Green Shipping Research Articles

Decision-Making on the Selection of Clean Energy Technology for Green Ships Based on the Rough Set and TOPSIS Method

In the context of the decarbonization of the shipping industry, the application of clean energy technologies is a catalyst for decarbonization. With the number of potential clean energy technologies expanding, the uncertainties in terms of technology maturity, policy regulation, and economics make clean energy technologies decision much more difficult. Therefore, it is urgent to establish a clean energy technology selection scenario for the green ship industry to assist shipowners in decision-making. Based on this, a technology selection model based on rough set (RS) and approximate ideal solution ranking (TOPSIS) is constructed. Using RS to reduce the evaluation index and calculate the weight can avoid the one-sidedness of subjective weighting. Using the TOPSIS method to rank alternatives. This paper selects seven clean energy technology alternatives, namely LNG power, LPG power, methanol power, HVO power, pure battery power, hydrogen fuel cell, and ammonia fuel cell, respectively, as the evaluation objects. Taking two types of vessels as examples, it is concluded that LNG power technology is suitable for large coastal ro-ro passenger vessels, and pure battery power technology is suitable for small inland river short-distances vessels. The results are in line with reality, which verifies the scientificity and validity of the proposed model.

Optimum trim prediction for container ships based on machine learning

Recent ship-related energy conservation efforts have directed increasing attention on green technology that has the potential to save energy in the shipping industry while protecting the environment. In particular, ship optimum trim energy-saving technology has several advantages, including facile implementation, convenient operation, and high energy-saving effects. This report proposes a method for predicting the optimum trim of container ships based on machine learning, and the developed approach can quickly determine the optimum trim of any container ship to achieve minimum resistance during operation. First, six container ship models from a trim optimization test database were consulted to extract the characteristic parameters of the container ships, thus providing a basic dataset for model training. Four machine learning models were selected to forecast the resistance of the container ship under different trim conditions. The results indicate that the performance of the random forest prediction model was significantly better than the three other tested models (i.e., backpropagation neural network, decision tree, K-nearest neighbor). Therefore, the random forest prediction model was used as the optimal prediction model for determining the optimum trim of container ships. Specifically, the 4700-TEU and 13500-TEU container ships were evaluated; relative to the experimental data, the prediction accuracy reached 85.71% and 88.89%, respectively. Finally, the developed model was applied to the 4250-TEU container ship operation, and the optimum trim angle was predicted under five sets of conditions; the predicted values were consistent with the experimental values. The container ship optimum trim prediction method based on machine learning described in this paper can predict the optimum trim of any container ship (in a certain state), guide its operation, realize energy-saving effects, reduce emissions, and promote the development of green ship technology.

Comprehensive evaluation method for site selection of LNG bunkering stations in Bohai Rim ports

With the introduction of emission peak and carbon neutrality strategy, green shipping has already become an urgent need for the development of water transportation industry. Using liquified natural gas (LNG)-powered ships is an effective way to deal with carbon emission, and more and more shipping companies are willing to choose it as the main ship type in the future. As the open cooperation portal to the Asia-Pacific region, the Bohai Rim region occupies an important position in China national shipping system. Focusing on the bunkering needs of LNG-powered ships in the future, ports in the Bohai Rim region should add LNG bunkering stations with reasonable layout and complete facilities. This paper constructs a comprehensive evaluation system for the site selection of LNG bunkering stations in coastal ports from five aspects: natural factors, infrastructure factors, economic factors, safety factors and policy factors, and conducts the evaluation on the alternative port areas. After comprehensive analysis, the Caofeidian Port Area of Tangshan Port is recommended as the location of LNG bunkering station.

Multi-objective optimization of daily use of shore side electricity integrated with quayside operation

Within the context of using shore side electricity (SSE) at container terminals, we propose a multi-objective optimization model to solve the problem of berth allocation and quay crane assignment (BACAP). The proposed optimization model integrates the interconnected decisions on each vessel’s berthing position, berthing start and departure time, duration of using SSE, and duration of using auxiliary engines to minimize the costs of using SSE, departure delay and emissions. Several factors, including the availability of SSE at different berths and vessels and the time-of-use (TOU) electricity pricing, which have been frequently ignored by previous studies, are specifically considered in this paper. Due to the complexity of the proposed model, an integrative algorithm framework is developed, composed of Partial Optimization Metaheuristic Under Special Intensification Conditions (POPMUSIC), Strength Pareto Evolutionary Algorithm 2 (SPEA2), and k-means clustering. The numerical experiments for a real-world case illustrate the efficiency of the developed algorithm framework and the effectiveness of the proposed model. Compared to the best-known solutions with only one objective considered, the proposed model reduces the costs of using SSE, departure delay, and vessel emissions by 27.47%, 37.51%, and 51.44%. Besides, some managerial insights are outlined based on the experiments under a series of designed scenarios. In doing so, the proposed optimization model assists the promotion of using SSE and the development of green ports and green shipping.

