Purpose: The purpose of the paper is to identify the multiple types of data that can be collected and analyzed by practitioners across the cold chain, the ICT infrastructure required to enable data capture and how to utilize the data for decision making in cold chain logistics. Design/methodology/approach: Content analysis based literature review of 38 selected research articles, published between 2000 and 2016, was used to create an overview of data capture, technologies used for collection and sharing of data, and decision making that can be supported by the data, across the cold chain and for different types of perishable food products. Findings: There is a need to understand how continuous monitoring of conditions such as temperature, humidity, and vibration can be translated to support real-time assessment of quality, determination of actual remaining shelf life of products and use of those for decision making in cold chains. Firms across the cold chain need to adopt appropriate technologies suited to the specific contexts to capture data across the cold chain. Analysis of such data over longer periods can also unearth patterns of product deterioration under different transportation conditions, which can lead to redesigning the transportation network to minimize quality loss or to take precautions to avoid the adverse transportation conditions. Research limitations/implications: The findings need to be validated through further empirical research and modeling. There are opportunities to identify all relevant parameters to capture product condition as well as transaction data across the cold chain processes for fish, meat and dairy products. Such data can then be used for supply chain (SC) planning and pricing products in the retail stores based on product conditions and traceability information. Addressing some of the above research gaps will call for multi-disciplinary research involving food science and engineering, information technologies, computer science and logistics and SC management scholars. Practical implications: The findings of this research can be beneficial for multiple players involved in the cold chain like food processing companies, logistics service providers, ports and wholesalers and retailers to understand how data can be effectively used for better decision making in cold chain and to invest in the specific technologies, which will suit the purpose. To ensure adoption of data analytics across the cold chain, it is also important to identify the player in the cold chain, which will drive and coordinate the effort. Originality/value: This paper is one of the earliest to recognize the need for a comprehensive assessment for adoption and application of data analytics in cold chain management and provides directions for future research.
Design waves have been used in the past for the probabilistic assessment of wave-induced loads and responses of offshore structures. Various response-conditioning techniques have been employed to determine suitable wave episodes, typically based on linear response transfer functions. Nevertheless, extreme events are not always driven by linear phenomena but can be triggered by near-resonant effects, as in the case of the slow-drift motions of moored floating bodies. Limited research has been devoted to addressing this class of responses using response-conditioned waves (RCW). This paper presents a new approach for deriving RCWs that accounts for combined wave- and low-frequency responses. Both the response amplitude operator (RAO) and the quadratic transfer function (QTF) are employed in an iterative response-conditioning procedure. That permits the identification of appropriate short-duration wave episodes that excite resonant slow-drift motions. These wave episodes are then used in a two-step multi-fidelity design wave methodology for the probabilistic evaluation of the fully nonlinear extreme responses. The proposed approach is validated experimentally for predicting the surge excursions of a moored container ship, and good agreement is found against Monte Carlo results in irregular waves.
This paper presents a detailed risk assessment framework tailored for retrofitting ship structures towards eco-friendliness. Addressing a critical gap in current research, it proposes a comprehensive strategy integrating technical, environmental, economic, and regulatory considerations. The framework, grounded in the Failure Mode, Effects, and Criticality Analysis (FMECA) approach, adeptly combines quantitative and qualitative methodologies to assess the feasibility and impact of retrofitting technologies. A case study on ferry electrification, highlighting options like fully electric and hybrid propulsion systems, illustrates the application of this framework. Fully Electric Systems pose challenges such as ensuring ample battery capacity and establishing the requisite charging infrastructure, despite offering significant emission reductions. Hybrid systems present a flexible alternative, balancing electric operation with conventional fuel to reduce emissions without compromising range. This study emphasizes a holistic risk mitigation strategy, aligning advanced technological applications with environmental and economic viability within a strict regulatory context. It advocates for specific risk control measures that refine retrofitting practices, guiding the maritime industry towards a more sustainable future within an evolving technological and regulatory landscape.
With the blue economic sectors growing, marine macroalgae cultivation plays an important role in securing food and energy supplies, as well as better water quality in sustainable ways, whether alone or as part of a cluster solution to mitigate the effects of fish farming. While macroalgae cultivation exists in Europe, it is not that widely distributed yet; with increasing marine activities at sea, Maritime Spatial Planning (MSP) needs to ensure social recognition as well as social and spatial representation for such a new marine activity. This comparative case study analysis of MSPs of three eastern Baltic Sea countries explores the levels of support for the development of macroalgae cultivation in MSP and the degree of co-location options for this new and increasingly important sector. It presents new analytical ways of incorporating co-location considerations into the concept of social sustainability. The results of this study support the harmonisation of views on co-location, propose ways of using space to benefit multiple users as well as marine ecosystems, and highlight some of the key social challenges and enablers for this sector.
