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Under the low-carbon background, 37 ports of countries along the South China Sea with capacity ranking in the world's top 100 container ports are selected as the research object to establish a shipping network, construct a directed dichotomous shipping network, and divide the port tiers after finding the kernel number by using kernel analysis method, respectively, to explore the relationship between tiers and the relationship between ports at the higher level, and then make clear the direction of the improvement for the reduction of carbon emissions. The results show that: the routes sent between container ports in countries along the South China Sea have formed a more stable connection, but the receiving routes are still in a passive position, and the port call relationship is affected by the port hierarchy. High-level ports such as Shanghai Port and Singapore Port undertake the transshipment function of cargo concentration and redistribution within the network. The small-world characteristics among ports such as Singapore Port, Ningbo Port, Haiphong Port, Shenzhen Port, Guangzhou Port, and Linchaban Port are obvious. Based on the results of the empirical analysis, corresponding suggestions are put forward to optimize the structure of the container port system in the countries along the South China Sea and promote the low-carbon development of the sea.

The optimization of empty container repositioning nets has become an essential problem in low-carbon port cooperation. This paper proposed three optimization models of multi-port low-carbon empty container repositioning considering threshold under input and output of empty containers as random variables. Non repositioning strategy means the highest threshold, and complete-repositioning strategy means the lowest threshold; threshold-repositioning strategy is in the middle. The probability of empty-container inventory in each port and the storage cost, repositioning cost, lease cost, and carbon emission cost of empty containers are calculated. This paper mainly compares each cost of three models. The results have shown that: (1) Compared with the non repositioning strategy, the threshold-repositioning strategy and complete-repositioning strategy can reduce the ports storage costs and lease costs of empty containers and also reduce carbon emissions. The lower the repositioning threshold of empty containers between ports is, the more obvious the advantages of the threshold-repositioning strategy become. (2) When the cost of storage per empty container increases, under three strategies, the total cost, storage cost, lease cost, and carbon emission cost of the port will all increase. The ports proportion of dependence on its own empty-container storage will decrease, and the proportion of dependence on other ports and leasing companies will both increase.

The huge fuel consumption of shipping activities has a great impact on the ecological environment, port city environment, air quality, and residents' health. This paper uses Automatic Identification System (AIS) data records and ship-related data in 2021 coastal waters of the United States to calculate pollutant emissions from ships in 30 ports of the United States in 2021. After calculating the pollutant emissions from ships at each port, the multiscale geographically weighted regression (MGWR) model is used to analyze the factors affecting the ship pollutant emissions. Geographically weighted regression (GWR) model is used to investigate the spatial heterogeneity of various factors affecting the characteristics of ship pollutant emissions at different scales. This paper mainly compares the effect of models of GWR and MGWR. MGWR may truly reveal the scale difference between different variables. While controlling the social and economic attributes, the coastline length, container throughput, and population are used to describe the spatial effects of ship pollutant emissions in the United States. The results denote that the distribution trend of ship pollutant emissions has a gap based on various ship types and ports. NOx accounts for the highest proportion of pollutant emissions from port ships, followed by SO₂ and CO. The impact coefficients of coastline length and population on pollutant emissions in port areas are mostly positive, indicating that the growth of coastline length and population will increase pollutant emissions in port areas, while the effect of container throughput is opposite. Relevant departments should put forward effective measures to curb NOx emission. Port managers should reasonably plan the number of ship transactions according to the coastline length of the port.

Port and maritime studies dealing with containerization have observed traffic concentration and dispersion throughout the world. Globalization, intermodal transportation, and technological revolutions in the shipping industry have resulted in both network extension and rationalization. However, lack of precise data on inter-port relations prevent the application of wide network theories to global maritime container networks, which are often examined through case studies of specific firms or regions. This paper presents an analysis of the global liner shipping network in 1996 and 2006, a period of rapid change in port hierarchies and liner service configurations. While it refers to literature on port system development, shipping networks, and port selection, it is one of the only analyses of the properties of the global container shipping network. The paper analyzes the relative position of ports in the global network through indicators of centrality. The results reveal a certain level of robustness in the global shipping network. While transhipment hub flows and gateway flows might slightly shift among nodes in the network, the network properties remain rather stable in terms of the main nodes polarizing the network and the overall structure of the system. Additionally, mapping the changing centrality of ports confirms the impacts of global trade and logistics shifts on the port hierarchy and indicates that changes are predominantly geographic.

Port operator APM Terminals, part of Denmark's A.P. MØLLER-MAERSK, is buying 11 container ports from Spanish shipping and logistics group Perez y Cia to boost its presence in emerging markets and better serve bigger container vessels.

Port operator APM Terminals, part of Denmark's A.P. MØLLER-MAERSK, is buying 11 container ports from Spanish shipping and logistics group Perez y Cia to boost its presence in emerging markets and better serve bigger container vessels.

PortGraphic: COVID-19 and how vulnerable are European container ports to the drop in Chinese port volumes?

An investigative piece exploring the importance of tugboats for berthing mega-ships at container ports...

An investigative piece exploring the importance of tugboats for berthing mega-ships at container ports...

The port of Singapore has posted lower container throughput in January compared to the year-ago period, according to preliminary estimates released by the Maritime and Port Authority of Singapore (MPA).

China's top container ports unclog backlog as virus curbs ease.

Largest Container Ship at Zeebrugge Port.

Traffic decline in container ports: the exception or the new normal?

Port of LA Container Volumes on the Rise.

Giant Container Ships Arrive On US Shores, But Many Ports Not Prepared For Era Of Megaships.

Port of Seattle to Redevelop Container Terminal for Cruise Uses.

U.S. Container Ports Seeing Impact of China's Coronavirus Slowdown.

Video: 15,000 TEU Container Ship Topples STS Crane at Port of Busan.

Video: Container Ship Destroys STS Crane at Port of Antwerp.

Turkey to open its largest container port in June.

China, as a major maritime nation, the China Containerized Freight Index (CCFI) serves as an objective reflection of the Chinese shipping market and an important indicator for understanding China's shipping industry globally. The shipping market is a complex ecosystem influenced by various factors, including vessel supply and demand, cargo supply and demand relationships and prices, fuel prices, and competition from substitute and complementary markets. To analyze and study the state of the Chinese shipping market, we selected the CCFI as an indicator and collected data on six factors that may affect the overall shipping market. These factors include "the China Coastal Bulk Freight Index(CCBFI)", "the Baltic Dry Index(BDI)", "the Yangtze River Container Freight Index", "Global: Aluminum (minimum purity of 99.5%, London Metal Exchange (LME) spot price): UK landed price", "Major Ports: Container Throughput", and "Coal Price: US Central Appalachia: Coal Spot Price Index". Then, we constructed an analyticaland predictive framework using Deep Neural Network (DNN), CatBoost regression model, and robust regression model to study the CCFI. Based on the R2 results of the three models, it is evident that DNN provides the best analytical and predictive performance for the CCFI, accurately forecasting its changes. Additionally, the robust regression model indicates that "Global: Aluminum (minimum purity of 99.5%, LME spot price): UK landed price" has the greatest impact on the CCFI. Finally, from a business perspective, we provide some suggestions for China's container shipping industry.

Fisherman's Protest in Brazil Stalls Container Port.