A COMPARATIVE RISK ASSESSMENT TECHNIQUE FOR TANKER OIL SPILLS

1979 ◽  
Vol 1979 (1) ◽  
pp. 37-43
Author(s):  
Halûk Özkaynak ◽  
Brian L. Murphy ◽  
Joel J. Watson
Keyword(s):  
Risk Assessment ◽  
Oil Spill ◽  
Oil Spills ◽  
Assessment Model ◽  
Traffic Density ◽  
Vessel Size ◽  
Oil Transport ◽  
Fleet Composition ◽  
The Matrix ◽  
Comparative Risk

ABSTRACT The tanker oil spill risk assessment model (TRAM) allows a user to investigate the way in which oil spill probabilities, and amounts spilled, vary with such factors as fleet composition, navigational aids, or particular properties of the route. Such a comparison of alternatives is generally required for an environmental impact statement. TRAM operates through multiplication of a series of matrices: P, Q, R, and S. The rows and columns of all matrices are parameterized by accident type (such as collision or grounding) and location (such as at a pier, or in a harbor). The probability of an accident (P) and of a spill following an accident (Q) are based on world tanker fleet data. The matrix S expresses the conditional probability that if there is a spill, the vessel will be a total loss. This enables catastrophic spills in which spill size can be related to vessel size to be distinguished from minor spills in which vessel size is generally not a factor. The matrix R contains most of the unique features of the model. It accounts for vessel and route-specific features that reasonably may be expected to alter the world tanker fleet data. Examples are given from the literature for the elements of R corresponding to: fleet composition (domestic/foreign carrier); navigation aids such as vessel traffic system; vessel age, and construction (double hull, inerting system, segregated ballast, etc.); and various features of the tanker route, such as channel width and traffic density, based on Macduff's causation probability formalism. The practical usage of the model is demonstrated by applying it to a hypothetical project involving tanker oil transportation. The extension of this analysis technique to other forms of risk analysis studies (including operations other than oil transport) is also discussed.

scholarly journals Approaches and Application of Comparative Risk Assessment Concepts to Oil Spill Preparedness Planning and Response

2003 ◽  
Vol 2003 (1) ◽  
pp. 59-61 ◽  
Author(s):  
Igor Linkov ◽  
Jim R. Clark
Keyword(s):  
Risk Assessment ◽  
Oil Spill ◽  
Oil Spills ◽  
Cost Benefit ◽  
Environmental Policies ◽  
Comparative Risk Assessment ◽  
Preparedness Planning ◽  
Benefit Evaluation ◽  
Comparative Risk ◽  
The Cost

ABSTRACT Comparative Risk Assessment (CRA) is emerging as a methodology that may be applied to facilitate decision-making when various possible activities compete for limited resources. The CRA framework may be an especially valuable tool for prioritization of remediation efforts and for making choices among various environmental policies specific to oil industry operations. This paper will show that CRA is an efficient and cost-saving tool that assists in developing oil spill response priorities based on the broadest possible range of concerns and issues important to all stakeholders. In addition, the CRA approach allows the cost/benefit evaluation of alternative environmental policies and strategies relative to the baseline risks and disruptions associated with oil spills (as well as other costs and benefits of petroleum use).

A Maritime Oil Spill Risk Assessment Model

2001 ◽  
Vol 2001 (1) ◽  
pp. 235-240 ◽  
Author(s):  
Lalit Yudhbir ◽  
Eleftherios Iakovou
Keyword(s):  
Risk Assessment ◽  
Oil Spill ◽  
Oil Spills ◽  
Transportation Network ◽  
Coast Guard ◽  
Maritime Transportation ◽  
Assessment Model ◽  
Risk Assessment Model ◽  
Case Scenario ◽  
Oil Transportation

ABSTRACT Mantime oil transportation decision-making models that integrate with oil spill risk assessment methodologies are scarce. Recently, first time quantitative efforts have been developed for the maritime transportation of petroleum products. However, there still exists a serious gap in the literature concerning risk assessment models that provide a rather significant input to any maritime oil transportation model, namely the estimation and assignment of risk costs to the links of such a network. The authors first present a critical review of oil spill risk assessment efforts found in the literature and then the development of a novel oil spill risk assessment model. The goal of this risk assessment methodology is twofold: first, to determine and assign risk costs to the links of a maritime transportation network, and second, to provide insights into contributors that lead to spills. Such insights may further lead to guidelines for the prevention of future incidents leading to spills. A federal regulatory agency (such as the U.S. Coast Guard) and/or a commercial shipper may use the identification of the dominant contributors to oil spills to evaluate the merits of alternative regulatory and shipping policies that could lead to improved safety performance of the marine system. The authors finally exhibit the usage of the proposed methodology on a real case scenario.

