Maritime Authorities Research Articles

Factors associated with drowning in Portugal, 2019-2023

Abstract Worldwide, mortality from drowning amounted to 236.000 individuals in 2019, corresponding to 8% of the total global mortality, making drowning the third leading cause of death from unintentional injuries and a universal public health problem. Portugal has a coastal zone of 950 km long, with 658 bathing waters and, in 2023, 157 people died due to drowning. This work aims to determine the factors associated with drownings that occurred in Portugal, between 2019 and 2023. This epidemiological descriptive-analytical study used the National Maritime Authority database, regarding the users of the portuguese coastal zone who suffered maritime incidents between 2019 and 2023. SPSS was used for statistical analysis and the results of the Poisson regression models are presented as adjusted prevalence ratios (APR) with 95% confidence intervals, according to individual (sex, age group and nationality), temporal (period of the week and day) and environmental (maritime department and beach surveillance status) variables. The total sample was 406 drownings and 15 860 other maritime incidents. Overall, the frequency of drownings in Portugal was higher in men (APR=1.393, 95%CI=1.130-1.717, p=.002), in the >55y age group (APR=1.780, 95%CI=1.005-3.152, p=.048), in foreigners (APR= 1.293, 95%CI=1.037-1.612, p=.022), on weekends (APR=1.299, 95%CI=1.063-1.586, p=.010), in the afternoon (APR=1.584, 95%CI=1.127-2.226, p=.008) and on unsupervised beaches (APR=2.436, 95%CI=1.958-3.029, p<.001) in comparison with users who suffered other maritime incidents. Individual, temporal and environmental factors are associated with a higher frequency of drownings in Portugal. Despite the limitation of the study that only includes users suffering maritime incidents and not all users of the portuguese coastal zone, our results allow a preliminary characterization of the drowning profile in Portugal and can contribute to the design of preventive strategies and policies to address this public health problem. Key messages • This study shows that there are individual, temporal and environmental factors strongly associated with a higher frequency of drownings in Portugal. • Portugal has a large coastal zone and the characterization of a drowning profile is the first step for the development of prevention strategies in order to oppose drowning morbidity and mortality.

Understanding of the Maritime Future Mentality; Safe E-navigation and Safe Maritime Surface Communication

Developing and changing technology affects all sectors globally. Although it primarily affects information systems digitally, it affects all sectors indirectly. Maritime transport, the most important transportation mode in the world, is affected by technological progress as seafarers, ships, and ports. When used for its intended purpose, the technology employs intelligent and rational solutions based on the logic of identifying previous errors and developing predictions accordingly. Maritime transportation is the movement of ships between ports safely and without harming the environment. The sea is a dynamic surface not previously exposed to fixed effects and is affected by meteorological and environmental conditions. As the international maritime authorities keep pace with technological advancements, they have embraced the e-navigation concept, a digital revolution that is set to transform the industry. This shift to Electronic Navigation requires all operations to be digital, making transmission easier and more efficient. It also mandates uninterrupted and high-quality digital communication with ships' land facilities during the entire voyage. ECDIS, one of the advanced automation technology products used for e-navigation, and the vector map ENC it uses are of great importance. ENC maps are produced with specific standards. S-100, which is described as the latest and most advanced standard, provides sailors with good opportunities for safe navigation and communication. The study has been prepared to explain e-navigation types of equipment, their standards, and how they communicate according to cyber security.

GreenHopper: The Danish spearhead towards autonomous waterborne mobility

Abstract GreenHopper is the first Danish zero-emission ferry developed as a test platform for autonomous waterborne navigation technologies. The paper presents technology development within the innovation project ShippingLab Autonomy, which led to the commissioning of GreenHopper at Limfjorden (DK) in December 2022. The technology research resulted in a holistic system architecture for surface vessel autonomy, based on distribution of functionality and responsibility on software modules, similar to the structure observed in the International Maritime Organization (IMO) Seafarers Training Certification and Watch-keeping (STCW) regulatory framework. The paper shows how this approach results in an architecture that supports safe behaviours of individual modules and of autonomous navigation at a system level. The paper presents the individual modules, specific features and benefits. Elements of the regulatory framework are highlighted to poise technology approval by maritime authorities. The paper reflects on lessons learned, discusses continued technology validation in dedicated operational scenarios.

