Cargo Throughput Research Articles

Impact of COVID-19 pandemic on greenhouse gas and criteria air pollutant emissions from the San Pedro Bay Ports and future policy implications

The Ports of Los Angeles and Long Beach, collectively known as the San Pedro Bay Ports, serve as vital gateways for freight movement in the United States. The COVID-19 pandemic and other influencing factors disrupted freight movement and led to unprecedented cargo surge, vessel congestion, and increased air pollution and greenhouse gas emissions from seaport and connected freight system operations beginning in June 2020. In this study, we conducted the first comprehensive monthly assessment of the excess particulate matter, oxides of nitrogen (NOx), and carbon dioxide (CO2) emissions due to the heightened congestion and freight transport activity from ocean-going vessels (OGVs), trucks, locomotives, and cargo handling equipment (CHE) supporting seaport operations. Excess emissions peaked in October 2021 at 23 tons of NOx per day and 2001 tons of CO2 per day. The strategic queuing system implemented in November 2021 significantly reduced the number of anchored and loitering OGVs and their emissions near the ports, even during continued high cargo throughput until Summer 2022. Looking forward, we analyzed projected emissions benefits of adopted California Air Resources Board regulations requiring cleaner and zero-emission trucks, locomotives, and CHE over the next decade. If a repeated port congestion event were to occur in 2035, NOx emissions from land-based freight transport should be lessened by more than 80%. Our study underscores the potential emissions impacts of disruptions to the freight transport network and the critical need to continue reducing its emissions in California and beyond.

EFFICIENCY ASSESSMENT OF SOME DANUBE PORTS BY USING DEA WINDOW ANALYSIS

The aim of this paper is to empirically assess the efficiency / inefficiency of five Danube ports in five neighbouring countries and to observe how it evolves over an eight-year period ranging from 2014 to 2021. The five ports are located on the lower course of the Danube River and are the most important in their states: Smederevo (Serbia), Ruse (Bulgaria), Galați (Romania), Giurgiulești (Moldova), and Izmail (Ukraine). The study uses a mixed-method, namely the Data Envelopment Analysis (DEA) window analysis method and Andersen and Petersenʼs super-efficiency model to evaluate the efficiency of these ports over time. Port efficiency analysis is based on a single output, i.e. the cargo throughput, and four inputs: the total port area, the total area of warehouses, the quay length, and the number of cranes. It was determined that none of the five ports analysed reaches the maximum efficiency of 1.000, their average efficiency being quite low, only 0.631. The highest average efficiency is recorded by the Serbian port of Smederevo, with 0.768, this port being found to make good use of its resources for production. On the other extreme, the Bulgarian port of Ruse was found to be the least efficient port, obtaining the lowest average efficiency over an eight-year period, with only 0.360. The study tries to capture the causes of the inefficiency of selected ports and propose some measures to improve their efficiency.

Comparative analysis of hub and spoke seaport performance in Nigeria: Case of Apapa Port and Tin Can Island Port

Purpose: The primary aim of this study is to evaluate and compare the operational performance of two major seaports in Lagos, Nigeria – Apapa Port and Tin Can Island Port – using specific port performance indicators. Methodology: The study employs the Cobb-Douglas production function and the Ordinary Least Squares (OLS) method to analyse data sourced from the Nigeria Ports Authority's operational bulletin records. The analysis was conducted using E-view software version 10.0. Results: The findings indicate that cargo throughput, used as the dependent variable, has a strong positive linear relationship with ship traffic, berth occupancy, turnaround time, and the number of employees. The R2 value is 85.89% for Apapa Port and 98.79% for Tin Can Island Port, suggesting that Tin Can Island Port is more productive. Theoretical Contribution: This study contributes to the field of maritime transport and logistics by providing empirical evidence on the efficiency and productivity of Nigerian seaports. It highlights the importance of modern infrastructure and effective port operations in enhancing seaport performance. Practical Implications: The study recommends that the Nigerian government should focus on reducing port congestion, improving road conditions leading to the ports, and streamlining port documentation processes. These measures are essential for enhancing the operational efficiency of Nigerian seaports.

