Arctic Routes Research Articles

How environmental data enables intelligent navigation: Factors assessment of affecting the navigation in the Northeast Arctic Route

Due to the more favorable navigational environment and higher safety along Northeast Arctic Route, this route is being used more and more frequently for international shipping. In this research, the factor analysis method is applied to assess the navigational environment of each sea area in the Northeast Arctic Route, revealing the effects of Arctic navigation influence factor on the navigational environment, and analyzing the change trend of the navigational environment of different sea areas in different seasons. Further, the effects of multiple factors on the number of voyages are discussed through multiple stepwise regression model, including the navigational environment score, geopolitical risk, export & import trade and the probability of pollution accidents, then the Interrupted time series analysis (ITSA) method combined with seasonal decomposition is explored the effect of emergencies on the number of voyages on the Northeast Arctic Route. The number of voyages on the Northeast Arctic Route has been altered to varying degrees by the occurrence of various emergencies. Further, the Yamal LNG project and the Russian-Ukrainian conflict have a significant effect on the number of voyages, while the Covid-19 epidemic has a lesser effect on the number of voyages.

Generalized transport costs in intermodal shipping: the context of the Northeast Passage

Intermodality is regarded as one way of achieving more sustainable transport solutions. To make intermodal transport the preferred solution among shippers, it must be attractive according to the concept of generalized transport costs. An extended model for generalized transport costs is developed which includes elements important for comparing maritime transport solutions in the Artic. This framework forms the basis for a principal discussion on the conditions that make one transport solution preferable to another within the context of maritime logistics. This model is then applied to the context of the Northeast Passage to discuss the necessary requirements for making an intermodal transport solution attractive relative to the current main route from Northeast Asia to Northwest Europe through the Suez Canal. Even though intermodality could be preferable in principle, current solutions cannot compete with either Arctic routes using unimodal solutions with high ice-class vessels or with the Suez route. Due to uncertainty and limited empirical evidence, a sensitivity analysis is conducted, focusing on the variables with the greatest impact on the result. Policymakers and stakeholders can consider the findings to improve transport competitiveness via the Northeast Passage.

Advanced Human Reliability Analysis Approach for Ship Convoy Operations via a Model of IDAC and DBN: A Case from Ice-Covered Waters

The melting of Arctic ice has facilitated the successful navigation of merchant ships through the Arctic route, often requiring icebreakers for assistance. To reduce the risk of accidents between merchant vessels and icebreakers stemming from human errors during operations, this paper introduces an enhanced human reliability assessment approach. This method utilizes the Dynamic Bayesian Network (DBN) model, integrated with the information, decision, and action in crew context (IDAC) framework. First, a qualitative analysis of crew maneuvering behavior in scenarios involving a collision with the preceding vessel during icebreaker assistance is conducted using the IDAC model. Second, the D–S evidence theory and cloud models are integrated to process multi-source subjective data. Finally, the human error probability of crew members is quantified using the DBN. The research results indicate that during convoy operations, the maximum probability that the officer on watch (OOW) chooses an incorrect deceleration strategy is 8.259×10−2 and the collision probability is 4.129×10−3. Furthermore, this study also found that the factors of Team Effectiveness and Knowledge/Abilities during convoy operations have the greatest impact on collision occurrence. This research provides important guidance and recommendations for the safe navigation of merchant ships in the Arctic waters. By reducing human errors and adopting appropriate preventive measures, the risk of collisions between merchant ships and icebreakers can be significantly decreased.

Fungal aerosols over the Northwest Pacific to Arctic Ocean: The influence of air mass and environmental factors

Bioaerosols, prevalent in the atmosphere, serve as carriers for microbe transmission and can also act as Cloud Condensation Nuclei (CCN) and Ice Nuclei (IN), exerting significant influence on cloud microphysics, radiative forcing, precipitation processes, and global climate dynamics. In this study, we conducted a comprehensive study of airborne fungi from the Northwest Pacific to the Arctic Ocean. During the 9th Chinese National Arctic Research Expedition (Chinare, 2018) cruise, total suspended particulate matter (TSP) samples were collected, followed by high-throughput sequencing to determine the microbial community's structure. Ascomycota and Basidiomycota are widespread in marine fungal aerosols along this route, with a notably higher abundance of Epicoccum and Cladosporium in fungal aerosols from the low-latitude Northwest Pacific compared to the high-latitude Arctic Ocean region. The composition of fungal communities depended on air mass transport processes and environmental factors. Long-range transport of terrestrial air masses not only enriches the abundance of fungal aerosols but also increases the relative abundance of dominant genera such as Basidiomycota, Epicoccum and Cladosporium. The knowledge gap about fungal aerosols over the Arctic route from the Northwest Pacific to the Arctic Ocean was filled in part by this work. This study deepens our understanding of how environmental factors and terrestrial air masses influence the composition and distribution of fungal community, offering valuable insights into the interconnections between marine and terrestrial ecosystems and their potential impacts on climate and atmospheric processes.