Development and Application of an Advanced Automatic Identification System (AIS)-Based Ship Trajectory Extraction Framework for Maritime Traffic Analysis

This study addresses the challenges of maritime traffic management in the western waters of Taiwan, a region characterized by substantial commercial shipping activity and ongoing environmental development. Using 2023 Automatic Identification System (AIS) data, this study develops a robust feature extraction framework involving data cleaning, anomaly trajectory point detection, trajectory compression, and advanced processing techniques. Dynamic Time Warping (DTW) and the Hierarchical Density-Based Spatial Clustering of Applications with Noise (HDBSCAN) algorithms are applied to cluster the trajectory data, revealing 16 distinct maritime traffic patterns, key navigation routes, and intersections. The findings provide fresh perspectives on analyzing maritime traffic, identifying high-risk areas, and informing safety and spatial planning. In practical applications, the results help navigators optimize route planning, improve resource allocation for maritime authorities, and inform the development of infrastructure and navigational aids. Furthermore, these outcomes are essential for detecting abnormal ship behavior, and they highlight the potential of route extraction in maritime surveillance.

Incorporating human and organizational failures into the formation pattern for different Arctic maritime accidents using a data-driven Bayesian network

To gain a comprehensive understanding of formation patterns for various maritime accidents in Arctic waters, the present study integrates human and organizational failures (HOFs) with accident risk factors (AIFs) to examine the individual or collective impacts of different AIFs and HOFs on Arctic maritime accidents. Firstly, a novel database is established within the improved Human Factors Analysis and Classification System (HFACS), encompassing 14 AIFs with multiple states and 33 HOFs with binary states. Secondly, the Association rule mining (ARM) is employed to capture the causal relationships among HOFs, while Augmented Naive Bayes (ANB) is introduced to account for the interdependency of AIFs, thereby developing the data-driven BN model for analyzing and predicting Arctic maritime accidents. Finally, the criticality and sensitivity of AIFs and HOFs across different Arctic maritime accidents are identified and ranked by BN forward and backward inference. Furthermore, three scenarios are simulated to demonstrate effective management strategies for prevention and mitigation of Arctic maritime accidents. Additionally, a correlation graph depicting the relationship between HOFs and AIFs is generated for each accident scenario, facilitating crew onboard ships as well as shipping companies and maritime authorities in customizing targeted safety measures aimed at preventing Arctic maritime accidents.

ESPAÇO MARÍTIMO BRASILEIRO E SEGURANÇA NO TRÁFEGO AQUAVIÁRIO

Maritime Traffic in Brazilian Jurisdictional Waters (BJW) is essential for trade, research, and recreational activities. However, it requires strict compliance with national and international regulations to ensure navigational safety, protect human life at sea, and preserve the marine environment. This abstract addresses the challenges and procedures related to the enforcement and application of these regulations. The objective of this work is to highlight the importance of maritime surveillance in BJW and how it contributes to maintaining a safe waterway environment. To achieve this goal, we examined legislation, the roles of maritime authorities, and inspection procedures, emphasizing the roles of naval inspectors at diferente levels. The methodology involved the analysis of regulations, laws, and documents related to waterway traffic safety, as well as the description of activities performed by naval inspectors at different levels of operation. We also highlighted the administrative measures and penalties that can be imposed in case of violations. To summarize, maritime surveillance plays a fundamental role in maintaining navigational safety, preventing environmental pollution, and protecting human life at sea in Brazilian Jurisdictional Waters. Through this constant surveillance, waterway traffic in BJW can be conducted efficiently and safely.

