Risk analysis in maritime transportation : principles, frameworks and evaluation

Risk analyses are widely used tools for supporting decision making. Nonetheless, many criticisms have been raised against the discipline of risk analysis, e.g. technical analyses having a narrow focus, poorly examined claims of the ability of accurately measuring risk and lack of standards for quality assurance and risk analysis evaluation. In response to these criticisms, calls have been made for increased focus on these and other foundational issues, both in the general risk analysis discipline and in the various application areas. This thesis answers these calls for research addressing the underlying concepts and principles of risk analyses, which are approached through applications focusing on the accidental risk of maritime transportation. Focusing first on a set of foundational issues underlying waterway risk analyses, it is established that many different definitions, perspectives and scientific approaches co-exist in the application area. Through two case studies of reliability of maritime risk models, previous research claiming that risk models provide unreliable decision support, are confirmed for some maritime applications, thus confirming the need for focusing on risk related principles. Subsequently, a set of principles is presented, addressing concepts and terminology, risk and prediction, risk model use and the consideration of uncertainty and bias. A framework is introduced to communicate the scientific principles adhered to in a specific risk analysis. Following this, the principles are translated in two risk analysis frameworks: one for policy-oriented and one for operational risk analysis; the first leading to a quantitative and the second to a qualitative risk characterization. In both, risk is understood as a concept referring to the possible but uncertain occurrence of a situation where something of human value is at stake. Risk models are used as putting forward an argument based on available evidence, as a tool for communication between stakeholders and as a platform for thinking. Uncertainties and value-laden biases are assessed, and some tools for communicating these are introduced. Both frameworks are illustrated by extensive case studies. The first concerns accidental risk of oil spills from tanker collisions in the Gulf of Finland. The second focuses on a risk-informed ship-ship collision alert system. A final issue addressed in the thesis concerns the evaluation of a risk analysis, i.e. principles and criteria for establishing credibility. An integrated framework for this is developed, addressing model use, model plausibility, value-related validity and process-related validity. Specific evaluation criteria are proposed and a selection of these is applied in the presented case studies

Unmanned Remotely Operated Search and Rescue Ships in the Canadian Arctic: Exploring the Opportunities, Risk Dimensions and Governance Implications

This chapter is a proactive risk exploration of hypothetical remotely operated search and rescue (SAR) ships in the Canadian Arctic. The harsh and remote environment in the region, combined with complicated coastlines and many uncharted or poorly charted traffic routes, makes it one of the most challenging SAR areas. Canada has committed itself to safety, environmental protection and sovereign presence in the area by maintaining joint SAR centres of federal government departments and mobilizing private volunteers. The characteristics of Canadian SAR response in the Arctic rest with its high dependency on heavy equipment such as aircraft, helicopters and icebreakers, entailing prolonged hours of response time. As recent climate change impacts and maritime traffic increase in the northern waters disclose safety gaps, innovation in SAR assets is anticipated. The safety gaps may be filled by state-of-the-art remote control technology. This chapter discusses remotely operated unmanned ships for SAR response, exploring their opportunities, risk dimensions and governance implications

Utilizing geographic information systems tools for risk-informed maritime search and rescue performance evaluation

In many sea areas there is significant recreational activity, with many sailing vessels and motor boats navigating, especially in coastal areas. Search and Rescue (SAR) organizations ensure the safety of people at sea, and are relatively frequently called to perform rescue or assistance missions to people in distress. Apart from the importance of adequate operational planning and training, rescue organizations benefit from establishing a robust, effective and cost-efficient response system. Risk-informed capacity planning can serve as a decision-support tool for determining the number and location of the required search and rescue units (SRUs). The purpose of this paper is to present such a risk-informed approach, which combines analysis of historic accident and incident data of recreational boating with information derived from Geographic Information System (GIS) methods. The method is applied to a case study focusing on the risk-informed capacity evaluation of the voluntary search and rescue services in the Finnish part of the Gulf of Finland. Results indicate that the response performance for recreational boating incidents is very good in most areas.Peer reviewe

