Assessment of Ship Emission Inventory in Strait of Malacca and Singapore based on Automatic Identification System Data

Abstract

This study is conducted to develop a comprehensive ship emission inventory in Strait of Malacca and Singapore (SOMAS) based on Automatic Identification System (AIS) data using the bottom-up method. With spatiotemporal analysis on the maritime traffic in SOMAS, it is implied that limited space and dense, complex shipping routes had created hindrances to the local traffic. Gaussian approach Kernel Density Estimation (KDE) is adopted to find the hotspot of the traffic and emission in SOMAS. Among all emitted pollutants estimated, nitrogen oxides (NO <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">x</inf> ) shared the most proportion among pollutants by maritime. With the argumentation of more NO <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">x</inf> emission generated under slow engine speed, the environment in SOMAS had favoured its generation. With over 100,000 ship trajectories compacted within the port waters and turning points between Johor and Singapore strait, it was found that the highest contributor of emissions came from containership as a result of slow steaming. Other cargo ships also contributed substantially on the emissions as a result of long period of manoeuvring or hotelling. The result presented draws the attention about the environmental impact caused by ship emissions.