A data-driven Ship Risk Profile model for Turkish Straits (TS-SRP) using Machine Learning

Marine accidents exhibit a higher frequency within ports, internal waters, and narrow waterways as compared to open seas, emphasizing the paramount concern of maritime authorities regarding the safe navigation of ships in congested waters. In response to this issue, coastal states, in addition to flag state and port state measures, institute preventive measures by conducting risk analyses in narrow waterways with geographical restrictions and high traffic density. To meet this need, this study aims to develop a Ship Risk Profile (SRP) model to monitor ships by evaluating the potential risks of the ships passing through narrow waterways and taking the necessary precautions proactively by Vessel Traffic Service (VTS) for mitigating the potential accident and environmental pollution risk. The Turkish Straits is determined as the application area for this paper. The proposed model employs Machine Learning (ML) methods and analyzes targeting factors from Port State Control (PSC), ship particulars obtained from Sailing Plan (SP)-1 reports specific to the Turkish Straits, as well as relevant environmental factors. The results demonstrate that the developed model holds promise for improving safety in Turkish Straits and can be adapted by VTSs in other sea regions by customizing it to suit their specific characteristics and conditions.

Seafarer competency analysis: Data-driven model in restricted waters using Bayesian networks

Despite the efforts of maritime authorities to enhance seafarer competencies through the International Convention on Standards of Training, Certification and Watchkeeping for Seafarers (STCW), human error remains a leading cause of maritime accidents. To thoroughly investigate the impact of various human errors among seafarers on accidents, this paper aims to examine the relationships between seafarer competencies and maritime accidents using a data-driven approach from the perspective of bridge resource management (BRM). Through analysis of historical maritime accident reports, the dataset of seafarer competencies associated with maritime accidents is established. The least absolute shrinkage and selection operator (LASSO) method is employed to identify the critical seafarer competencies for accident prevention. Then, a data-driven Bayesian Network (BN) model, based on a Tree Augmented Naive Bayes (TAN) method, is constructed to reveal the relationship between seafarer competencies and accident types, which are validated by sensitivity analysis and case study. The results indicate that the key seafarer competencies for all maritime accidents are ‘Maneuvers’, ‘Amend/maintain ship course’, ‘Decision making’, ‘Cognitive capacity’, ‘Information’, ‘Procedure operations’, ‘Situational awareness’ and ‘Communication’. Moreover, the study underscores the importance of leveraging lessons learned from past accidents to mitigate risks and ensure safe maritime operations. The findings contribute to a deeper understanding of the dynamics between seafarer competencies and accident types, unveiling the joint impact of different seafarer competencies on maritime accidents. This perspective offers valuable insights for maritime authorities in strengthening maritime safety regulations.

Optimal Policies and Heuristics to Match Supply with Demand for Online Retailing

Problem definition: We consider an online retailer selling multiple products to different zones over a finite horizon with multiple periods. At the start of the horizon, the retailer orders the products from a single supplier and stores them at multiple warehouses. The retailer determines the products’ order quantities and their storage quantities at each warehouse subject to its capacity constraint. At the end of each period, after random demands in the period are realized, the retailer chooses the retrieval quantities from each warehouse to fulfill the demands of each zone. The objective is to maximize the retailer’s expected profit over the finite horizon. Methodology/results: For the single-zone case, we show that the multiperiod problem is equivalent to a single-period problem and the optimal retrieval decisions follow a greedy policy that retrieves products from the lowest-cost warehouse. We design a nongreedy algorithm to find the optimal storage policy, which preserves a nested property: Among all nonempty warehouses, a smaller-index warehouse contains all the products stored in a larger-index warehouse. We also analytically characterize the optimal ordering policy. The multizone case is unfortunately intractable analytically, and we propose an efficient heuristic to solve it, which involves a nontrivial hybrid of three approximations. This hybrid heuristic outperforms two conventional benchmarks by up to 22.5% and 3.5% in our numerical experiments with various horizon lengths, fulfillment frequencies, warehouse capacities, demand variations, and demand correlations. Managerial implications: A case study based on data from a major fashion online retailer in Asia confirms the superiority of the hybrid heuristic. With delicate optimization, the heuristic improves the average profit by up to 16% compared with a dedicated policy adopted by the retailer. The hybrid heuristic continues to outperform the benchmarks for larger networks with various structures. Funding: X. Li is supported by the Singapore Ministry of Education [Tier 1 Grant 23-0619-P0001]. Y. F. Lim is grateful for the support from the Singapore Management University under the Maritime and Port Authority Research Fellowship and the Singapore Ministry of Education [Tier 1 Grant MSS23B001]. Supplemental Material: The online appendix is available at https://doi.org/10.1287/msom.2021.0394 .

