Ports In China Research Articles

Port Service Coordination Sustainability in the Yangtze River Delta in China Based on Spatial Effects

With the prevalence of international trade protectionism and transformation and the upgrading of the domestic market structure, the contradiction between the demand for and the competitive development of the port market in the Yangtze River Delta in China has become increasingly prominent. The 19 major ports of the Yangtze River Delta in China were selected for this study, and using the methods of index evaluation, gravitational model, and spatial interpolation, the spatial effects in the hinterland were calculated from three dimensions, central potential, spatial gravity and distribution convenience, and the regional coordination of port services. The results show that the potential of the Shanghai Port and Ningbo Zhoushan Port in China is stronger, and the difference in the distribution of the ports is quite clear. The spatial gravity of each port city can be superimposed over one another to form a clear dense semi-circular zone, and the ability of the marginal ports to participate in this zone is weak. The convenience of their distribution in the hinterland changes from being location-dependent to traffic-dependent. The service gap in the hinterland of the port system is more significant, but the expansion of spatial effects makes the sustainability of regional coordination gradually improve. Finally, several policy suggestions are proposed to ensure ecological responsibility among resource-oriented enterprises.

Charting sustainable vistas: Analysis of internal and external sustainability performance of Chinese ports

The global economy's rapid expansion highlights the need for sustainable development in ports. However, existing research has overlooked the crucial aspect of social sustainability. To address this gap, this paper evaluates ports' sustainability using a novel framework that combines cross-hierarchical data envelopment analysis and cross-efficiency. Examining 18 ports in China from 2017 to 2020, we assess their internal and external sustainability dimensions. Results show that most ports demonstrate commendable efficiency in internal sustainability, though room for improvement remains. In terms of external sustainability, some ports excel economically and socially, but environmental indicators require more attention. Overall, sustainability performance shows an encouraging upward trend, with southern ports leading in sustainability practices. However, economic factors pose challenges to port development, emphasizing the need for heightened focus on environmental and social dimensions. By filling a knowledge gap and offering valuable recommendations, this study introduces a fresh perspective on sustainable port development.

Port governance and sustainable development: The impact of port smartization on port carbon emission efficiency

Considering the growing volume of seaborne trade worldwide, most ports need smart policies to address high carbon emissions. As a major shipping nation, China is committed to reducing port carbon emissions. China recently introduced a series of smartization policies to accelerate the construction of smart ports, but their effectiveness in energy saving and emission reduction is unclear. Taking 39 major ports in China as research subjects, this study uses the super-efficiency SBM model to measure carbon emissions and the generalized difference-in-differences method to deeply explore the impact of port smartization policies on port carbon emission efficiency. Results indicate that these policies have significantly improved the carbon emission efficiency of ports, a conclusion validated through multiple robustness tests. Heterogeneity analyses show that ports in coastal areas, and in cities with larger populations or moderate economic development, are more significantly affected by port smartization initiatives. Mechanism analysis suggests that the number of port berths, the length of wharves, and container throughput are important channels through which smart port policies influence carbon emission efficiency. This research enriches carbon emission efficiency literature, offers insights for developing countries on reducing emissions and achieving carbon neutrality, and provides a basis for China's smart port construction.

Laser-Induced Breakdown Spectroscopy and a Convolutional Neural Network Model for Predicting Total Iron Content in Iron Ores.

