Reducing emissions of atmospheric pollutants along major dry bulk and tanker routes through autonomous shipping

Abstract

The present study investigates the environmental benefits of phasing-in autonomous ships in global maritime transportation along major dry bulk and tanker routes using Bayesian probabilistic forecasting algorithm. The focus is on the simulations and calibrations on the navigational behavior of autonomous ships at both port and high-sea, as well as the potential emission abatement of atmospheric pollutants compared to the conventional fleet along the sailing routes. We use historical data on major international tanker and dry bulk trade routes to characterize the ship movements and trends in ship emission. Different scenarios are evaluated with a combination of autonomous ship phase-in rates (25, 75, 100%) and cleaner fuel choices in Years 2030 and 2050 (from the baseline Year, 2020). The results show that the magnitude of the emission reduction generally increases with a higher level of autonomous ships in the fleet as expected, and the magnitude ranges from small increments to major reductions of 37-64% along the different routes. Overall, we hope that our findings can contribute towards the realization of environmental benefits with the adoption of autonomous shipping along the major shipping routes in the future.

Keywords: Autonomous shipping; Bayesian forecasting; Emission; Port-to-port optimization.