Cascading failure modelling in global container shipping network using mass vessel trajectory data

Port plays a key role in maintaining traffic flows and the effectiveness of global maritime logistics. However, the vulnerability of the Global Container Shipping Network (GCSN) is likely to increase when a single port interruption entails failures in cascading when ports encounter situations like congestions, labor strikes or natural disasters. Such situations require the deployment of port protection measures and adjustments of shipping schedules. This paper introduces a cascading model, which employs extensive and worldwide vessel trajectory data to comprehensively analyze the occurrence of cascading failures within a GCSN. The principles behind the cascading failure model are that port failures are simulated and the maritime traffic is redistributed and equilibrated to other routes and ports. A Motter-Lai overload model is applied, complemented by a three-level balanced redistribution of the traffic flows according to the specific roles of the disrupted ports. Overall, this favors the analysis of the GCSN's vulnerability, reliability, potential risks, and possible impacts. It enables maritime authorities and decision-makers to optimize service routes and mitigate the GCSN's vulnerability.

Pelaksanaan Pengawasan oleh Direktorat Jendral Bea Cukai Terhadap Larangan Thrifting Pakaian Bekas Impor

The purpose of this research report is to understand the procedures for implementing controls on the ban on thrifting of imported used clothing and to identify the factors that regulate the control of export and import activities by customs and tax authorities and hinder these bodies. The method used in this research is a qualitative method with a normative-empirical approach and the materials used include primary, secondary and tertiary data collection techniques, therefore based on observation, literature and documentation. The results of the investigation show: 1) the emergence of a period of supervision of correspondence with identification (scanning dogs or drug detectors), then inspections were carried out by all relevant agencies, maritime and maritime authorities, in the cases specified in Order Number PER -17/BC/2020 concerning procedures how to control the Director of Taxes and Customs. 2) Placement of customs and tax officers in the free zone (KB) hall through a computerized storage system and CCTV monitoring system, so that the company has a computerized inventory information system that cannot be differentiated from the existence of various types of warehouses. favorable and unfavorable factors.

Study on Cost-Effective Performance of Alternative Fuels and Energy Efficiency Measures for Shipping Decarbonization

Within the context of global initiatives to address climate change, the shipping industry is facing increasingly intensified pressure to decarbonize. The industry is engaging in the exploration and implementation of greenhouse gas (GHG) emission reduction measures, including energy efficiency technologies and alternative fuels, with the objective of accelerating the progression towards greenhouse gas mitigation. The application of various GHG emission reduction measures usually requires different levels of investment costs, and economic feasibility is a key factor influencing policy formulation and investment decisions. In this regard, this paper developed a cost-effective model for energy efficiency measures and alternative fuels based on the marginal abatement cost (MAC) methodology. This model can distinguish the differences between energy efficiency measures and alternative fuels in terms of Tank-to-Wake emissions and Well-to-Wake emissions in the GHG emission evaluation system. By taking typical ship types with significant emission contributions as study cases, i.e., bulk carriers (61–63K DWT), container ships (8000 TEU), product tankers (115K DWT), crude oil tankers (315–320K DWT), and Ro-Ro passenger ferries (3500 DWT), the GHG abatement cost-effective performance of major categories of measures such as operational measures, technical measures, renewable energy sources, and alternative fuels were calculated. According to the MAC results, the marginal abatement cost curves were plotted based on the ranking of energy efficiency measures and alternative fuels, respectively. The impacts of bunker fuel prices and carbon market prices on the cost-effectiveness were analyzed. The research results provided the GHG abatement potential of the integrated application of cost-effective energy efficiency measures, the cost-effectiveness ranking of alternative fuels, and the carbon emission price expected to bridge the price gap between alternative fuels and conventional bunker fuel. The presented methodology and conclusions can be used to assist shipping companies in selecting emission reduction measures, and to support maritime authorities in developing market-based measures.