Research and application of a novel grey multivariable model in port scale prediction under the impact of Free Trade Zone

Purpose Considering the impact of the Free Trade Zone (FTZ) policy on forecasting the port cargo throughput, this paper constructs a fractional grey multivariate forecasting model to improve the prediction accuracy of port cargo throughput and realize the coordinated development of FTZ policymaking and port construction.Design/methodology/approach Considering the effects of data randomization, this paper proposes a novel self-adaptive grey multivariate prediction model, namely FDCGM(1,N). First, fractional-order accumulative generation operation (AGO) is introduced, which integrates the policy impact effect. Second, the heuristic grey wolf optimization (GWO) algorithm is used to determine the optimal nonlinear parameters. Finally, the novel model is then applied to port scale simulation and forecasting in Tianjin and Fujian where FTZs are situated and compared with three other grey models and two machine learning models.Findings In the Tianjin and Fujian cases, the new model outperforms the other comparison models, with the least mean absolute percentage error (MAPE) values of 6.07% and 4.16% in the simulation phase, and 6.70% and 1.63% in the forecasting phase, respectively. The results of the comparative analysis find that after the constitution of the FTZs, Tianjin’s port cargo throughput has shown a slow growth trend, and Fujian’s port cargo throughput has exhibited rapid growth. Further, the port cargo throughput of Tianjin and Fujian will maintain a growing trend in the next four years.Practical implications The new multivariable grey model can effectively reduce the impact of data randomness on forecasting. Meanwhile, FTZ policy has regional heterogeneity in port development, and the government can take different measures to improve the development of ports.Originality/value Under the background of FTZ policy, the new multivariable model can be used to achieve accurate prediction, which is conducive to determining the direction of port development and planning the port layout.

Modeling and simulation analysis of optimal layout scheme of aviation logistics park based on genetic algorithm

AbstractAs an important component of modern logistics industry, aviation logistics parks address the problems of unreasonable layout and low efficiency in traditional planning and construction methods. The study first constructed a grid model for optimizing the layout of functional areas in the aviation logistics park, and selected the layout scheme with the highest comprehensive correlation as the optimal planning. At the same time, three important model parameters were determined: prediction of cargo throughput, size of functional areas in the park, and comprehensive correlation values between functional areas. Subsequently, in response to the optimization problem of functional area layout in aviation logistics parks, a cosine adaptive genetic algorithm based on adaptive reversal operation was introduced to solve the model. According to the findings, the research mention algorithm has an average utilization rate of up to 69.64% in the international freight zone, which is a 12.38% improvement over the conventional genetic algorithm. Additionally, it has an average domestic cargo area utilization rate of 67.93%, 11.24% greater than the genetic algorithm. This demonstrated that the functional area layout scheme of the aviation logistics park produced by examining the suggested algorithm is extremely viable and offers new ideas and techniques for the planning and designing of aviation logistics parks.

Which ports differ in the copycat effectiveness of the hinterland strategy? Based on port-hinterland distance correlation

ABSTRACT With increasing cargo and intensifying competition, port differentiation needs to be considered for port expansion, investment and other decisions, as the effectiveness of the same strategies may be different for different ports. Under the concept of hinterland, this paper tries to distinguish large ports by the distance correlation with their hinterland. According to the evolution history of hinterland’s spatial structure, only the continent level or more advantaged port are uncorrelated with its continent level hinterland in distance. Following this idea, Granger causality test is applied to differentiate the ports. This paper uses Nighttime Light (NTL) data to represent the human activities of the hinterland for higher spatial accuracy and statistical consistency, rather than common economic indicators such as GDP. In the case of the European continent and surrounding ports, this paper has differentiated the container port by cargo throughput (TP) and liner shipping connectivity (LSC). In result, ports are divided by the presence and absence of port-hinterland distance correlation, and additionally these ports with port-hinterland correlations are divided into 4 groups. Ports can copycat strategies with each other only in same division, because the port-hinterland relationships among different divisions are not same.