Collaboration of vessel speed optimization with berth allocation and quay crane assignment considering vessel service differentiation

Green shipping and efficient information sharing deepen the collaboration between shipping companies and ports, enabling vessel speed optimization (VSO) to be integrated with the berth allocation and quay crane assignment problem (BACAP). However, the literature presented to date usually considers all vessels as a whole and only addresses the vertical conflict between the two levels of the BACAP and the VSO but neglects the horizontal conflict among vessels in each level of the collaborative planning. To describe and address the conflicts within and between levels, we consider the vessel service differentiation (VSD) and propose a BACAP-VSO with VSD (BACAP-VSO-w/-VSD) collaboration mode. To this end, we set up a bi-level multi-objective optimization model. In the upper-level BACAP model, the VSD is implemented by separating vessels into different preferential groups. Multi-objectives are formulated to minimize the service delays of vessels in preferential groups and all vessels. In the lower-level VSO model, the VSD is realized by grouping vessels based on their shipping companies. Multi-objectives are solved to minimize the fuel consumption costs of each shipping company. We develop a nested genetic algorithm incorporated with an inheritance factor and jumping operations for the solution approach. Experimental results show that the proposed collaboration mode can analyze trade-offs among multiple conflicting objectives in any and between both planning levels. Compared to the existing collaboration mode, the proposed collaboration mode further reduces service delays of vessels and fuel consumption costs of shipping companies, improves customer satisfaction, and effectively reduces vessel emissions.

A two-step strategy for fuel consumption prediction and optimization of ocean-going ships

The prediction and optimization of ship fuel consumption are the core techniques for the successful implementation of smart and green shipping. However, in previous studies, there were some drawbacks with poor prediction performance based on single models, as well as a few studies on data-driven trim optimization. To bridge these gaps, a two-step strategy for the prediction and optimization of ship fuel consumption was proposed in this study. In the first step, the collected fuel consumption data is processed, and a novel hybrid prediction model is then developed based on the stacking theory by fusing several state-of-the-art single models. Subsequently, the second step proposes a method based on the developed hybrid model in combination with the enumeration method to optimize the fuel consumption from the perspective of trim adjustment. To support the proposal, two real-world voyages from bulk carrier are taken as examples. Through experimentation, the proposed hybrid model has better accuracy and robustness than the other seven popular single models. Furthermore, trim optimization can effectively reduce the fuel consumption and carbon emissions by 0.69%–1.82%. This study provides fundamental theoretical, methodological, and technical support for fuel saving and emission reduction in ships.

A numerical study on the effects of charge air temperature on the combustion and emission characteristics of a marine generator engine

A numerical study was carried out to investigate the effectiveness of the charge air cooling method on the exhaust gas emission reduction when applied to a four-stroke marine generator diesel engine at full load. The AVL FIRE 2018a software was used to perform three-dimension (3D) simulations of the combustion process and emission formations inside the engine cylinder operating with various charge air temperatures (CATs). The simulation results were then verified by measured values obtained from experiments in the Green Ship Technology laboratory (GSTLab), Korea. The simulation results showed In-Cylinder peak pressure increase tendencies as the CAT decreased from 360 K to 320 K, leading to an increase in the brake mean effective pressure (BMEP) by 10.74%. At the same time, the In-Cylinder peak temperature was decreased, resulting in a reduction in NO emission by 33.85%. Soot, CO, and CO2 emissions were also reduced by 63.92, 44.66, and 3.22%, respectively. In addition, the CAT cooling method also reduced specific fuel oil consumption (SFOC) by 9.68% due to the increase in the indicated efficiency. This study would be a useful material for operating engines in cases of trying to reduce exhaust gas emissions from existing engines without any additional emission post-treatment device.