Introduction

This chapter introduces a multidisciplinary collection of chapters addressing various aspects of governance of Arctic shipping written by leading international scholars. It investigates how ocean changes and anthropogenic impacts affect our understanding of risk, policy, management and regulation for safe navigation, environment protection, conflict management between ocean uses, and protection of Indigenous peoples’ interests in Canadian Arctic waters. The book is divided in three parts, together providing a multi-faceted and interdisciplinary view on governance of Arctic shipping. The first part addresses conceptual and empirical aspects of risk governance, management, and assessment in the Canadian Arctic. The second part focuses on the human dimensions of a changing Arctic, providing insights in Inuit perspectives and knowledge, occupational safety issues onboard cruise and other commercial vessels, and aspects of fishing vessel safety. The third part focuses on regulatory considerations of shipping and ocean use, with contributions addressing the IMO’s framework for Arctic shipping, the Polar Code implementation in Canada, and contemporary topics concerning ship emissions, heavy fuel oil, and maritime spatial planning. It is hoped that the contributions encourage further multi- and interdisciplinary work by established and emerging scholars, and that these can assist decision-makers in planning, managing, and regulating Arctic Shipping

Developing fuzzy logic strength of evidence index and application in Bayesian networks for system risk management

Digitalization is becoming a trend in our modern society and systems. Meanwhile, risk analysis and management has rooted and been applied in various fields. Therefore, there is an increasing need to integrate risk analysis and management into the coming digital society. Risk has been represented digitally by the product of probability and consequence i.e. R = P x C traditionally. However, it has been increasingly discussed to include strength of evidence (SoE) in addition to the traditional consequence (C) and probability (P). Although much advance has been achieved along this direction, there still remains challenges, e.g. ambiguity in rating SoE and visual expression of risk diagrams. This paper focuses on addressing these issues and meanwhile aims to make the risk expression fully digital so that it is more efficient and flexible to be included in a system analysis and visualization. This is achieved firstly by reviewing state-of-the-art discussions on SoE assessment in risk management and identifying the remaining challenges. Then, the paper proposes an approach to address the challenges by forming a fuzzy logic SoE index based on fuzzy logic theory, which enables a transfer from linguistic variable to a digital one with the ambiguity avoided. After the SoE index is formed, it is applied into BNs as the node size index to demonstrate its practical application. Meanwhile, with the BNs forming the infrastructure to calculate and present consequences and probabilities, it showcases a new system risk management approach. All the variables in the system can be expressed in a risk diagram. This further enables an improved risk visualization, risk management and risk communication for system analysis, towards risk digitalization.Peer reviewe

Implementing Bayesian networks for ISO 31000:2018-based maritime oil spill risk management: State-of-art, implementation benefits and challenges, and future research directions

The risk of a large-scale oil spill remains significant in marine environments as international maritime transport continues to grow. The environmental as well as the socio-economic impacts of a large-scale oil spill could be substantial. Oil spill models and modeling tools for Pollution Preparedness and Response (PPR) can support effective risk management. However, there is a lack of integrated approaches that consider oil spill risks comprehensively, learn from all information sources, and treat the system uncertainties in an explicit manner. Recently, the use of the international ISO 31000:2018 risk management framework has been suggested as a suitable basis for supporting oil spill PPR risk management. Bayesian networks (BNs) are graphical models that express uncertainty in a probabilistic form and can thus support decision-making processes when risks are complex and data are scarce. While BNs have increasingly been used for oil spill risk assessment (OSRA) for PPR, no link between the BNs literature and the ISO 31000:2018 framework has previously been made. This study explores how Bayesian risk models can be aligned with the ISO 31000:2018 framework by offering a flexible approach to integrate various sources of probabilistic knowledge. In order to gain insight in the current utilization of BNs for oil spill risk assessment and management (OSRA-BNs) for maritime oil spill preparedness and response, a literature review was performed. The review focused on articles presenting BN models that analyze the occurrence of oil spills, consequence mitigation in terms of offshore and shoreline oil spill response, and impacts of spills on the variables of interest. Based on the results, the study discusses the benefits of applying BNs to the ISO 31000:2018 framework as well as the challenges and further research needs.Peer reviewe

