PNNL

Abstract

Global shipping accounts for 13% of global emissions of SO2 which, once oxidised to sulphate aerosol, acts to cool the planet both directly by scattering sunlight and indirectly by increasing the albedo of clouds. This cooling due to sulphate aerosol offsets some of the warming effect of greenhouse gasses and is the largest uncertainty in determining the change in the Earth’s radiative balance by human activity. Ship tracks – the visible manifestation of the indirect of effect of ship emissions on clouds as quasi linear features – have long provided an opportunity to quantify these effects. However, they have been arduous to catalogue and typically only studied in particular regions for short period of times. Using a novel machine learning algorithm to automate their detection we catalogue more than one million ship tracks to provide a global climatology. We use this to investigate the effect of stringent fuel regulations introduced by the International Maritime Organization in 2020 on their global prevalence since then, while accounting for the disruption in global commerce caused by COVID-19. We find a marked, but clearly non-linear, decline in ship tracks globally: an 80% reduction in SOx emissions causes only a 25% reduction in the number of tracks detected.