Cuprous oxide single-crystal film assisted highly efficient solar hydrogen production on large ships for long-term energy storage and zero-emission power generation

Designing and manufacturing green ships and achieving zero emissions is one of the important trends in modern society for energy conservation and emission reduction. This article explores a novel combined technology of photovoltaic and photoelectrocatalysis to achieve efficient solar hydrogen production, in which the onset voltage for solar water splitting moved from 1.23 V forward to 0.59 V under the assistance of p-Cu2O single-crystal film. After implementing on a 110-m barge for the first time, a solar to hydrogen conversion efficiency of 9.79% has been achieved, which is state-of-the-art in large practical projects, producing 63 Nm3 of hydrogen every day accompanied with an outstanding Faraday efficiency higher than 98.2%. The hydrogen has been purified and compressed for storage, then generates 96 kWh of electricity on demand through the fuel cell stack (43% efficiency). The hydrogen-powered ship can reduce 6.1 tons of diesel consumption and 18.9 tons of carbon dioxide emissions each year.

Research on Design Optimization of High-Speed Ship Bulbous Bow Based on Nelder-Mead Algorithm

In order to reduce the wave-making resistance of ships, this paper proposes an optimization design method for bulbous bow form based on potential flow theory. In this paper, we restrict our interest to parametric deformation of the bow, at the same time constrain the displacement and the length of the ship. Based on Rankine source method, the wave-making resistances of DTMB5512 and ITTC Ship A-2 are calculated. For optimization, Sobol algorithm is selected to create sample space; based on it, we use Nelder–Mead algorithm to obtain the optimal hull form in the space. Additionally, we compare and analyze the hydrodynamic performance of the ship. The results show that the optimization design method reduces the wave-making resistance of DTMB5512 and ITTC Ship A-2, which verifies the feasibility of the method. Introduction Energy Efficiency Design Index (EEDI) guides the future development of the shipbuilding industry toward green ships and accelerates the pace of energy conservation and emission reduction. EEDI is closely related to hull form; therefore, the design optimization of ship hull focus on reducing EEDI becomes the central issue of the current research (Hou et al. 2018).

Knowledge recombination for emerging technological innovations: The case of green shipping

The paper explores knowledge recombination by analysing how knowledge networks in established technological fields influenced the formation of the emerging field of green shipping in the period 2007–2018. Previous research has demonstrated that embeddedness, proximity, and status are important mechanisms for the evolution of single technological fields. We investigate if these mechanisms also apply across technological fields. By employing dynamic social network analysis models, we find that actors transferred knowledge across technological fields through (re)combination mechanisms, which affected the emergence of the new technological field, but in different ways. While embeddedness and proximity played an important role, status was less important.

Influence of Implementation of Composite Materials in Maritime Industry on CO2 Emission’s Reduction

The future of the composites market looks attractive with opportunities in the transportation, construction, wind energy, pipe - tank, marine, consumer goods, electrical and electronics, aerospace, and others. The composite materials market is expected to reach an estimated $40.2 billion by 2024 and it is forecast to grow at a CAGR of 3.3% from 2019 to 2024. The composite materials that have started to be used in the production of tourist boats, especially those of the yacht type, have proved in practice the designers' expectations for the great advantages they have brought compared to steel. The performance of the new generation ships of this millennium, will require the ever-increasing use of new and innovative materials, to meet the also growing demands of potential buyers of these vehicles. On the other hand, based on the already sanctioned principles of the European Community for the observance of the norms set for CO2 emissions from maritime transport - (Green shipping) in respect of the Kyoto Protocol on Climate Change, it becomes more necessary to produce marine vehicles that significantly reduce the weight of marine vessels, consequently engine power and fuel consumption by significantly reducing CO2 emissions. This study aims to bring a specific analysis of the impact of composite materials to the CO2 emission’s reduction.

Green shipping networks as drivers of decarbonization in offshore shipping companies

Within the next 30 years, shipping companies must find their zero-emissions route. However, there is no consensus on which technologies and fuels are the most appropriate to decarbonize shipping. Shipping companies are now navigating the flows of trends and new technologies and fuels. At the same time, the “cluster trend” raises expectations that “green networks,” “green clusters” and “cleantech clusters” will aid sustainability transitions. This qualitative multiple case study of three Norwegian offshore shipping companies analyzes the drivers that shape the companies’ strategies to reduce greenhouse gas emissions, with particular focus on how the strategies are impacted by membership in green shipping networks. Process tracing is used to track the case companies’ approaches to emissions reduction from 2008 to 2020, the main drivers of emissions reduction, and whether changes in strategy are linked to network membership. This study finds that the main drivers have been initiatives by internal key persons, participation in voluntary programs, mandatory regulations, and customer demand. The analysis shows no major shifts in strategy after joining a green shipping network; however, it does show two ways that network membership may impact the way shipping companies work with emissions reduction. First, membership can lead to adjustments and smaller changes as shipping companies collect information about new trends and technologies. Second, one-on-one guidance and support for preparing funding applications from network administrations may lead to the adoption of zero-emissions technology or fuels.

