the response to oil spill incidents.

Oil spills in the Barents Sea: The results of multiyear monitoring with synthetic aperture radar

This paper presents the results of multiyear satellite monitoring of oil pollution in the Barents Sea conducted in 2015–2020. Monitoring was based on synthetic aperture radar (SAR) images from the European Space Agency's Sentinel-1A and Sentinel-1B satellites. During monitoring, more than 26,000 SAR images were collected and analyzed for oil pollution in the form of oil spills. A geographic information system (GIS) and a conventional interactive technique were used to efficiently analyze a substantial number of SAR images covering the Barents Sea. Our approach employed online geoportal based on GIS technology with a large volume of additional information (oceanographic, physical-geographical, and industrial) about the marine basin, including those for offshore oil and gas infrastructure. As a result, multiyear oil spill distribution map was generated and analyzed, and the most oil-polluted regions of the sea and natural seeps were identified. The analysis focused on the general characteristics of the spatial and temporal distribution and the main sources of oil pollution of the Barents Sea. Sources of oil spills with areas ranging from 0.5 to 90 km2 were interpreted based on data from the automatic ship identification systems used to monitor shipping and fishing. Based on the monitoring results, the general level of oil pollution in the Barents Sea is established, statistics were calculated, and risk zones identified. The most polluted marine areas are in the southern part of the sea, where maritime shipping continuous; moderate levels of pollution appear in the fishing zones in the central part of the sea. Finally, the study results show that overall oil pollution in the Barents Sea is still relatively low compared to other marginal and inland seas of Europe.

Investigation of Petroleum Hydrocarbon Fingerprints of Water and Sediment Samples of the Nestos River Estuary in Northern Greece

The oil and gas industry is definitely considered the main contributor in the energy sector, acting as the lifeblood of our planet. However, environmental contamination by crude oil and petroleum products due to anthropogenic activities is of great concern. Nestos River springs from Bulgaria and has a total length of 234 km, from which 135 km belong on Greek land. It is globally recognized as nature’s miracle accommodating a variety of habitats, flora, and fauna species at the deltaic area protected by the RAMSAR Convention. In the current study, water and sediment samples from three different sites along the river course and other six sites of the delta region and the surrounding sea area were selected in order to investigate the potential environmental impact of the nearby oil and gas industry in the Prinos-Kavala basin that operates over 40 years. The samples were analyzed by fingerprinting techniques using gas chromatography-mass spectrometry. Crude oil samples and different petroleum products were also analyzed to disclose specific markers (biomarkers) that characterize the different sources of oil spills. The analytical data revealed that the distribution of biomarkers is a valuable tool in oil spill identification as well as in their correlation to suspected sources. Extract ion chromatograms of the reference samples showed significant differences in the distribution of n-alkane, isoprenoid, sterane, triterpane, and dibenzothiophene compounds. The results on the analyzed water and sediment samples bared no evidence of environmental hazards associated with the hydrocarbon exploration and production activities of the neighboring oil and gas company.

Year-to-year variability of oil pollution along the Eastern Arabian Sea: The impact of COVID-19 imposed lock-downs

This study investigated the year-to-year variability in the occurrence, abundance and sources of oil spills in the Eastern Arabian Sea (EAS) using sentinel-1 imagery and identified the potential oil spills vulnerable zones. The four consecutive year's data acquired from 2017 to 2020 (March–May) reveal three oil spill hot spot zones. The ship-based oil spills were dominant over zone's-1 (off Gujarat) and 3 (off Karnataka and Kerala), and the oil field based over zone-2 (off Maharashtra). The abundance of oil spills was significantly low in zone-1, only 14.30km2 (1.2%) during lock-down due to the covid-19 pandemic. Whereas, the year-to-year oil spills over zone's 2 and 3 are not significantly varied (170.29 km2 and 195.01 km2), further suggesting the influence of oil exploration and international tanker traffic are in operation during the lock-down. This study further recommends that manual clustering is the best method to study the distribution of unknown oil spills.