Laser-induced breakdown spectroscopy (LIBS) is a rapid method for detecting total iron (TFe) content in iron ores. However, accuracy and measurement error of univariate regression analysis in LIBS are limited due to factors such as laser energy fluctuations and spectral interference. To address this, multiple regression analysis and feature selection/extraction are needed to reduce redundant information, decrease the correlation between variables, and quantify the TFe content of iron ores accurately. Overall, 339 batches of iron ore samples from five countries were obtained from the ports of China during the discharging, and 2034 representative spectra were collected. A convolutional neural network (CNN) model for total iron content prediction in iron ores is established. The performance of variable importance random forest (VI-RF), variable importance back propagation artificial neural network (VI-BP-ANN), and CNN-assisted LIBS in predicting the TFe content of iron ores was compared. Coefficient of determination (R2), root mean square error (RMSE), mean relative error (MRE), and modeling time were selected for model evaluation. The result shows that variable importance significantly enhances the quantitative accuracy and reduces modeling time compared to traditional BP-ANN and RF models. Moreover, the CNN model outperformed manual feature selection methods (VI-BP-ANN and VI-RF), exhibiting the shortest modeling time, highest R2, lowest RMSE, and MRE. CNN model's unique characteristics, such as weight sharing and local connection, make it well suited for analyzing high-dimensional LIBS data in multivariate regression analysis. Our approach demonstrates the effectiveness of machine learning and deep learning approaches in improving the accuracy of LIBS for TFe content prediction in iron ores. CNN-assisted LIBS method holds great potential for practical applications in the mining industry.

Analysis of Financing Issues in China's Port Infrastructure Construction under the Background of Intelligence

Analysis of Financing Issues in China's Port Infrastructure Construction under the Background of Intelligence

A Proposed Coupling Framework of Biological Invasions: Quantifying the Management Prioritization in Mealybugs Invasion

ABSTRACTPrioritizing potential invasive alien species, introduction pathways, and likely places susceptible to biological invasions is collectively critical for developing the targeting of management strategies at pre‐border, border, and post‐border. A framework for prioritizing the invasion management that considered all these elements in combination is lacking, particularly in the context of potential coinvasion scenarios of multispecies. Here, for the first time, we have constructed a coupling framework of biological invasions to evaluate and prioritize multiple invasion risks of 35 invasive alien mealybugs (IAMs) that posed a significant threat to the agri‐horticultural crops in China. We found that the imported tropical fruits from free trade areas of the Association of Southeast Asian Nations to entry ports of southern China were the primary introduction pathway for IAMs, vectored on various fruit commodities. There was also a high probability for cointroductions of potential multi‐IAMs with a single imported tropical fruit. The potential distribution of such IAMs with dissimilar net relatedness were mainly located in southern China. These distributions, however, are likely to expand to the higher latitudes of northern China under future climate and land use/land cover changes. Temperature and anthropogenic factors were both independently and collectively determining factors for the diversity and distribution patterns of imported IAMs under near‐current climate conditions. Our findings highlight that these multiple components of global change have and will continue to facilitate the introduction and establishment risks of IAMs in southern China, as well as the spread risk into northern China. Additionally, our findings, for the first time, demonstrated management prioritization across the continuous invasion stages of 35 IAMs in China, and provide additional insights into the development of targeting of their biosecurity and management decisions.

Secular variation and risk factors of preterm birth in Hainan, the Free Trade Port in China from 2010 to 2021

ObjectivesPreterm delivery rates have increased obviously worldwide over the past decade, yet reliable epidemiological studies on the incidence of preterm birth and temporal trends are not available in Hainan, The Free Trade Port in China. We aimed to describe the rate of preterm birth and trends between 2010 and 2021 and to primarily explore risk factors associated with preterm birth in Hainan, China.MethodsThis was an observational study was based on data from the Hainan Provincial Birth Certificate System (HPBCS) for live births between 1 January 2010 and 31 December 2021. We included pregnancies resulting in at least one live birth, with newborns born at a gestational age of 28 weeks or greater, or with a birth weight of 1000 g or more. The outcome were preterm birth rates and their trends over time. Potential risk factors were collected, including infant gender, maternal age, paternal age, maternal ethnicity, paternal ethnicity, home address, and single or multiple pregnancies. The logistic regression model was used to assess the relationship between preterm birth and potential risk factors.ResultsA total of 1,537,239 live births and 86,328 preterm births were investigated, giving a total preterm birth rate of 5.62%. The overall preterm birth rate increased from 4.47% in 2010 to 7.12% in 2021 (compound annual growth rate [CAGR] 4.32). The CAGR of late preterm birth is consistent with the overall preterm birth rate (4.32%). The fastest growth is observed in the rate of very preterm births (5.53%), while the rate of moderate preterm births exhibits the slowest growth (3.87%). Infant gender, multiple pregnancy, home address, parental age, and ethnicity had significant effects on preterm birth.ConclusionThe preterm birth rate was increasing year by year from 2010 to 2021 in Hainan, The Free Trade Port in China. Incidence of preterm births in Hainan Province in relation to multiple pregnancies, infant sex, parental age, parental race and residential address.