Contextual Comparative Analysis of Dar es Salaam and Mombasa Port Performance by Using a Hybrid DEA(CVA) Model

Background: This research conducts a contextual comparative analysis between Dar es Salaam and Mombasa ports, employing a hybrid data envelopment analysis (DEA) model that integrates the contextual value-added approach (CVA). The assessment incorporates various inputs (quay length, number of cranes, and storage area) and outputs (number of ship calls and cargo throughput) to compute efficiency scores, offering nuanced insights into the strengths, weaknesses, and areas for improvement of both ports. Methods: The hybrid DEA model with CVA is applied to calculate efficiency scores, considering the diverse inputs and outputs. This approach allows for a comprehensive evaluation of the relative performance of Dar es Salaam and Mombasa ports. The study also explores the influence of trade-related externalities on port efficiency, providing a holistic understanding of the factors shaping the ports’ operational effectiveness. Results: The efficiency scores depict distinctive performance trends between Dar es Salaam and Mombasa ports. Notably, Dar es Salaam exhibits maximum efficiency (efficiency value of 1) in 2018 and 2021, while Mombasa attains optimal performance (efficiency value of 1) in 2021. However, efficiency values fluctuate for both ports in other years, ranging between 0.895 and 0.985 for Mombasa and 0.924 and 0.960 for Dar es Salaam. Conclusions: This study highlights the dynamic efficiency levels of Dar es Salaam and Mombasa ports over multiple years and identifies critical factors influencing their performance. The findings contribute valuable insights to the field of port analysis, offering guidance to port management and policymakers in optimizing the efficiency and competitiveness of these vital maritime hubs.

Real-time Tracking System for Distribution Information of Logistics Enterprises Based on IOT Technology

Logistics enterprise distribution information real-time tracking system in the actual application process, there is the problem of low cargo throughput, this study was aimed to design a kind of logistics enterprise distribution information real-time tracking system based on Internet of Things technology. In hardware part: control the reading and writing equipment according to the predetermined working mode, adjust the parameters of the reader, connect the circuit and other accessories; in software part: increase the correlation between the tables by setting foreign keys, build the logistics enterprise distribution information database, control and supervise the logistics activities. The result shows that the average value of cargo throughput between the real-time tracking system of distribution information of logistics enterprises in the paper and two other real-time tracking systems of logistics enterprises is 1412.14 T/H, 1049.38 T/H and 1088.81 T/H respectively, indicating that the real-time tracking system of distribution information of logistics enterprises designed after the application of IOT technology is more perfect.

Stochastic Frontier Analysis of Selected Nigerian Seaports Container Throughput’s Efficiency

This paper measures economic efficiency of container throughputs with the aid of input-output efficiency ratio of selected terminals across Nigerianseaports. Productivity of a terminal does not equal toits efficiency. Different efficiencies like allocative and technical characterized economic efficiency of a port system.Overall economic efficiency means there is no delay at the port in processing container as all ship, labour and machines are optimally utilized. This research determinedthe overall efficiencies of container throughputs Apapa, Warri, Onne, Calabal and Tin Can Island usingsecondary data (2012-2022) from Nigerian Bureau of Statistics oncontainer cargo throughputs in Nigeria. Total container outputsin (Tonnes) from different terminals with their corresponding inputs variables from number of ship per annum, cranes used and the dock workers net gang hour (ngh) were aggregated together in form of input-output ratio and arrived at each port’s level of overall economic efficiency. The analysis was executed with the aid of R using Stochastic Frontier Analysis(SFA)for each termina/seaport collected data. It was found from the results that;terminals at Onne are most efficient followed by Calabar. Tin can Island terminal efficiency was a slightly higher than that of Apapa as both had a little above average mean efficiency value. Warri terminals are the least while Rivers was not considered for unavailabilityof data. There may be other unexplained factors causing inefficiencies of mostly Apapa, Tin Can and Warri seaports not explained but can be investigated in future research.