Influence of sea ice on ship routes and speed along the Arctic Northeast Passage

The accelerated melting of sea ice and the growing influx of ships in the Arctic pose significant challenges to navigational safety and the resilient development of the Arctic routes. This study aims to explore the influence of sea ice on ship routes and speed by analyzing the spatiotemporal correlation of Sea Ice Concentration (SIC), Sea Ice Thickness (SIT), Sea Ice Volume (SIV), and Automatic Identification System (AIS) data along the Northeast Passage (NEP) in 2022. Our findings indicate that during the navigation window period (July–October), 115 ships traversed the NEP. It was observed that ships preferred navigating at speeds ranging from 6kn to 14kn when the SIC was below 10% and the SIT was less than 0.1m. Compared with cargo ships and tankers, the trajectory and speed distributions of other ships show greater differences under the influence of sea ice. Furthermore, our results suggest that the SIV, compared to the SIC and SIT, could better reflect the influence of sea ice on ship navigation. These insights are crucial for developing management strategies in Arctic routes.

Projected navigability of Arctic shipping routes based on climate model FIO-ESM v2.1

As Arctic sea ice has rapidly declined, the navigational potential of the Arctic routes has greatly increased. Based on sea ice output from the First Institute Of Oceanography-Earth System Model version 2.1 (FIO-ESM v2.1) and the Arctic Transport Accessibility Model, this study investigates the future navigability of the Arctic routes for open-water ships (OW) without icebreaking capabilities and ships with different icebreaking capabilities, namely Polar Class 7 (PC7), Polar Class 6 (PC6), and Polar Class 3 (PC3). The results show that the simulations of FIO-ESM v2.1 adequately reproduce the changes in the navigability of the four types of ships in Arctic shipping routes over the past 40 years. The navigable area for the four ship types is projected to continue to expand in the future. Under the high emission scenario (Shared Socioeconomic Pathways 5–8.5, SSP585), the four ship types are projected to achieve full Arctic navigability in summer (September) by the end of the 21st century, and PC6 and PC3 ships are projected to achieve full Arctic navigability in winter (March). Under the high emission scenario, year-round navigability in the Northwest Passage is projected for PC3 and PC6 ships, and in the Northeast Passage is projected for all four types of ships. The impact of emission scenario on the navigability of the Arctic shipping routes varies with different ship types: the largest impact is for OW ships, followed by PC6 and PC7 ships, and the smallest impact is for PC3 ships. The impact of scenario is also larger in winter than in summer.

Evaluation of navigation capacity in the Northeast Arctic passage: evidence from multiple factors

ABSTRACT Arctic ice is melting away as a result of global warming, making possible the further commercial exploitations of the Arctic shipping routes, both to satisfy the shipping demand and to avoid the growing Somali piracy. In this research, the hierarchical regression is utilized to examine the impact of natural and economic factors on the Northeast Arctic Route (NER) through sample data on cargo volume from 2011 to 2021. From the results, the natural factors related to sea ice have a negative impact on the navigability of the NER, whereas economic factors and sea ice melting periods have a positive impact. Additionally, all variables are standardized to compare their respective significances on the cargo volume. Furthermore, Russian energy exports have a greater impact on shipping capacity than other variables, followed by the number of ship transits. Finally, the interrupted time-series analysis is introduced to find that the project of Yamal liquefied natural gas (LNG) has a positive effect on the NER, which could not offset the side effect of the COVID-19 epidemic.