Spatial-temporal characteristics of port infrastructures on sulfur-oxide concentrations of coastal port in China

Port infrastructure is an important guarantee to support the development of shipping trade and a main link to connect shipping routes, where its construction and expansion promote economic progress whereas exacerbating regional pollution. Based on the panel data of 18 above-scale coastal ports in China from 2005 to 2020, the spatial characteristics and correlation of sulfur-oxide (SOX) concentrations are first analyzed, then the spatial Durbin model (SDM) is established to evaluate the extent of port infrastructure's impact on the concentrations, further the intermediation effects of three dimensions on the concentrations are explored. From the outcome, the influences of port infrastructures on the SOX concentrations are from decreasing the SOX concentrations through improving the operational efficiencies and increasing the SOX concentrations by adding the operational equipment, which also shows significant spatial spillover effects. In addition, the mechanical dimension as a mediation makes the trade dimension have an indirect effect on the SOX concentrations. This paper employs a spatial econometric model to analyze panel data from 18 coastal ports and ports of higher tiers in China, spanning from 2005 to 2020. It uncovers the intricate mechanism by which port infrastructure influences SOX concentration, thus providing a scientific foundation and decision support for environmental protection and sustainable port development.

Finding alternative stepwise improvement paths with different improvement effects

Targets on the data-envelopment-analysis (DEA) efficient frontier show the direction of inefficient decision-making units’ (DMUs) improvements. Some authors have correlated the improvement effects of targets with management needs. Nevertheless, targets are unattainable for DMUs with poor performance. Hence, stepwise improvement paths with different improvement effects should be provided to solve the problem of unachievable targets and flexibly meet decision-makers’ (DMs) diverse management needs in performance improvement. For this purpose, we propose novel stepwise DEA benchmarking approaches and a search algorithm to find progress-improvement strategies with different improvement effects. The contributions of our approaches are as follows. (1) Several stepwise improvement paths with different improvement effects are found, which provides DMs with more abundant alternatives for performance optimization in various management situations. (2) The upper bound for efforts in all intermediate improvement steps can be effectively controlled, which overcomes the problem of unachievable targets and makes stepwise improvement paths more feasible. To illustrate our approaches, we conducted a case study on 18 ports in China. In this case study of Chinese ports, we further highlighted the advantages of our methods by comparing them with existing DEA models. In sum, our approaches are suitable for poorly performing units that aspire to align performance improvements with management needs.

High-Level Feature Fusion Deep Learning Model for Fault Detection in Handling Equipment in Dry Bulk Ports

The flexibility of handling equipment in dry bulk ports is poor, and frequent equipment fault induced by the high-load and high-power working conditions greatly impacts the overall port handling operations, making accurate fault detection play an important role in improving the efficiency and stability of dry bulk port operations. However, as we know, most fault detection methods for port handling equipment depend heavily on monitoring sensor data, which is not applicable in the dry bulk port due to high configuration and maintenance cost, as well as the high false alarm rate of monitoring sensors caused by strong background noise. To solve the problem, this study proposes a High-Level Feature Fusion Deep Learning Model, which uses different deep learning sub-models to extract features of structured and unstructured data. It fuses the extracted feature vectors to achieve fault detection in the handling equipment, establishing the mapping relationship between the fault (e.g., waiting for the pre-loading process, equipment fault, and others) and multi-source heterogeneous operation and maintenance data for the handling equipment, including reclaimers, belt conveyors, dumpers, and ship loaders. To verify the effectiveness of the proposed method, the actual data of a coal port in Northern China is employed as an example. The results show the deep learning model can achieve high prediction accuracy (over 86%) with high efficiency (0.5 s for each sample), which provides decision support for the fault detection in dry bulk port handling equipment.