scholarly journals Risk assessment of oil spill accidents

2014 ◽  
Vol 16 (4) ◽  
pp. 743-752 ◽  
Keyword(s):  
Oil Spill ◽  
Oil Spills ◽  
Stochastic Approach ◽  
Assessment Model ◽  
Joint Research ◽  
Water Currents ◽  
Oil Transport ◽  
Oil Slick ◽  
Maritime Traffic ◽  
Joint Research Project

<div> <p>The objective of this study is to present an integrated stochastic approach for quantifying the risk of oil spill in marine waters and adjacent coasts. This was achieved via the effective cooperation between the National Technical University of Athens (NTUA) and the Bogazici University (BU) within the framework of a bilateral joint research project. The proposed methodology integrates four models: (1) a physics-based hydrodynamic model (HYM) which computes the spatial distribution of surface water currents as the main driving force for oil transport, (2) an expert-based accident assessment model (<st1:stockticker w:st="on">AAM</st1:stockticker>) to compute the frequency, location and characteristics of expected oil spills, (3) a physics-based oil spill model (<st1:stockticker w:st="on">OSM</st1:stockticker>) which computes the propagation and fate of the oil slick, and (4) an expert-based impact assessment model (IAM) to compute the distribution of coastal impact due to oil contamination. The model is applied to two pilot areas: the Saronicos Gulf, Greece and Izmir Bay, Turkey. The flow fields in these areas were determined by the HYM for a large number of wind scenarios, based on which the transport and weathering of an oil slick were computed by the <st1:stockticker w:st="on">OSM</st1:stockticker>. The most probable oil spill locations were identified by <st1:stockticker w:st="on">AAM</st1:stockticker> based on the bathymetry, the maritime traffic and the currents. Finally, the IAM was applied to draw Coastal Oil Impact Maps in the regions of interest. Emphasis was placed on the presentation of the risk of oil reaching the coastline. Environmental sensitivity and economic importance were taken into account by assigning index values to all coastal cells.&nbsp;</p> </div> <p>&nbsp;</p>

Oil spill risk assessment for a Single Buoy Mooring terminal in the Port of Taranto (Southern Italy)

2021 ◽  
Author(s):  
Svitlana Liubartseva ◽  
Ivan Federico ◽  
Giovanni Coppini ◽  
Rita Lecci
Keyword(s):  
Risk Assessment ◽  
Oil Spill ◽  
Oil Spills ◽  
Cost Benefit Analysis ◽  
Cost Benefit ◽  
Oil Refinery ◽  
Plant Oil ◽  
Contamination Assessment ◽  
Subsea Pipeline ◽  
Oil Pipeline

&lt;p&gt;Being situated in a semi-enclosed Mediterranean lagoon, the Port of Taranto represents a transport, industrial and commercial hub, where the port infrastructure, a notorious steel plant, oil refinery and naval shipyards coexist with highly-dense urban zone, recreation facilities, mussel farms, and vulnerable environmental sites. A Single Buoy Mooring in the center of the Mar Grande used by tankers and subsea pipeline that takes oil directly from tanker to refinery are assumed to stay at risk of accidental oil spills, despite significant progress in technology and prevention.&lt;/p&gt;&lt;p&gt;The oil spill model MEDSLIK-II (http://medslik-ii.org) coupled to the high resolution Southern Adriatic Northern Ionian coastal Forecasting System (SANIFS http://sanifs.cmcc.it Federico et al., 2017) is used to model hypothetical oil spill scenarios in stochastic mode. 15,000+ hypothetical individual spills are generated from randomly selected start locations: 50% from a buoy and 50% along the subsea pipeline 2018&amp;#8211;2020. Individual spill scenario is based on a real crude oil spill caused by a catastrophic pipeline failure happened in Genoa in April 2016 (Vairo et al., 2017). The model outputs are processed statistically to represent quantitively: (1) timing of the oil drift; (2) hazard maps in probability terms at the sea surface and on the coastline; (3) oil mass balance; (4) local-zone contamination assessment.&lt;/p&gt;&lt;p&gt;The simulations reveal that around 48% of the spilled oil will evaporate during the first 8 hours after the accident. Being transported by highly variable currents and waves, the rest is additionally exposed to multiply reflections from sea walls and concrete wharfs that dominate in the study area. As a result, the oil will be dispersed almost isotropically in the Mar Grande, indicating a rather moderate or small level of concentrations over the minimum threshold values (French McCay, 2016).&lt;/p&gt;&lt;p&gt;We have concluded that at a probability of 50%, the first oil beaching event will happen within 14 hours after the accident. The most contaminated areas are predicted on and around the nearest Port berths, on the coastlines of the urban area and on the tips of the breakwaters that frame the Mar Grande openings. The remote areas of the West Port and Mar Piccolo are expected to be the least contaminated ones.&lt;/p&gt;&lt;p&gt;Results are applicable to contingency planning, ecological risk assessment, cost-benefit analysis, and education.&lt;/p&gt;&lt;p&gt;This work is conducted in the framework of the IMPRESSIVE project (#821922) co-funded by the European Commission under the H2020 Programme.&lt;/p&gt;&lt;p&gt;References&lt;/p&gt;&lt;p&gt;Federico, I., Pinardi, N., Coppini, G., Oddo, P., Lecci, R., Mossa, M., 2017. Coastal ocean forecasting with an unstructured grid model in the southern Adriatic and northern Ionian seas. Nat. Hazards Earth Syst. Sci., 17, 45&amp;#8211;59, doi: 10.5194/nhess-17-45-2017.&lt;/p&gt;&lt;p&gt;French McCay, D., 2016. Potential effects thresholds for oil spill risk assessments. Proc. of the 39 AMOP Tech. Sem., Environment and Climate Change Canada, Ottawa, ON, 285&amp;#8211;303.&lt;/p&gt;&lt;p&gt;Vairo, T., Magr&amp;#236;, S., Qualgliati, M., Reverberi, A.P., Fabiano, B., 2017. An oil pipeline catastrophic failure: accident scenario modelling and emergency response development. Chem. Eng. Trans., 57, 373&amp;#8211;378, doi: 10.3303/CET1757063.&lt;/p&gt;