Market-based measures and their impact on green shipping technologies

In the strategy on the reduction of greenhouse gas (GHG) emission of the International Maritime Organization (IMO), market-based measures (MBMs) are considered feasible mid-term measures. Thus, the relevance of MBMs for the shipping industry can be expected to grow in the future and, consequently, carbon and other GHG emissions will impact the investment appraisal for greening technologies. This paper illustrates the impact of carbon pricing on the valuation of greening technologies (especially wind-assisted propulsion technologies) and on the relevant decision-making. In this regard, the straightforward approach of a direct acquisition and installation of the respective technology is considered and compared against innovative financing models, such as shared savings. Hence, the Fuzzy Pay-Off Method (FPOM) is applied in order to visualize the risks and chances linked to MBMs. Due to the economic life of greening technologies, the results are already relevant for today’s investment appraisals, even though carbon pricing has not been enforced so far.

Research on Coupling Coordination and the Development of Green Shipping and Economic Growth in China

The shipping industry is an important indicator of economic development, and it is closely related to economic growth. At present, China’s economy has moved from a high-speed growth stage to a high-quality development stage. The popularization of the green shipping concept also creates higher requirements for sustainable economic development. The core innovation point of this paper is to construct an index system of green shipping and economic growth in China, and to measure the coupling coordination degree and relative development degree of the two through the comprehensive development index in the form of overall and regional division. This is rarely covered in the existing literature. By constructing an index system for green shipping and economic growth, this paper calculates a comprehensive development index for the two systems and studies the degree of coupling coordination and relative development of the comprehensive system. The results show that, first, during the observation period, the comprehensive system of green shipping and economic growth in China has maintained a growth trend, rising from a near imbalance to a good coordination level, and the two have developed into a synchronous state. Second, the development of the Yangtze River Delta has been relatively rapid, closely followed by that of the Pearl River Delta, while the Bohai Rim area has seen the slowest development. Since 2010, China’s comprehensive system of 11 coastal provinces has mostly left the imbalanced state and it entered the coordination state by 2019. The results of the study provide some suggestions for the coordinated development of green shipping and economic growth.

Electrical and Energy Systems Integration for Maritime Environment-Friendly Transportation

The policies against climate change require the reduction of greenhouse gas emissions of marine transportation. To reach the planned goals, the most promising approach is working both on ships improvement and ports redesign. The latter must enable the new green ships supply with sustainable electrical energy, by integrating shore connection systems, local renewables, and energy storage systems. In this paper, a methodology to obtain such an objective is proposed, capable of taking into account both ships’ and ports’ characteristics. The methodology workflow is explained through a case study, where two shore connection power sizes and two different operative approaches for recharging the ship onboard energy storage are considered. A discussion about the most suitable energy storage technologies is also provided. The case study shows how the methodology can be applied, as well as demonstrating that the port infrastructure has a direct effect on the ship environmental performance.

Riverside underwater noise pollution threaten porpoises and fish along the middle and lower reaches of the Yangtze River, China

The Yangtze River exhibits a high biodiversity and plays an important role in global biodiversity conservation. As the world's busiest inland river in regard to shipping, little attention has been paid to underwater noise pollution. In 2017, the underwater noise level in 25 riverside locations along the middle and lower reaches of the Yangtze River mainly at night time were investigated by using passive acoustic monitoring method. Approximately 88% and 40% of the sampled sites exhibit noise levels exceeding the underwater acoustic thresholds of causing responsiveness and temporary threshold shift, respectively, in cetacean. Noise pollution may impose a high impact on fish with physostomous swim bladders and Weberian ossicles, such as silver carp, bighead carp, goldfish and common carp, whereas it may affect fish with physoclistous swim bladders and without Weberian ossicles, such as lake sturgeon and paddlefish, to a lesser extent. Noise levels reductions of approximately 10 and 20 dB were observed in the middle and lower reaches, respectively, of the Yangtze River over the 2012 level. The green development mode of the ongoing construction of green shipping in the Yangtze River Economic Belt, including the development of green shipping lanes, ports, ships and transportation organizations, may account for the alleviated underwater noise pollution. Follow-up noise mitigation endeavors, such as the extension of ship speed restrictions and the study and implementation of the optimal navigation speed in ecologically important areas, are required to further reduce the noise level in the Yangtze River to protect local porpoises and fish.