Adaptation planning of container ports in the context of typhoon risks: The case of Ningbo-Zhoushan port in China

This study conducts a comprehensive survey of the risk of typhoon to container ports by assessing the risk level of typhoons in China's major container ports, predicting their economic losses, and evaluating corresponding adaptation measures. It analyzes adaptation measures in response to typhoon impacts, with a case study of Ningbo-Zhoushan port, one of China's most representative regional ports. It identifies the inadequate supply of institutions and the absence and misbehavior of the main port stakeholders as the main cause of varying institutional imperfections in the port adaptation system. This study contributes to the development of efficient port typhoon prevention policies, reduction of economic losses and casualties, and improvement of port operational efficiency. It also fills an important research gap on climate risk and adaptation in China's container ports, with an emphasis in enhancing port resilience.

Motivation and Performance Analysis of Spin-offs and Listings: A Case Study of Ningbo-Zhoushan Port

Spin-off and listing is one of the means of contractile asset operation. This paper takes Ningbo Zhoushan Port (hereinafter referred to as Ningbo Port), the first case of "A split A" of China's port and shipping enterprises, as the research object, explores the motivation of Ningbo Port's spin-off and listing of Ningbo China Ocean Shipping(Group) Company (COSCO), and analyzes the risks of the spin-off to enterprises and market investors based on some financial indicators of the parent and subsidiary before and after the spin-off. The results show that from the perspective of the overall spin-off effect, the spin-off effect of Ningbo Port is not significant. From the perspective of the realization of specific motivations, the spin-off of Ningbo COSCO by Ningbo Port conforms to the external development trend and the characteristics of the enterprise in its own mature stage. From the perspective of market reaction, the market is not optimistic about the prospect of this spin-off, and the stock price of Ningbo Port has fallen before and after the spin-off. At the same time, after Ningbo Port spun off Ningbo COSCO and listed, Ningbo Port's control over Ningbo COSCO has declined, which also makes investors worried. This study hopes to provide a reference for the spin-off and listing of Chinese port enterprises in terms of broadening financing channels and reducing market information asymmetry.

Analyzing foreland dynamics in China's port clusters under global major events (2019–2022) by AIS trajectory data

Port foreland, serves as the maritime mirror of the hinterland, encompasses the ports and overseas markets interconnected through shipping services. During major global events, understanding port foreland structures becomes imperative for nations and port authorities to anticipate future trade trends and potential coastal management risks. However, systematic approaches for accurately identifying foreland structures remain lacking, particularly given liner shipping complexities. In response, this paper develops two algorithms to analyze changes in the foreland structure of five port clusters in China for the years 2019 and 2022, leveraging over 2.1 billion global vessel AIS trajectory signals. We aim to understand the foreland dynamics of China's ports amidst the broader impacts of the China-US trade war, the COVID-19 pandemic, and the Russia-Ukraine (RU) conflict, and provide insights for maintaining the global trade continuity. Our findings show that geopolitical events and bilateral relations highly influence port foreland structures, yet global supply chain requirements prompt stakeholders to adopt alternative transport strategies. In 2022, China's foreland structures remain stable despite its strict epidemic control measures. Positive developments in China's port forelands with the US are driven by improving bilateral relations and reduced impacts of the US-China trade war, while conflicts in RU cause shrinkage in Europe. On this basis, we provide three constructive opinions on the development of China's port clusters.