scholarly journals Predicting the impact of future oil-spill closures on fishery-dependent communities—a spatially explicit approach

2019 ◽  
Author(s):  
Igal Berenshtein ◽  
Shay O’Farrell ◽  
Natalie Perlin ◽  
James N Sanchirico ◽  
Steven A Murawski ◽  
...  
Keyword(s):  
Oil Spill ◽  
Oil Spills ◽  
Transport Model ◽  
Gulf Coast ◽  
Three Dimensional ◽  
Management Tool ◽  
Spatially Explicit ◽  
Oil Transport ◽  
Fishing Fleets ◽  
The Impact

Abstract Major oil spills immensely impact the environment and society. Coastal fishery-dependent communities are especially at risk as their fishing grounds are susceptible to closure because of seafood contamination threat. During the Deepwater Horizon (DWH) disaster for example, vast areas of the Gulf of Mexico (GoM) were closed for fishing, resulting in coastal states losing up to a half of their fishery revenues. To predict the effect of future oil spills on fishery-dependent communities in the GoM, we develop a novel framework that combines a state-of-the-art three-dimensional oil-transport model with high-resolution spatial and temporal data for two fishing fleets—bottom longline and bandit-reel—along with data on the social vulnerability of coastal communities. We demonstrate our approach by simulating spills in the eastern and western GoM, calibrated to characteristics of the DWH spill. We find that the impacts of the eastern and western spills are strongest in the Florida and Texas Gulf coast counties respectively both for the bandit-reel and the bottom longline fleets. We conclude that this multimodal spatially explicit quantitative framework is a valuable management tool for predicting the consequences of oil spills at locations throughout the Gulf, facilitating preparedness and efficient resource allocation for future oil-spill events.

Enhanced Leak Detection Risk Model Development

2010 ◽  
Author(s):  
Lorna Harron ◽  
Rick Barlow ◽  
Ted Farquhar
Keyword(s):  
Risk Assessment ◽  
Risk Model ◽  
Risk Mitigation ◽  
Detection System ◽  
Leak Detection ◽  
Mitigation Strategies ◽  
Assessment Model ◽  
Flow Meter ◽  
The Matrix ◽  
Risk Mitigation Strategies

Increasing concerns and attention to pipeline safety have engaged pipeline companies and regulatory agencies to extend their approaches to pipeline integrity. The implementation of High Consequence Areas (HCAs) has in particular had an impact on the development of integrity management protocols (IMPs) for pipelines. These IMPs can require that a risk based assessment of integrity issues be applied to specific HCA risk factors. This paper addresses the development of an operational risk assessment approach for pipeline leak detection requirements for HCAs. A detailed risk assessment algorithm that includes 25 risk variables and 28 consequence variables was developed for application to all HCA areas. The significant likelihood and consequence factors were chosen through discussions with the Leak Detection Risk Assessment Model Working Group and subject matter experts throughout Enbridge. The leak detection algorithm focuses on sections of pipe from flow meter to flow meter, as these are the locations that impact the leak detection system used by Enbridge. Each section of pipe is evaluated for likelihood, consequence and risk. When a high or medium risk area has been identified, an evaluation of potential Preventive and Mitigative (P&M) measures will be undertaken. A P & M Matrix has been developed to identify potential mitigation strategies to be considered for higher risk variables, called risk drivers, in the model. The matrix has been developed to identify potential risk mitigation strategies to consider for each variable used in the HCA Leak Detection Risk Assessment. The purpose of the matrix is to guide the user to consider actions identified for variables that drive the risk for the particular location. Upon review of the matrix, the user determines feasibility of the risk mitigation strategies being considered to identify an action. The paper will describe the consultative process that was used to workshop the development of this algorithm. Included in this description is how the process addressed various methods of leak detection across a wide variety of pipelines. The paper closes with “development challenges” and future steps in applying operation risk assessment techniques to mainline leak detection risk management.