Shore power management for green shipping under international river transportation

ABSTRACT Greenhouse gas emissions in the shipping industry have been a major challenge in the sustainability of international transportation. This paper studied shore power management for river shipping, which has become increasingly popular in some international transport networks. We discussed stakeholders’ incentives and concerns regarding shore power and found that vessel owners play one of the dominant roles in the wide implementation of shore power. Then, a mathematical model is developed to show the advantages of shore power by combining it with an analysis of the optimal oil inventory plan for vessels. When the plan of the oil inventory on vessels is well designed, using shore power could be more beneficial than oil even if the shore power has a higher price than the latter because using shore power can provide the vessel with more options to improve the oil inventory plan by reducing oil consumption during berthing and the number of refueling. Sensitivity analyses are conducted to obtain a better understanding of the impact of the parameters on the performance of shore power. Our policy suggestions and findings can shed lights on how to make incentive policies for a wider and easier implementation of shore power under international shipping.

Green Shipping—Multifunctional Marine Scrubbers for Emission Control: Silencing Effect

Scrubber systems abate the sulphur oxide emissions of engines when cheap fuel oils that are high in sulphur content are employed as combustibles. However, the ships with these voluminous devices installed on board is space demanding. This work analyses the feasibility of incorporating the acoustic abatement of the exhaust gas noise functionality into the scrubber design to provide a combined scrubber–silencer system. For this purpose, a finite element analysis is performed on a simple expansion chamber, which is assessed using both analytical and experimental data. The transmission loss is the acoustic parameter chosen in this work. The numerical model depicts a good correlation with the transmission loss measured on a model scale scrubber. Finally, scrubber geometry modifications alter the transmission loss, changing and/or enhancing its featuring. These abilities indicate the feasibility to confer to scrubber silencing effects.

Factors influencing green ship recycling: A conceptual framework and modeling

It is an environmentally friendly and economical way to send end-of-life ships for dismantling and recycling by the shipowners. More and more countries expressed concerns on the pollutants caused during ship dismantling and proposed green ship recycling concept. This study aims to propose the factors influencing green ship recycling and evaluate their interrelationships and effects on green ship recycling. By investigating the procedures and pollutants during ship dismantling, customized factors influencing green ship recycling were proposed. Questionnaire survey was designed and conducted by scholars, managers and workers in ship recycling field. The data were analyzed based on structure equation modeling with a proposed theoretical model. Overall, organization and management factor has the largest total effect on green ship recycling, followed by environmental protection facilities and plans factor and ship recycling technology and equipment factor. The environmental protection facilities and plans factor and ecological index factor are the direct contributors of green ship recycling. The theoretical implication of this study is discussed, as well as the managerial implication which could be beneficial to ship recycling companies and policy makers.

A comparison of dispersion models for the LNG dispersion at port of Koper, Slovenia

The challenges of ensuring green shipping and green ports force ports to adequately and safely implement engineered systems for the distribution and supply of LNG in port areas that meet the requirements of Seveso Directive. As the process of LNG bunkering is only seemingly similar to classical oil bunkering or liquid cargo, the handling of the technical and safety challenges is much more subject to investigation.In this work, the dispersion part of the consequences of LNG release, pooling, evaporation and dispersion during the future bunkering operation in the port of Koper, Slovenia, where the populated area (city) is located in close proximity. We follow the comparison of three different tools, namely the model Unified Dispersion Model (UDM) implemented by the software PHAST from DNV-GL® and two CFD (FDS - Fire Dynamics Simulator from NIST and Ansys Fluent®) in the same case scenario. Geometry, initial and boundary conditions are assumed to be the same as far as possible according to the limitations of the respective software tools. The simulation tools are first applied to a flat terrain model and later the models of CFD are compared, including the 3D geometry of the dock site in real size, with two relevant wind directions. The effects of evaporation rates on water and turbulence on CFD estimates are also given and numerically tested. The results of the applied models provide valuable information for further establishment of similar LNG leakage and dispersion models for simulation in ports or similar facilities.