Ship emissions assessment by automatic identification system and big data in Latin America

Abstract

Automatic Identification System (AIS) data records a high quantity of information regarding the safety and security of ships and port facilities in the international maritime transport sector. However, the big databases are not only useful for these safety functions. It can also be helpful for other areas in maritime traffic, such as reducing environmental impacts, improving logistics, and examining compliance with current International Maritime Organization (IMO) regulations. The purpose of this research is to provide a ship emission inventory and an assessment of the efficiency of several technical options to reduce the impact of ocean-going ships on the atmosphere and climate. In other words, this work aims to examine how technological improvements and policy strategies might help reducing emissions from international shipping in the future. Input data for these approaches were collected from different sources and maritime databases such as the worldwide ship fleet register and AIS database. The present proposal assess how possible improvements in technology or alternative energies and fuels could impact the future evolution of ship emissions. Three cases of studies are developed to estimate ship emissions based on AIS. The last case study added an application of scenarios, and it defined considering a combination of technologies and several future ship traffic demand scenarios mainly determined by the economic growth. The prediction is for 2050. The result shows how alternative energies and fuels could impact almost 50% of most minor ship emissions, concurrently implementing newly introduced international policy measures. In conclusion, a better quantitative understanding of the efficiency and impact of the technical alternative to reduce ship emissions may help the decision-makers to improve their strategies.