Although the concept of ecosystem services has been in use for many decades, its application for policy support is limited, particularly with respect to marine ecosystems. Gaps in the assessments of ecosystem services supply prevent its empirical application. We advance these assessments by providing an assessment tool, which links marine ecosystem components, functions and services, and graphically represents the assessment process and its results. The tool consists of two parts: (i) a matrix following the ecosystem services cascade structure for quantifying the contribution of ecosystem components in the provision of ecosystem services; (ii) and a linkage diagram for visualizing the interactions between the elements. With the aid of the Common International Classification of Ecosystem Services (CICES), the tool was used to assess the relative contribution of a wide range of marine ecosystem components in the supply of ecosystem services in the Latvian marine waters. Results indicate that the tool can be used to assess the impacts of environmental degradation in terms of ecosystem service supply. These impacts could further be valued in socioeconomic terms, as changes in the socioeconomic values derived from the use of ecosystem services. The tool provides an opportunity for conducting a holistic assessment of the ecosystem service supply and communicating the results to marine spatial planning practitioners, and increasing their understanding and use of the ecosystem service concept.
The aim of this paper is to provide the foundations for the development of a spatial decision-support toolset that combines cumulative impacts and ecosystem service supply assessments to support what-if scenario analysis in a maritime spatial planning context. Specifically, a conceptual framework for a toolset has been designed in order to introduce a new approach for place-based assessments of change in relative ecosystem service supply in multiple services at a time due to changes in cumulative impacts. Central to the toolset are two pre-existing approaches for relative ecosystem service supply and cumulative impact assessments and tools that facilitate them. The tools take advantage of available data from various sources, including geodata and expert knowledge, and have already been proven to support maritime spatial planning in a real-world context. To test the new approach and demonstrate the outputs, an ecosystem service supply assessment was done manually using the two currently separate tools. The results of the test case ecosystem service supply assessment for the Gulf of Riga in the Baltic Sea are also presented in this paper and illustrate the assessment steps and data needs. Although presently the focus of the illustrative assessment is the Gulf of Riga, the toolset will be able to accommodate analysis of cumulative impacts and service supply of any location, leaving the scope of the assessment to be determined by the objectives of the assessment as well as data availability (i.e., geospatial data availability and extent of expert knowledge).
The aim of this paper is to provide the foundations for the development of a spatial decision-support toolset that combines cumulative impacts and ecosystem service supply assessments to support what-if scenario analysis in a maritime spatial planning context. Specifically, a conceptual framework for a toolset has been designed in order to introduce a new approach for place-based assessments of change in relative ecosystem service supply in multiple services at a time due to changes in cumulative impacts. Central to the toolset are two pre-existing approaches for relative ecosystem service supply and cumulative impact assessments and tools that facilitate them. The tools take advantage of available data from various sources, including geodata and expert knowledge, and have already been proven to support maritime spatial planning in a real-world context. To test the new approach and demonstrate the outputs, an ecosystem service supply assessment was done manually using the two currently separate tools. The results of the test case ecosystem service supply assessment for the Gulf of Riga in the Baltic Sea are also presented in this paper and illustrate the assessment steps and data needs. Although presently the focus of the illustrative assessment is the Gulf of Riga, the toolset will be able to accommodate analysis of cumulative impacts and service supply of any location, leaving the scope of the assessment to be determined by the objectives of the assessment as well as data availability (i.e., geospatial data availability and extent of expert knowledge).
Ship engines are subject to a very demanding work environment, where maximum availability is a must. In this project we look at different operational variables of a marine engine from large cargo ships, with the aim of detecting and trending damage onset on different engine sub-components. This information can be used by owners to expedite O&M interventions and maximize ship availability.
The integration of offshore wind assets with green hydrogen production and storage units can offer a much-needed solution for intermittency and curtailment issues of the offshore energy industry. To gain confidence that such novel integrated assets will be fit for purpose, the present study presents a comprehensive risk assessment followed by an action plan to mitigate the identified risks to help facilitate their technology qualification. The new methodology introduced here involves all the life-cycle phases of an offshore green hydrogen production system. Following, prevailing failure modes, their effects, and their causes are identified through an extensive review of relevant literature. Subsequently, risk prioritization is performed by ranking the criticality scores obtained from a multidisciplinary group of experts to the questionnaire designed to reveal the chosen subsystems' technology readiness, degree of change, concern in manufacturing and operation, and potential consequences regarding occupational health, safety, environment, economic and regulatory.
Increasing concerns related to fossil fuels have led to the introducing the concept of emission-free ships (EF-Ships) in marine industry. One of the well-known combinations of green energy resources in EF-Ships is the hybridization of fuel cells (FCs) with energy storage systems (ESSs) and cold-ironing (CI). Due to the high investment cost of FCs and ESSs, the aging factors of these resources should be considered in the energy management of EF-Ships. This article proposes a nonlinear model for optimal energy management of EF-Ships with hybrid FC/ESS/CI as energy resources considering the aging factors of the FCs and ESSs. Total operation costs and aging factors of FCs and ESSs are chosen as problem objectives. Moreover, a stochastic model predictive control method is adapted to the model to consider the uncertainties during the optimization horizon. The proposed model is applied to an actual case test system and the results are discussed.