Assessment of Container Terminal Operations in South-Western Ports in Nigeria

Containers, a global maritime trade influencer, have increased the importance of ports. Ports serve as an economic catalyst for revenue and employment. The importance of container transport cannot be overemphasized in international trade especially in Nigeria. Hence, it becomes expedients to assess the elements of container terminal capacity, analyse the trend of cargo throughput and as well determine the relationship between handling equipment and cargo dwell time in Western ports in Nigeria. The study adopts multistage sampling. Also, both primary and secondary data were collected from the staff of the container terminal operators in Tincan Island Port Complex and Apapa Port Complex and 347 respondents were chosen using Yamene formular. Furthermore, Descriptive statistics such as frequency table, line graph, bar charts were used to examine the elements of container terminal capacity, analyse the trend of cargo throughput. The inferential statistics such as regression analysis was used examines the relationship between thandling equipment and cargo dwell time. The result showed a decline in cargo throughput from 2019 to 2020, a trend that can be directly attributed to the COVID-19 pandemic. Also, it was shown that the coefficient of handling equipment is 0.725, indicating that for every unit increase in the handling equipment score, the cargo dwell time increases by 0.725 units. The t-value of 21.558 and a significance level of 0.000 signify that the handling equipment is a significant predictor of cargo dwell time. Based on the findings of the study, it was concluded that terminal space, handling equipment, daily stock and port labour were significant factors or elements of container terminal capacity. It was recommended that Nigerian Ports Authority should invest more on sustainable infrastructure and terminal operators and stevedoring company should train and retrain their staff on modern handling equipment.

Comparative study of two selected eastern port operational performance in Nigeria: Case of Rivers and Delta ports

Purpose: The main purpose of this paper is to compare the operational performance of two selected eastern ports in Nigeria: Rivers and Delta ports. Methodology: The paper uses secondary data from the Nigeria Port Authority (NPA) Portal from 2008 to 2013. The paper employs multiple regression models to analyze the data using SPSS and Statgraphics software packages. Results: The results show that Rivers port has a higher operational efficiency than Delta port, with an R-squared value of 81.34% and 79.47%, respectively. The results also reveal a significant relationship between cargo throughput and some independent variables, such as vessel traffic, turnaround time, berth occupancy, and number of employees. Theoretical contribution: The paper contributes to the existing literature on port performance measurement and improvement by applying multiple regression models to assess the operational efficiency of two Nigerian ports. The paper also provides empirical evidence on the factors affecting port performance in a developing country context. Practical implications: The paper has practical implications for port authorities, maritime agencies, shipping companies, and the government. The paper suggests some policy recommendations to enhance the operational performance of the eastern ports, such as improving port infrastructure, pricing policy, and strategic competition.

Neural network-based prediction system for port throughput: A case study of Ningbo-Zhoushan Port

Port throughput is a crucial indicator for assessing the efficiency of port enterprises. Accurately predicting long-term port throughput can help mitigate the risk of investing in major infrastructure during the development process. This study introduces a neural network-based system for predicting port throughput at the Ningbo-Zhoushan Port. By utilizing the grey relational analysis method, we identified 12 highly correlated factors that affect port throughput variation in Ningbo-Zhoushan Port. These factors were then used as input indicators for the BiLSTM model to predict port throughput. Our research indicates that the proposed model achieved a high level of accuracy, with a MAPE value of 2.95%, outperforming commonly used machine learning and neural network models. Additionally, the model's predictions suggest a rapid growth trend in cargo throughput at Ningbo-Zhoushan Port by 2026. Consequently, we provide relevant suggestions to address this trend. Our research can assist port enterprises in making informed decisions, contributing to the field of port logistics.

Port Reforms and Concession: A Study of Apapa and Tin Can Island Seaports

This research looked at the impact of port reforms and concessions on the management of ports in Nigeria, using Apapa and Tin Can Island Seaports as case studies. The study’s goal was to ascertain if the concessions at these ports had improved port infrastructure as well as decreased ship waiting time. The research was explained using the New Public Management Theory, which promotes the notion of developing a performance-oriented culture in a decentralised public sector. The survey research was used for the study, and this guided the use of a standardised questionnaire to gather information from the research participants. Hard data from the Nigerian Ports Authority supplemented this. Even though they cannot be compared to international best practices, the study’s results indicated that there have been advances in the level of turnaround time for oceangoing vessels, the level of cargo throughput, and the berth occupancy rate. As a result of this discovery, it was suggested, among others, that the government work with the concessionaires to increase infrastructure spending so that it is simple to enter and exit the port facilities. Additionally, steps should be taken to lessen the presence of MDAs and other security personnel at the ports.

