Shipping regulations lead to large reduction in cloud perturbations.
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Published version
Author(s)
Type
Journal Article
Abstract
Global shipping accounts for 13% of global emissions of SO2, which, once oxidized to sulfate aerosol, acts to cool the planet both directly by scattering sunlight and indirectly by increasing the albedo of clouds. This cooling due to sulfate 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 catalog and typically studied only in particular regions for short periods of time. Using a machine-learning algorithm to automate their detection we catalog more than 1 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 nonlinear, decline in ship tracks globally: An 80% reduction in SO[Formula: see text] emissions causes only a 25% reduction in the number of tracks detected.
Date Issued
2022-10-11
Date Acceptance
2022-08-16
Citation
Proceedings of the National Academy of Sciences of USA, 2022, 119 (41), pp.1-5
ISSN
0027-8424
Publisher
National Academy of Sciences
Start Page
1
End Page
5
Journal / Book Title
Proceedings of the National Academy of Sciences of USA
Volume
119
Issue
41
Copyright Statement
© 2022 the Author(s). Published by PNAS.
This open access article is distributed under Creative
Commons Attribution License 4.0 (CC BY).
This open access article is distributed under Creative
Commons Attribution License 4.0 (CC BY).
License URL
Sponsor
Royal Society
Identifier
https://www.ncbi.nlm.nih.gov/pubmed/36191195
Grant Number
URF\R1\191602
Subjects
aerosol
climate
machine learning
shipping
COVID-19
Greenhouse Gases
Humans
Respiratory Aerosols and Droplets
Ships
Sulfates
Publication Status
Published
Coverage Spatial
United States
Date Publish Online
2022-10-03