The impact of opening the Arctic Northeast Passage on China's carbon emissions

The increase in shipping along Arctic routes has resulted in an increasing need for the environmental effects of shipping to be considered. Existing studies on the environmental impact of Arctic routes have focused mainly on shipping operations and have paid little attention to the dynamic features of opening new shipping routes. In light of the continuing retreat of Arctic sea ice, this study aimed to predict changes in China's CO2 emissions from a production perspective via scenarios of the opening of the Arctic Northeast Passage (NEP) in different future years (2025, 2030, 2035). A shipping cost model was first developed to calculate the changes in shipping costs resulting from commercial use of the NEP. Then, an energy-environmental version of the Global Trade Analysis Project (GTAP-E) model and the GTAP-E 10.0 database were used to simulate the changes in CO2 emissions that may arise from the economic adjustments to the opening of the NEP. The driving factors and possible mechanisms of the environmental effects of the NEP were analyzed based on the simulation results. The re-simulation for the environmental effects of opening the NEP taking emission control policies into account was performed. The findings showed that the opening of the NEP would increase global CO2 emissions. This effect would gradually increase over time. For China, opening the NEP would initially reduce short- and medium-term CO2 emissions owing to upgrades of sectoral structure, while ultimately elevating emissions in the long run due to a large expansion in trade and the economy. The economic growth driven by commercial use of the NEP would tend to optimize the Chinese sectoral and energy structure in the short run. Notably, emission control policies would markedly affect the aforementioned environmental outcomes of opening the NEP.

Trend Research on Maritime Autonomous Surface Ships (MASSs) Based on Shipboard Electronics: Focusing on Text Mining and Network Analysis

The growing adoption of electric propulsion systems in Maritime Autonomous Surface Ships (MASSs) necessitates advancements in shipboard electronics for safe, efficient, and reliable operation. These advancements are crucial for tasks such as real-time sensor data processing, control algorithms for autonomous navigation, and robust decision-making capabilities. This study investigates research trends in MASSs, using bibliographic analysis to identify policy and future research directions in this evolving field. We analyze 3363 MASS-related articles from the Web of Science database, employing co-occurrence word analysis and latent Dirichlet allocation (LDA) topic modeling. The findings reveal a rapidly growing field dominated by image recognition research. Keywords such as “datum”, “image”, and “detection” suggest a focus on collecting and analyzing marine data, particularly with deep learning for synthetic aperture radar imagery. LDA confirms this, with “image analysis and classification research” as the leading topic. The study also identifies national and organizational leaders in MASS research. However, research on Arctic routes lags behind that on other areas. This work provides valuable insights for policymakers and researchers, promoting a deeper understanding of MASSs and informing future policy and research agendas regarding the integration of electric propulsion systems within the maritime industry.

Research on the competitiveness of the Arctic transportation route under the belt and road initiative

AbstractWith the continuous improvement of the navigation environment of the Arctic routes, the commercialization potential of the Arctic routes is enhanced, which brings new challenges to the Suez Canal route and the China–Europe railway Express. In addition, geopolitical factors such as the Russia–Ukraine conflict and the Red Sea crisis have also brought some impact on the Eurasian transport pattern. In this context, the future trade and transportation between China and Europe will take on a new pattern. In order to study the transport competition pattern between China and Europe under the opening of the Arctic routes, this article takes into account the time‐value cost of goods and geopolitical factors, constructs a logit competition model, and quantitatively investigates the competitiveness of the Arctic route and the traditional routes of the “Belt and Road Initiative” using major international transportation hub cities in China. The results show that the types of cargo and the level of freight are important factors affecting the competitiveness of Arctic routes. Under the influence of geopolitics, the competitive advantage of the Arctic routes are highlighted.

Environmental Risk Analysis of Different Segments of The Arctic Northeast Route

There are huge differences in the sea ice conditions, climate and environment, geographical conditions and communication conditions in the Arctic waters, and the equipment and navigation requirements of ships are also different. In order to ensure the safety and success of the ships, through the route, this paper using fuzzy level analysis (Fuzzy Analytic Hierarchy Process, FAHP), build the northeast arctic route risk evaluation index system, targeted analysis of different segments, the results show that: (1) although the sea risk point is different but the natural environment risk has a significant impact on the arctic waters.(2) The risk coefficient of Arctic route is higher than that of traditional ordinary routes. Among the five sea areas in this study, Chukchi Sea is the highest, followed by East Belia Sea. The crew need to pay more attention when sailing.(3) The research in this paper can provide a reference for the navigation safety of the northeast Arctic shipping route.