AIS-based kinematic anomaly classification for maritime surveillance

Anomaly detection is crucial for maritime surveillance and law enforcement. Early identification of abnormal behavior ensures maritime order and fosters a safer environment for maritime traffic. However, anomaly identification and classification methods often suffer from vagueness because of the complexity of anomalies, limiting their effectiveness. We propose a systematic and data-driven framework for kinematic anomaly classification and detection. Through extensive inspection and experiments, a comprehensive characterization of diverse anomalies is provided to classify vessel kinematic anomalies into three categories, including Speed and Course Anomaly (SCA), Turning Anomaly (TA) and Loitering Anomaly (LA), along with detection methods that are tailored to each anomaly type to facilitate the production of high-quality anomaly labels. Subsequently, supervised training is exploited for anomaly classification. The effectiveness of the proposed method is validated using the open Automatic Identification System (AIS) dataset provided by the Danish Maritime Authority (DMA). With proper feature design, the proposed method can achieve a classification accuracy of approximately 99% using simple neural networks.

A novel algorithm for ship characteristic points extraction based on density clustering

With the widespread application of ship Automatic Identification System (AIS) in maritime operations, a large number of ship trajectories become available. This study aims to improve the safety of ships navigating through densely trafficked areas and address the challenge of sufficient data exploration while fully describing the traffic conditions in these waters. To achieve this objective, traffic flow information is extracted from AIS data collected in Zhoushan waters. A combination of multi-algorithms is employed to extract the traffic flow frame, specifically, the Douglas-Peucker compression algorithm and trajectory intersection algorithm are utilised to identify the characteristic points of ship trajectories. Subsequently, a density clustering algorithm is applied to extract the three types of characteristic points: compressed trajectory points, intersection points, and ship position points, facilitating data mining efforts. The resulting initial traffic flow characteristic points are then subject to weighted fusion, followed by image superposition processing to create an overlapping map of the ship trajectories. This process culminates in the generation of a traffic flow frame for the region. The framework integrates various track characteristic points, offering insights into the distribution of essential routes in the vicinity waters, thereby providing a comprehensive depiction of ship traffic flow patterns. The proposed framework can be applied to the route planning and serve as a reference to the maritime authorities when selecting recommended shipping lanes.

Port State Control Inspections under the Paris Memorandum of Understanding and Their Contribution to Maritime Safety: Additional Risk Classifications and Indicators Using Multivariate Techniques

Port State Control (PSC) inspections conducted under the Paris Memorandum of Understanding (MoU) agreement have become a crucial tool for maritime administrations in European Union countries to ensure compliance with international maritime safety standards by ships entering their ports. This paper analyses all PSC inspections conducted in 10 major European ports belonging to the Paris MoU between 2012 and 2019. For its study, a multivariate HJ-Biplot statistical analysis is carried out, which facilitates the interpretation and understanding of the underlying relationships in a multivariate data set by representing a synthesis of the data on a factorial plane, with an interpretation that is very intuitive and accessible for readers from various fields. Applying this method with ship characteristics as explanatory variables, several classifications were derived. These classifications align with the annual performance lists published by the Paris MoU and the International Association of Classification Societies list, suggesting that this method could serve as a reliable classification approach. It provides maritime authorities with an additional indicator of a ship’s risk profile, aiding in the prioritising of inspections. The method also effectively categorises ports and types of ships used for cargo transport, offering insights into the specific maritime traffic each port experiences. Furthermore, this study identifies characteristics associated with substandard ships, which is a primary objective of PSC inspections. Beyond revealing these traits, this research underscores the existence of several readily applicable techniques to enhance maritime safety and reduce the risk of ocean pollution.