Life Cycle Assessment of Large-Scale Solar Photovoltaic Plant based in Malaysia

Abstract A cradle-to-grave life cycle assessment (LCA) has been performed on a Large Scale Solar Photovoltaic (LSSPV) plant based in Peninsular Malaysia to study the detailed environmental impact of its life cycle. The LSSPV, with a capacity of 78 MWdc, is currently one of Malaysia’s largest solar power plants. The different life cycle phases of the LSSPV, starting from resource manufacturing and transportation, through plant construction and electricity generation, and to decommissioning of the plant, were assessed using the SimaPro software with the Ecoinvent v3.8 database. Results show that the overall emission rate for the LSSPV is 0.0309 kgCO2eq/kWh. It is estimated that the construction phase of the power plant, which includes activities such as infrastructure works and production of PV modules and Balance of System, yields the largest amount of kgCO2eq/kWh emission at 85.7% and imposes the highest environmental impact as compared to the other phases. The second biggest contributor is attributed to the transportation phase, contributing to 14.0% of the total kgCO2eq/kWh emission, of which most of the emission is emitted during the sea freight transportation of PV components from China port to Malaysia port (12.4%). A sensitivity analysis was performed to compare the environmental impact between open ground installation and the slanted roof installation mounting system of LSSPV. The findings from LCA proposed that open-ground installation has a greater negative impact on the environment because it involves additional land clearing and infrastructure transformation. The findings from this study serve as a benchmark for the LSSPV system in Malaysia and present technical perspectives for the future development of PV projects considering environmental impacts across the project lifetime.

Exploring the evolution trends of port integration policy in China by a text mining approach

Ports are essential and strategic nodes of international trade and economic activities. The integration of port resources helps enhance the optimal division of port functions to further promote economic development. This paper explores the evolutionary trends of port integration policy from 2011 to 2021 in China through a text-mining approach. We first used the Latent Dirichlet Allocation (LDA) topic analysis method to analyze the port integration policies and summarize the evolutionary trends of port policies. In addition, an association analysis was conducted to explore port integration policies' impacts by examining their relationships among the environmental protection, digitalization level, and port development scale. Our findings suggested that China's port integration policy has evolved from specific and simple to abstract and complicated at the managerial level. Port development has enriched from infrastructure construction to the ideology of economic development. Our findings show that China's port integration is gradually improving the port operation. The findings of the study contribute to the extant literature by analyzing the port integration policy evolution in China and can be referred to by other countries.

Impact of Ship Emission Control Area Policies on Port Air Quality—A Case Study of Ningbo Port, China

The implementation effectiveness of ship emission control area (ECA) policies can be effectively evaluated using econometric models. However, existing studies mainly focus on changes in SO2 concentrations in the air. In order to comprehensively assess the impact of ECA policies on air quality, this study takes Ningbo Port in China as an example and uses a regression discontinuity (RD) model to analyze the influence of ship emissions around the wharf on concentrations of SO2, NO2, and particulate matter (PM) in the air. The results indicate that individual ships’ activities within the monitoring area (within 300 m) make a relatively small contribution to the concentration of SO2 in the air and do not form a significant breakpoint. However, there is a noticeable breakpoint in the concentration of NO2 around the monitoring point as the ship approaches. At the same time, the variation range of PM2.5 is significantly greater than that of PM10, which aligns with the characteristics of PM emitted by ships. The experimental results have passed three robustness tests, demonstrating that the current policy on ship ECAs has a positive limiting effect on SO2 emissions and, to some extent, reduces PM emissions. However, further reductions in ship emissions may require more restrictions in nitrogen oxide emissions.

Data-driven study of container handling charges in coastline ports of China

With the rapid development of networking and digitization, the data generated by various industries has shown exponential growth. The seaport industry is the fundamental industry to support the operation of the national economy, and undertakes the vast majority of China's foreign trade, materials, and coal transport along the sea. In response to some of China's major seaports of container handling charges for different extent of the upward event. In this paper, by researching the main seaports of China's coastal ports, we have obtained the level of container handling charge, and operating cost of container section. Meanwhile, this paper combines the reform history of China's port container charging policy and the comparison of domestic and foreign charging levels to discover the cost structure of the container handling charges. It establishes the benchmark for the optimization of the container handling charges. Utilizing data analysis related to production and operations, this paper proposes an optimization method of container handling charges based on the cost analysis of container port companies with macro and micro coupling and puts forward effective suggestions on this basis. This paper suggests the establishment of a mechanism for regulating container handling charges. It also proposes a mechanism for monitoring and regular announcement of container costs.