Hazard Identification in Winter Navigation

In this report, a hazard identification in winter navigation has been performed in order to detect, determine, list and categorize different relevant hazards threatening the safety performance and development of the winter navigation operations. The analysis presented in this report aims to gather all available information from different sources in order to detect hazards for the practice of winter navigation, having a particular consideration of winter navigation hazards of oil tankers operation and/or vessels with similar characteristics. The report introduces the implemented framework to detect the relevant hazards of winter navigation and describes in details the three utilized sources to detect those hazards: hazard identification workshops with winter navigation experts, accident cases analysis, and analysis of accident statistics of 5 winters. Results obtained are presented after the performed collection and data analysis. Finally, discussion and conclusions are drawn

Risk Assessment and Management for Maritime SAR and Oil Spill Response

This report summarizes selected publications that deal with maritime Search and Rescue (SAR) operations, winter navigation as well as oil spill response. In the first part of this report, the SAR capabilities, response times and effects of weather on Finnish Search and Rescue Units (SRUs) are evaluated. Besides this, the risk of oil spill and effects of winter conditions were evaluated. Two of the most relevant accident types – collisions consequences on oil tanker and RoPAx vessels – were evaluated. Both tankers as well as RoPax vessels are very common vessels in the Gulf of Finland, carrying thousands passengers or tonnes of oil. However, during the project it was found that there are currently no particularly reliable methods for assessing which sea areas are most prone to accidents. This highlights the need for future research in the methodology. Furthermore, a model is presented that describes the interaction between ships and the ice when navigating in an ice channel. This model helps to understand better the increased side forces and yaw that occurs in ice channel when compared to sailing in open waters. This can be used to train bridge personnel to better understand their ship's behavior under challenging ice channel conditions, thus decreasing risk.  A final model describes how fast an oil slick will spread in an ice channel as a function of factors such as the ice concentration and ice floe size, allowing for better estimation of how far oil will spread until effective clean-up measures can be taken

Addressing the challenges to search and rescue operations caused by ice conditions in Nunavut, Canada

Search and rescue (SAR) operations on the land, water, and ice of Nunavut are often complex and challenging due to austere environmental conditions, the strain they place on local resources, and the vast distances involved in responding with Canadian Coast Guard icebreakers or southern-based aerial assets. Using the results of a literature review, practitioner interviews, and three regional SAR roundtables conducted in November 2022 in cooperation with Nunavut Emergency Management, this paper will assess: a) how changing ice conditions in the region add to these challenges by increasing the risk of SAR incidents; b) the ways in which the ice affects response operations; and c) how ice conditions exacerbate other difficulties in the SAR system. This paper concludes with a discussion of how the Nunavut Search and Rescue (NSAR) Project aims to address these challenges, focusing on modelling and analysis approaches

A model for oil spill scenarios from tanker collision accidents in the Northern Baltic Sea

Oil spills from maritime activities can lead to very extensive damages to the marine environment, and disrupt maritime ecosystem services. Shipping is an important activity in the Northern Baltic Sea, and with the complex and dynamic ice conditions present in this sea area, navigational accidents occur rather frequently. Recent risk analysis results indicate that especially collisions may lead to extensive oil spills. In Finnish sea areas, the current wintertime response preparedness is designed to a level of 5000 tonnes of oil, whereas a state-of-the-art risk analysis conservatively estimates that spills up to 15000 tonnes are possible. Hence, there is a need to more accurately estimate oil spill scenarios in the Northern Baltic Sea, to assist the relevant authorities in planning the response fleet organization and its operations. An issue which has not received prior consideration in maritime waterway oil spill analysis is the dynamics of the oil outflow, i.e. how the oil outflow extent depends as a function of time. Hence, this paper focuses on time-dependent oil spill scenarios from collision accidents possibly occurring to tankers operating in the Northern Baltic Sea. To estimate these, a Bayesian Network model is developed, integrating information about designs of typical tankers operating in this area, information about possible damage scenarios in collision accidents, and a state-of-the-art time-domain oil outflow model. The resulting model efficiently provides information about the possible amounts of oil spilled in the sea, in different periods of time, thus contributing to enhanced oil spill risk assessment and response preparedness planning.Peer reviewe