Implementation of the MLC Convention in Albania and its Role in Seafarer’s Standards

The Maritime Labor Convention (MLC) is an international labor standard adopted by the International Labor Organization (ILO) in 2006 [1] . The MLC was designed to ensure that seafarers receive decent working conditions on board ships, without any difference regardless their nationality. The convention sets out minimum requirements to be met by authorities, shipping companies, for seafarer’s employment rights, working conditions, and social protection. Convention, 2006, as amended (MLC 2006) on 28 Oct [2]ober 2016, and the convention entered into force in Albania on 28 October 2017. The amendments of the Code of the Convention approved by the International Labor Conference (ILC) in 2018 entered into force in Albania on 26 December 2020. The aim of this paper is to examine the implementation of MLC requirements and its impact in Albanian maritime industry, and to identify the needed steps to be undertaken by Albanian maritime authorities to fully comply with MLC requirements.
 
 Received: 23 February 2024 / Accepted: 18 March 2024 / Published: 23 March 2024

Risk maturity model for the maritime authorities: a Delphi study to design the R-Mare matrix model

Maritime authorities have the administrative responsibility for the safety and security of shipping and the prevention of marine and atmospheric pollution caused by ships. This responsibility involves various tasks that can be supported through effective risk management, but currently, there are no models available to evaluate its level of maturity in maritime administrations. To fill this gap and respond to the needs identified by maritime authorities, this article introduces a new risk maturity model called the R-Mare matrix. This model is built on recent scientific knowledge in the field of risk management, and it has been designed in close cooperation with end-users and maritime risk management experts using the Delphi methodology. As a result of this process, the article provides a qualitative risk maturity matrix specifically tailored to support the self-evaluation of maritime authorities. The matrix consists of 17 state-of-the-art risk management attributes, a five-step risk maturity scale, and associated risk maturity grid descriptions. These elements can be used to evaluate the current risk management performance of maritime authorities, identify areas for improvement, and develop a plan to achieve a higher level of maturity. Overall, the R-Mare matrix model represents an important step forward in this field while laying the foundation for further development.

Impact on seafarers of extreme events: A case study arising out of the situation in Ukraine.

Maritime transportation is the lifeblood of the world's economy. However, seafarers are exposed to isolated, confined and particularly extreme environments. Maritime operations in the face of geopolitical conflicts profoundly impact seafarers' mental health, well-being and safety. The study comprises 27 seafarer interviews and 21 stakeholder interviews covering 4 maritime education and training institutions, 11 crewing agencies, 4 medical facilities and 2 maritime authorities. An online questionnaire survey of seafarers who were affected by the conflict in Ukraine and had sailed in the conflict zone in the period 24 February 2022 to 30 September 2023 yielded 319 valid responses. The study suggests that seafarers in the conflict zone are exposed to constant imminent threats to personal safety, constant stress and anxiety, prolonged lack of sleep, limited opportunities of contact with families, and high risk to mental health among other things further exacerbated by a lack of mental health support from company, and anxiety resulting from loss of access to shore-based training facilities and uncertainty in updating competency certificates. The study presents rare insights on the psychological and emotional toll on seafarers who continue to serve the critical needs of the maritime transportation industry in a newly ordained role as keyworkers. This study underscores the need for improved mental health support and counselling services within the maritime industry, in particular, maritime stakeholders likely affected by geopolitical conflicts. From the practical perspective, this is among the first studies to focus on the mental health and well-being of seafarers arising out of the situation in Ukraine since 24 February 2022. From the theoretical perspective, this is a maiden study attempting an exploration of social conditions in three different dimensions by integrating three distinct theoretical constructs namely, UN Human Security Framework, Holmes & Rahe Social Readjustment Rating Scale and ILO Maritime Labour Convention framework.