Discrete-event modelling of container terminal cargo fronts

The basis for designing and upgrading new sea ports and container terminals is regulatory documentation. A part of designing a new sea port is making key technological decisions, including on calculating its cargo throughput capacity. However a method for capacity evaluation of operating ports is not described in the regulatory documents. Operating cargo terminals often undergo significant changes since the moment they were put into operation. Equipment, resources and infrastructure of cargo fronts should not be the only thing taken into consideration when evaluating an existing container terminal capacity. The way in which a terminal interacts with external transport systems (railroad, vessel fleet, etc.) as well as interactions between cargo fronts inside a terminal should also be considered. A discrete- event simulation model for the system consisting of a railroad cargo front, a container yard and a berth cargo front of a container terminal is proposed in the paper. This model allows to evaluate the balance between calls of different modes of transport (vessel calls, cargo train calls), as well as the impact of this balance on the state of container yard and on the terminal cargo throughput capacity in general. Container terminal in terms of proposed model is not merely a set of unrelated objects, but a system. In such system interaction with one of elements has influence on all the others. The model is described as mathematical dependencies between key variables. Cargo train and vessel calls generation is performed via standard spreadsheet methods. To acquire more accurate results, specific sea port statistical data should be used.

Optimizing Port Multi-AGV Trajectory Planning through Priority Coordination: Enhancing Efficiency and Safety

Efficient logistics and transport at the port heavily relies on efficient AGV scheduling and planning for container transshipment. This paper presents a comprehensive approach to address the challenges in AGV path planning and coordination within the domain of intelligent transportation systems. We propose an enhanced graph search method for constructing the global path of a single AGV that mitigates the issues associated with paths closely aligned with obstacle corner points. Moreover, a centralized global planning module is developed to facilitate planning and scheduling. Each individual AGV establishes real-time communication with the upper layers to accurately determine its position at complex intersections. By computing its priority sequence within a coordination circle, the AGV effectively treats the high-priority trajectories of other vehicles as dynamic obstacles for its local trajectory planning. The feasibility of trajectory information is ensured by solving the online real-time Optimal Control Problem (OCP). In the trajectory planning process for a single AGV, we incorporate a linear programming-based obstacle avoidance strategy. This strategy transforms the obstacle avoidance optimization problem into trajectory planning constraints using Karush-Kuhn-Tucker (KKT) conditions. Consequently, seamless and secure AGV movement within the port environment is guaranteed. The global planning module encompasses a global regulatory mechanism that provides each AGV with an initial feasible path. This approach not only facilitates complexity decomposition for large-scale problems, but also maintains path feasibility through continuous real-time communication with the upper layers during AGV travel. A key advantage of our progressive solution lies in its flexibility and scalability. This approach readily accommodates extensions based on the original problem and allows adjustments in the overall problem size in response to varying port cargo throughput, all without requiring a complete system overhaul.

Research on Second-Hand Sailboat Prices Based on Machine Learning

With the development of the international shipping market and changes in second-hand ship prices, the operation and trade of second-hand ships are quite active. To accurately evaluate the price of second-hand ships, it is particularly important to establish a pricing model for second-hand ships. The first part of this article uses X-GBoost and PCA to rank and reduce the importance of features, and obtains four principal components. Based on 5 indicators and their importance ratios, establish an optimized X-GBoost regression model for Sine Cosine Algorithm (SCA) to predict the price of second-hand ships. In order to further investigate the impact of regional characteristics on prices, local population density, per capita GDP, and cargo throughput were selected to further classify regional characteristics. A linear regression model was established to investigate the impact of population density, per capita GDP, and cargo throughput on regional error prices, and to explore the impact of various regional characteristics on error prices. Divide sailboats into three categories – low-end sailboats, mid-range sailboats, and high-end sailboats, and discuss the impact of regional characteristics on prices. The study found that there is a significant difference in the prices of low-end sailboats and mid-range sailboats between regions, indicating consistency in regional effects. Studying the pricing of second-hand sailboats can help to correctly select trading markets, develop marketing strategies, purchase ships with higher economic priority, and promote the development and prosperity of the sailing industry.