Research on the hydroelastic response of ice floes and wave scattering field

Abstract The marginal ice zone (MIZ) is the area between sea ice and open water, the structure of which is mainly determined by wave and ice interactions. Thus mastering the characteristics of MIZ is of great significance to the Arctic routes opening and the natural resources development. In this paper, the hydroelastic response of ice floes in waves is studied, a three-dimensional numerical wave tank is established based on the computational fluid dynamics (CFD) technology. The finite volume method (FVM) and finite element method (FEM) are respectively utilized for discrete fluid domain and ice domain. A mapping interface at the junction of the fluid and ice floes domains is created to perform data mapping by the shape function interpolation method and the least square method. This work presents a series of numerical simulations to study the fluid-solid interaction (FSI) of waves and ice floes. Under the given incident wave parameters, the vertical bending deformation of ice floes with different shapes under the excitation of waves, the effect of ice floes' deformation on the wave field are studied, and the effect of wave overwash on the transmitted wave field is emphasized. Results show that the shape of the ice floes significantly affects its elastic deformation and scattered wave field, and the wave overwash phenomenon attenuates the scattering wave.

Арктиканың көліктік-транзиттік әлеуеті және Қытай: проблемалар, мүмкіндіктер және перспективалар

The Arctic region, with its changing climate and shrinking sea ice, has significant potential for transport and transit activities, especially for countries looking for new trade routes and resource exploration opportunities. This article examines the transport and transit potential of the Arctic and its significance for China. Particular attention is paid to the Arctic routes, including the Northern Sea Route, the Transpolar Sea Route and the Northwest Passage. In addition, the paper examines China's involvement in the development of Arctic infrastructure, as well as the potential benefits and future prospects for China in the use of Arctic transport routes. Through in-depth analysis, this article elucidates the evolving dynamics of transport and transit in the Arctic and its implications for China's economic and strategic interests.

An empirical study of Sino-European trade geographic regional competition under the Belt and Road and Arctic Routes based on transportation cost equilibrium line model

An empirical study of Sino-European trade geographic regional competition under the Belt and Road and Arctic Routes based on transportation cost equilibrium line model

Changes in Accessibility of Chinese Coastal Ports to Arctic Ports under Melting Ice

Global warming has accelerated the melting of Arctic sea ice, providing favorable conditions for Arctic shipping. Arctic ports are gaining prominence in shipping networks and international trade. Accessibility is a key indicator of port facilitation, and identifying trends in Arctic port accessibility holds significance for Arctic route planning and port development. To achieve this, this paper develops a modeling framework for assessing the accessibility of Arctic ports. First, we utilize the Coupled Model Intercomparison Project (CMIP6) model to predict sea ice conditions and quantify the navigation risk for open water (OW) vessels and Arc4 ice-class (Arc4) vessels during the summer months of 2030–2050. The A-star (A*) algorithm is then used to plan the vessel’s shortest route while avoiding high-risk waters. Finally, changes in the accessibility of Arctic ports are calculated by using an improved gravity model. The framework is applied for the quantitative analysis of the accessibility of Chinese coastal ports to Arctic ports. The results indicate that accessibility to Arctic ports will gradually increase for all Chinese ports in the future, with the port of Shanghai continuing to maintain its prominence under the trend of melting sea ice.

Daily-Scale Prediction of Arctic Sea Ice Concentration Based on Recurrent Neural Network Models

Arctic sea ice prediction is of great practical significance in facilitating Arctic route planning, optimizing fisheries management, and advancing the field of sea ice dynamics research. While various deep learning models have been developed for sea ice prediction, they predominantly operate at the seasonal or sub-seasonal scale, often focusing on localized areas, and few cater to full-region daily-scale prediction. This study introduces the use of spatiotemporal sequence data prediction models, namely, the convolutional LSTM (ConvLSTM) and predictive recurrent neural network (PredRNN), for the prediction of sea ice concentration (SIC). Our analysis reveals that, when solely utilizing SIC historical data as the input, the ConvLSTM model outperforms the PredRNN model in SIC prediction. To enhance the models’ capacity to capture spatiotemporal relationships between multiple variables, we expanded the range of input data types to form the ConvLSTM-multi and PredRNN-multi models. Experimental findings demonstrate that the prediction accuracy of the four models significantly surpasses the CMIP6 model in three prospective climate scenarios (SSP126, SSP245, and SSP585). Of the four models, the ConvLSTM-multi model excels in assimilating the influence of reanalysis data on sea ice within the sea ice edge region, thus exhibiting superior performance than the PredRNN-multi model in predicting daily Arctic SIC over the subsequent 10 days. Furthermore, sensitivity tests on various model parameters highlight the substantial impact of sea surface temperature and prediction date on the accuracy of daily sea ice prediction, and meteorological and oceanographic parameters primarily affect the prediction accuracy of the thin-ice region at the edge of the sea ice.