Big Data-Assisted Maritime Management: The Relationship between Ship PSC Inspections and Vessel Distress Alarms

Maritime activities play a crucial role in the social and economic development of human societies. Many countries around the world have become powerful as a result of the flourishing maritime activities. However, maritime activities entail high risks, making ship navigation safety a paramount concern for maritime authorities, practitioners, and scholars worldwide. In recent years, the continuous growth in the number and tonnage of vessels, coupled with the increasing density of waterway traffic, has posed a serious threat to maritime safety, leading to a rise in maritime accidents. This paper conducts a comprehensive analysis by examining distress alarm data from the Guangzhou Coastal Radio Station over a decade from 2010 to 2019, and integrating it with Port State Control (PSC) inspection data from the Guangzhou Port Supervision and Inspection Station. The aim is to explore scientific and effective approaches for analyzing the safety status of ship navigation, preemptively preventing maritime accidents, and thereby providing valuable insights for maritime management agencies and navigation security departments to enhance their maritime management capabilities and navigation safety service levels.

Diagnostics of Safety Hazardous Ageing Conditions for Commercial Lithium-Ion Pouch Cells

It is well-known that Lithium-ion cells can have safety issues. A large number of battery fire incidents have been reported the last years within e.g. battery energy storage systems [1], electric and hybrid-electric ships [2], electric vehicles and mobile phones [3]. The causes for these incidents are numerous and can include internal shortage of the Li-ion cell, external shortage of the battery system, over-heating or over-charging. All these causes result in overheating which can lead to an eventual thermal runaway which again could lead to a severe fire and explosion. We report on changes in thermal stability due to different ageing mechanisms in abstract Lian (#176439) and in Lian [4]. A decrease in thermal stability due to battery ageing could be hazardous and might be an end-of-life criteria. It is thus of vital importance to develop diagnostic tools capable of detecting a potentially hazardous drop in thermal stability for aged lithium-ion cells.This study is based on results from a battery life study performed on a large renowned Li-ion pouch cell with an initial capacity of 64 Ah. More than 100 cells were tested following a selected test matrix including different temperatures, currents, and State-of-Charge windows. All cells were tested until they reached a remaining capacity of between 60 to 80 % State-of-Health. A large dataset with diagnostic data was recorded during ageing, including e.g., dQ/dV (incremental capacity analysis) and DC resistances. Thermal properties of selected new and aged cells were studied in an Accelerated Rate Calorimeter (ARC), see Lian (abstract #176439). A post-mortem study of selected new and aged cells was performed to relate the collected diagnostics data to different ageing paths and safety properties. Based on detailed cell characterization, an experimental parameter set for an electrochemical pseudo-two-dimensional (P2D) model was established.Based on the dQ/dV (ICA) analysis, a distinct change in diagnostic patterns was observed for cells aged and cycled at low temperature (5-15 °C) compared to cells cycled at higher temperatures (35 -45 °C). This correlates to the observed differences in thermal stability reported by Lian (abstract #176439). To verify the observed ageing mechanisms from the post-mortem studies, emulated ageing modelling was performed both based on the Alawa tool [5], as well as the P2D model coupled with different ageing mechanisms. References McKinnon, M.B., S. DeCrance, and S. Kerber, Four Firefigheters Injured In Lithium-Ion Battery Energy Storage System Explosion - Arizona, U. Laboratories, Editor. 2020, Underwriters Laboratories: Columbia, MD. p. 66.Norwegian Maritime Authority, Supporting preliminary findings after battery incident. 2019: Norwegian Maritime Authority.BBC, Samsung confirms battery faults as cause of Note 7 fires, in BBC. 2017, BBC.Lian, T., et al., (Invited) Changes in Thermal Stability of Cyclic Aged Commercial Lithium-Ion Cells. ECS Transactions, 2019. 89(1): p. 73-81.Dubarry, M., et al., State of health battery estimator enabling degradation diagnosis: Model and algorithm description. Journal of Power Sources, 2017. 360: p. 59-69.