Ship emission projections based on time series forecasting model for sustainable shipping in the strait of Malacca and Singapore

Abstract

As maritime activities continue to play a pivotal role in global trade, concerns over ship emissions' environmental impact have intensified. This study presents detailed projection of ship emissions in Strait of Malacca and Singapore (SOMS), based on Automatic Identification System (AIS) data. By harnessing the rich AIS dataset, emission profiles were developed out of the ship activities data. To envision a sustainable maritime future, we incorporate some possible scenarios around the region combined with a time series forecasting model to project the future conditions of ship emission in SOMS. By analysing the conditions in each scenario, essentials for shaping intelligent systems for efficient maritime traffic can be discovered. Our analysis considers evolving factors such as various ship properties, operational modes, and trajectories. The results provide insights for policymakers, industry stakeholders, and environmental planners seeking to mitigate the local maritime sector's carbon footprint. This study signified the value of AIS data-driven approach to facilitate regional strategist in confronting resolutions for greener maritime operation, aligning with the transition to intelligent and sustainable practices in the maritime industry within the SOMS.