Analysis of the Network Efficiency of Chinese Ports in Global Shipping under the Impacts of Typhoons

With the increasing volume of international trade and maritime demand, the requirements for the stability and reliability of the global shipping system are also increasing. The research on the network efficiency of Chinese ports for global shipping can not only examine the importance of Chinese ports in the shipping network but also find out the aspects that need to be improved in the construction of the port’s climate adaptability in the resilience assessment to strengthen port construction and further improve the efficiency of the network. The current study builds a shipping network based on RCEP and systematically examines the key ports in China within the networks. The research paper aims to improve the resilience of the ports and the whole shipping network in response to typhoon disasters. As such, this paper focuses on shipping research based on complex networks and network multi-centricity analysis, followed by a ranking of ports. Firstly, this paper uses UCINET 6 software to build a global shipping network. Such a network evaluates the centrality of ports, calculates the degree of centrality, proximity to centrality, and centrality, and scores them according to the ranking. Then, it selects the top 20 ports in China according to the ranking and researches network efficiency for the listed ports considering the typhoon risks. The analysis of network robustness, average shortest path length, and network efficiency are carried out for the shipping network and China’s essential port nodes in the network. According to the experimental results, no matter the robustness, average shortest path length, or network efficiency, when the important ports of China in the shipping network are affected, they will cause different degrees of impact, and the performance loss caused by multiple ports is higher than that of a single port. They emphasise the significant impact of typhoons on multiple ports and remind people to minimise losses as much as possible based on experimental results, ensuring the stable operation of ports and improving resilience in typhoon prevention under the changing climate. Additionally, they provide a solid foundation to further sustain global shipping network resilience.

An empirical study of the performance of the sixth generation ports model with smart ports with reference to major container ports in mainland China

Since the UNCTAD proposed the initial port model, called the first generation port model (1GP) in 1994, its adaptation and transformation have evolved, reflecting not only the evolution of port operations and technological advancements, but also the resilience of ports to natural disasters and supply disruptions. Recently, the trio of COVID-19, digitalization, and decarbonization (CDD) has emerged as core challenges whilst providing numerous opportunities for building adaption and resilience for the port industry. In light of this, the sixth generation ports (6GP) model has emerged. This paper addresses crucial research gaps by empirically testing the 6GP model, emphasizing the impact of emerging factors of the CDD, including 1) the lack of empirical testing for the 6GP model and the emphasis on the CDD; 2) the exploration of factors contributing to the significant development of Chinese container ports; 3) the investigation into how the CDD lead to the reversal of the port devolution continuum path. In doing so, an empirical study has been conducted, focusing on six major container ports in mainland China, all of which are among the world’s top 10 container ports in terms of container throughput. It evaluates the importance of the criteria of the 6GP model with the performance of the six ports. The findings of this research are discussed for managerial and policy implications, enriching the existing literature on port devolution, and providing the port industry with a holistic view of port development and strategy in the post-pandemic period.

Study on the coupling coordination effect and dynamic relationship between tourism development and the ecological environment: a case study of Hainan Island

As a Free Trade Port in China, the protection of ecological environment and high-quality tourism development on Hainan Island have become a national strategy. Exploring the coupling relationship of the two subsystems holds great practical significance for promoting the island’s international demonstration area and high-quality development. Based on the characteristics of international islands, a comprehensive index system is established to explore the coupling coordination evolutionary process and interactive stress relationship of tourism development and the ecological environment in Hainan Island from 2005 to 2020. The results show: (1) From 2005 to 2019, the comprehensive evaluation index of the two subsystems of Hainan Island generally showed a continuous growth trend. (2) From 2005 to 2019, the coupling degree of the two subsystems of Hainan Island strengthened continuously, the coupling coordination degree increased steadily from a moderate imbalance to good coordination, and tourism development and the ecological environment entered a stage of parallel and benign interactive development. (3) In 2020, affected by COVID-19, the tourism development indicators declined rapidly, while the ecological environment still maintained a rising trend. (4) Based on the inverted U-shaped curve model, when the tourism development index reaches 0.7269, the ecological environment quality reaches the maximum value of 0.7956, which is the best state between the two subsystems. The ecological environment and tourism development of Hainan Island are generally in a benign interaction, but there are signs of interactive stress starting in 2017. In the future, the pressure on the ecological environment of Hainan Island will increase.