A Comparative Risk Assessment for Listeria monocytogenes in Prepackaged versus Retail-Sliced Deli Meat

2010 ◽  
Vol 73 (4) ◽  
pp. 612-619 ◽  
Author(s):  
SARAH ENDRIKAT ◽  
DANIEL GALLAGHER ◽  
RÉGIS POUILLOT ◽  
HEATHER HICKS QUESENBERRY ◽  
DAVID LaBARRE ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Sensitivity Analysis ◽  
Listeria Monocytogenes ◽  
Shelf Life ◽  
Risk Ratio ◽  
Growth Inhibitor ◽  
Assessment Model ◽  
Growth Inhibitors ◽  
Comparative Risk ◽  
Inspection Service

Deli meat was ranked as the highest-risk ready-to-eat food vehicle of Listeria monocytogenes within the 2003 U.S. Food and Drug Administration and U.S. Department of Agriculture, Food Safety and Inspection Service risk assessment. The comparative risk of L. monocytogenes in retail-sliced versus prepackaged deli meats was evaluated with a modified version of this model. Other research has found that retail-sliced deli meats have both higher prevalence and levels of L. monocytogenes than have product sliced and packaged at the manufacturer level. The updated risk assessment model considered slicing location as well as the use of growth inhibitors. The per annum comparative risk ratio for the number of deaths from retail-sliced versus prepackaged deli meats was found to be 4.89, and the per-serving comparative risk ratio was 4.27. There was a significant interaction between the use of growth inhibitors and slicing location. Almost 70% of the estimated deaths occurred from retail-sliced product that did not possess a growth inhibitor. A sensitivity analysis, assessing the effect of the model's consumer storage time and shelf life assumptions, found that even if retail-sliced deli meats were stored for a quarter of the time prepackaged deli meats were stored, retail-sliced product is 1.7 times more likely to result in death from listeriosis. Sensitivity analysis also showed that the shelf life assumption had little effect on the comparative risk ratio.

Development and application of oil-spill risk assessment model for offshore pipeline

2014 ◽  
Vol 13 (3) ◽  
pp. 415-420 ◽  
Author(s):  
Yan Lu ◽  
Jia Wang ◽  
Wenpu Wei ◽  
Yong Yang ◽  
Wei An
Keyword(s):  
Risk Assessment ◽  
Oil Spill ◽  
Assessment Model ◽  
Risk Assessment Model ◽  
Offshore Pipeline

scholarly journals A guide to toxicity assessment and monitoring effects at lower levels of biological organization following marine oil spills in European waters

2010 ◽  
Vol 67 (6) ◽  
pp. 1105-1118 ◽  
Author(s):  
C. Martínez-Gómez ◽  
A. D. Vethaak ◽  
K. Hylland ◽  
T. Burgeot ◽  
A. Köhler ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Oil Spill ◽  
Oil Spills ◽  
Biological Effects ◽  
Toxicity Assessment ◽  
Biological Organization ◽  
Marine Oil ◽  
Assessment And Monitoring ◽  
Marine Oil Spills ◽  
Selection Of

Abstract Martínez-Gómez, C., Vethaak, A. D., Hylland, K., Burgeot, T., Köhler, A., Lyons, B. P., Thain, J., Gubbins, M. J., and Davies, I. M. 2010. A guide to toxicity assessment and monitoring effects at lower levels of biological organization following marine oil spills in European waters. – ICES Journal of Marine Science, 67: 1105–1118. The usefulness of applying biological-effects techniques (bioassays and biomarkers) as tools to assist in evaluating damage to the health of marine ecosystems produced by oil spills has been demonstrated clearly during recent decades. Guidelines are provided for the use of biological-effects techniques in oil spill pollution monitoring for the NE Atlantic coasts and the NW Mediterranean Sea. The emphasis is on fish and invertebrates and on methods at lower levels of organization (in vitro, suborganismal, and individual). Guidance is provided to researchers and environmental managers on: hazard identification of the fuel oil released; selection of appropriate bioassays and biomarkers for environmental risk assessment; selection of sentinel species; the design of spatial and temporal surveys; and the control of potential confounding factors in the sampling and interpretation of biological-effects data. It is proposed that after an oil spill incident, a monitoring programme using integrated chemical and biological techniques be initiated as soon as possible for ecological risk assessment, pollution control, and monitoring the efficacy of remediation. This can be done by developing new biomonitoring programmes or by adding appropriate biological-effects methods to the existing monitoring programmes.

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