Estimation of land-based emissions during container terminal operations in the Ambarlı Port, Turkey

Many types of mobile vehicles are used simultaneously in container terminal operations. Because most of these mobile vehicles have diesel engines, they emit a significant amount of pollutant emissions into the atmosphere during their operation. They are considered as land-based mobile emission sources (MobES) and should be included in the total port emission inventory. The emission inventory is a basic requirement in developing an environmental management strategy to improve emission control. In this context, this study aims to estimate the emission inventories of mobile vehicles used in terminal operations in the Ambarlı container ports located in the city of Istanbul, which is one of the most populous cities in the world. In this respect, the amounts of the emissions of all the container handling equipment with diesel engines in the port areas, including external trucks delivering/receiving containers to/from the port were estimated using an activity-based method. It has been found that approximately 42.39% of the total CO2 emission is owing to terminal tractors and the total annual CO2 value per TEU (Twenty-foot Equivalent Unit) of MobES is 0.01259 tons. The CO2 value per TEU can serve as a CO2 emission performance indicator for land-based MobES in process of the evaluation of emission inventories in container ports.

An Investigation into Switching Vessel Sizes for Efficient Container Terminal Operations: A Case Study of Kaohsiung Port

Given the continued growth in the size of container ships, major hub ports around the world have carried out large-scale upgrades of their port facilities to attract shipping companies to choose their ports, thereby enhancing the competitiveness of their ports. This study takes Kaohsiung Port as an example and uses the Decision Analytic Network Process (DANP) method to investigate container terminal operations by switching container terminal operations to appropriate new locations. The results of the study indicate that, despite the external issues (such as a lack of deep-water terminals and hinterland in the port area, the upsizing of ships, and new strategic shipping alliances), Kaohsiung Port authority must accelerate the upgrade of its container terminals, integrate its port resources to build deep-water berth facilities with highefficient container operating system, and improve the operating efficiency of its existing terminals, as a means to maintain the status of Kaohsiung Port as a regional centre.

A hybrid framework for evaluating the performance of port container terminal operations

This work intends to integrate artificial neural network (ANN) and data envelopment analysis (DEA) in a single framework to evaluate the performance of operations in the container terminal. The proposed framework is based on three steps. In the first step, a proposed identify the performance measures objectives and the indicators affecting the system. In the second step, the efficiency scores of the system are computed by using the Charnes Cooper and Rhodes (CCR) model (oriented inputs). In the last step, the Moth Search Algorithm (MSA) is employed as a new method for training the Feedforward Neural Network (FNN) to determine the efficiency scores. To demonstrate the efficacy of the proposed framework, two container terminals of Tangier and Casablanca are adopted to evaluate the performance.