Exploring the Economic Significance of Arctic Routes in the Supply Chain Field by Contrasting with Traditional Route

With global climate warming, the reduction of Arctic ice and the opening of shipping routes during the summer season, the Arctic route has gradually become an important choice in the field of supply chains as it connects Asia, Europe, and North America. It offers the advantages of reducing shipping time, lowering transportation costs, expanding trade opportunities, and diversifying supply chain routes. This article collected data from websites such as the Clarksons and the Shanghai Shipping Exchange to investigate the current number of voyages along the Arctic route and various factors that impact the cost of navigation. By comparing the navigation costs between the Arctic route and the traditional Suez Canal route, it was found that the Arctic region has higher voyage transportation costs compared to the Suez route, indicating that the Suez route still holds an economic advantage. However, choosing the Arctic route can shorten the delivery lead time and reduce certain supply chain costs.

A data-driven risk assessment of Arctic maritime incidents: Using machine learning to predict incident types and identify risk factors

The rise in Arctic temperatures has caused sea ice to melt, making the region more navigable through a new, shorter shipping route. Navigating the Arctic poses high risks due to extreme environmental conditions. This study proposes scalable data-driven predictive models to assess the risk of Arctic navigation under uncertain weather and sea ice conditions. Machine learning is applied to predict the type of Arctic incidents and identify their risk factors. Several models are investigated, and the most accurate model for the two Arctic routes, the North West Passage (NWP) and the Northern Sea Route (NSR), is determined based on several validation metrics. Random forest and Naïve Bayes models provide the best accuracy and F1-score for NWP and NSR, respectively. The wind speed, vessel type, length, and age are important risk factors for NWP while temperature at 2 m above the surface, vessel length, and age are important for NSR. Partial dependence plots are used to investigate the effect of each feature on predicting each incident type. Equipment failures are more common among newer and longer vessels. Collision related incidents are more likely to be predicted for longer vessels, while grounding related incidents are more frequent at higher air temperature.

Numerical Investigation of Global Ice Loads of Maneuvering Captive Motion in Ice Floe Fields

During escort and convoy operations, icebreakers are often required to maneuver to open up channels or adjust routes due to the prevalence of ice floe conditions in Arctic routes. This study aimed to investigate the global ice load characteristics of the maneuvering captive motions, including constant turning motion, pure yaw motion, and pure sway motion, of the icebreaker Xue Long, using a combination of the discrete element method (DEM) and drag model. First, the method was verified using simulating Araon model tests from the Korea Institute of Ocean Science and Technology (KIOST). In addition, the maneuvering captive motions of the Xue Long model were simulated at varying turning radii, drift angles, and sway and yaw periods, which are typical but currently poorly studied maneuvering motions. Overall, the results of the study showed that the method is able to reproduce the coupling effect of the ship–ice–water system by considering ship–ice interaction and ice resistance, where the mean deviation and maximum deviation of ice resistance are 9.45% and 13.3%, respectively. The influences of the turning radius, drift angle, and sway and yaw period on the ice resistance and transverse force characteristics were studied and analyzed via ship–ice interactions. The present study provides a prediction tool for the assessment of ship maneuvering performance to assist the hull line development and model testing of icebreakers.

PolarGAN: Creating realistic Arctic sea ice concentration images with user-defined geometric preferences

In this paper, we introduce a novel generative adversarial network (GAN), called PolarGAN, that is capable of creating realistic artificial images of Arctic sea ice concentration (SIC) for data augmentation. One of the key features of the PolarGAN is that it considers real-valued geometric preferences, defined by six statistics, to generate SIC images that align with specific geometric characteristics. Unlike other GANs that also consider user-defined preferences, the PolarGAN allows for more detailed control over the shape and size of the generated images by using differentiable projection functions to convert the created images into geometric features, and a newly-designed loss function to minimize the gap between the user-defined preferences and the geometric features of the generated images. Through extensive experimentation, we compare the PolarGAN with other GANs and demonstrate artificial SIC scenarios that can be used to test the performance of algorithms for Arctic route planning in edge cases or to improve data-driven models such as SIC prediction models which require additional data to avoid overfitting issues.