Spatiotemporal heterogeneity of the relationships between PM2.5 concentrations and their drivers in China's coastal ports

PM2.5 is one of the primary air pollutants that affect air quality and threat human health in the port areas. To prevent and control air pollution, it is essential to understand the spatiotemporal distributions of PM2.5 concentrations and their key drivers in ports. 19 coastal ports of China are selected to examine the spatiotemporal distributions of PM2.5 concentrations during 2013–2020. The annual average PM2.5 concentration decreases from 61.03 μg/m3 to 30.17 μg/m3, with an average decrease rate of 51.57%. Significant spatial autocorrelation exists among PM2.5 concentrations of ports. The result of the geographically and temporally weighted regression (GTWR) model shows significant spatiotemporal heterogeneity in the effects of meteorological and socioeconomic factors on PM2.5 concentrations. The effects of boundary layer height on PM2.5 concentrations are found to be negative in most ports, with a stronger effect found in the Pearl River Delta, Yangtze River Delta and some ports of the Bohai Rim Area. The total precipitation shows negative effects on PM2.5 concentrations, with the strongest effect found in ports of the Southeast Coast. The effects of surface pressure on PM2.5 concentrations are positive, with stronger effects found in Beibu Gulf Port and Zhanjiang Port. The effects of wind speed on PM2.5 concentrations generally increase from south to north. Cargo throughput shows strong and positive effects on PM2.5 concentrations in ports of Bohai Rim Area; the positive effects found in Beibu Gulf Port increased from 2013 to 2018 and decreased since 2019. The positive effects of GDP and nighttime light on PM2.5 concentrations gradually decrease and turn negative from south to north. Understandings obtained from this study can potentially support the prevention and control of air pollution in China's coastal ports.

Analyzing the Relationship between Cargo Throughput and Total Ship Traffic in Lagos, Lomé, and Tema Seaports using TOMS: A Comparative Study

Analyzing the Relationship between Cargo Throughput and Total Ship Traffic in Lagos, Lomé, and Tema Seaports using TOMS: A Comparative Study

An empirical study on the economic linkage characteristics of Yangtze River port cities based on discrete second-order derivatives

Abstract Rapid economic development cannot be achieved without a well-developed trade in goods of various forms, so it depends on the construction and development of coastal or inland ports. How to coordinate the relationship between ports and cities in the development process is of great significance to the sustainable development of port cities, and is also an important part of the current research on ports. This paper uses gray correlation model to study the correlation between city economic development indexes and port development indexes, and finds that the correlation between GDP and gross industrial output value and port cargo throughput is the largest, and on the basis of gray correlation analysis, the impulse response analysis finds that the growth of total economic volume and gross industrial output value of port cities has an obvious promotion effect on the development of ports in the short term. The research results show that the value added of Nanjing’s tertiary industry drives the port logistics of Nanjing port most significantly; the growth rate stabilizes at 0.006 after the 11th period. The growth of Nanjing port container throughput on the value added of Nanjing’s secondary industry changes most significantly and finally stabilizes at 0.0035.

Evaluation and obstacle factors of marine resources and environment carrying capacity in Beibu Gulf Urban Agglomeration

With the strong support of the Chinese government, the Beibu Gulf Urban Agglomeration has responded positively to the national call to vigorously develop the marine economy. However, a series of marine resource and environmental problems such as over-exploitation of marine resources and excessive discharge of marine pollutants in the Beibu Gulf Urban Agglomeration has also arisen along with the rapid development of the marine economy, limiting the space for the development of the marine economy in the Beibu Gulf Urban Agglomeration. Based on the panel data of seven coastal cities in the Beibu Gulf urban agglomeration from 2011-2021, the DPSIR model was used to construct a marine resources environmental carrying capacity evaluation index system including five dimensions of driving force, pressure, state, impact and response, and the TOPSIS model with combined weighting was used to make a comprehensive evaluation of the marine resources carrying capacity of the Beibu Gulf urban agglomeration, and then the barrier degree model was used to explore the barriers to the carrying capacity of marine resources and environment in the Beibu Gulf Urban Agglomeration. The empirical results show that, on the whole, the marine resources and environment carrying capacity of the seven coastal cities in the Beibu Gulf Urban Agglomeration show an upward trend. From the situation of each subsystem, the pressure subsystem and response subsystem have greater evaluation values, while the evaluation of the driving force, state, and influence subsystem needs to be improved; from the analysis of obstacle factors, the main single indicator obstacle factors include per capita coastline length, total import and export volume, and port cargo throughput, etc. The status subsystem is the main classification indicator barrier factor affecting the improvement of the marine resource and environmental carrying capacity of the Beibu Gulf Urban Agglomeration. Based on the results of the empirical analysis, corresponding suggestions are put forward.