Atmospheric Composition and Radiative forcing changes due to UN International Ship Emissions regulations (ACRUISE)

Lead Research Organisation: University of Oxford
Department Name: Oxford Physics

Abstract

Ships generally burn low quality fuel and emit large quantities of sulfur dioxide and particulates, or aerosols (harmful at high concentrations), into the atmosphere above the ocean. In the presence of clouds the sulfur dioxide is rapidly converted into more particle mass growing them to sizes where they act as sites for cloud droplet formation. Given that about 70% of shipping activities occur within 400 km of the coast, ships are a large source of air pollution in coastal regions, causing 400k premature mortalities per year globally. In the UK, air pollution (including ship emissions) is responsible for 40,000 premature mortalities each year. In an effort to reduce air pollution from shipping activity, the United Nation's International Maritime Organization (IMO) is introducing new regulations from January 2020 that will require ships in international waters to reduce their maximum sulfur emissions from 3.5% by mass of fuel to 0.5%.

Particulates emitted by ships may enhance the number of cloud droplets and potentially form regions of brighter clouds known as ship tracks. Largely because of this effect, some global models predict that ship emissions of particulates currently have a significant cooling influence on the global climate, masking a fraction of the warming caused by greenhouse gas emissions. So whilst a reduction in ship sulfur emission is predicted to almost halve the number of premature deaths globally via a reduction in sulfate aerosols, a lack of similar reductions in greenhouse gases from shipping (e.g. CO2) could lead to an overall climate warming. However, the magnitude of the cooling caused by particulates is very uncertain, with large discrepancies between global model and satellite-based estimates. This may be due to imprecise representations of the effects of aerosols on clouds in global models or biases in satellite detections of ship tracks. Furthermore, how shipping companies respond to the 2020 regulation (i.e. degree and method of compliance), in international waters where surveillance is challenging, is largely unknown and requires observational verification.

We will take advantage of this unique and drastic "inverse geoengineering" event in 2020. By combining aircraft observations, long-term surface observations, satellite remote sensing, and process-level modelling, we will investigate the impact of the 2020 ship sulfur emission regulation on atmospheric composition, radiative forcing and climate in the North Atlantic. Results of this project will improve our understanding of the impact of ship emissions on air quality and climate.

Planned Impact

To reduce ship-derived air pollution in coastal regions, International Maritime Organisation (IMO) regulations require ships to reduce their sulfur emissions from a maximum of 3.5% to 0.5% in 2020. However, whilst a reduction in sulfur would help to improve air quality, a lack of similar reductions in greenhouse gases from shipping could lead to an overall, but highly uncertain, climate warming effect. We will take advantage of this unique "inverse geoengineering" event in 2020, by combining in situ observations, remote sensing, and process-level modelling to investigate the impact of the 2020 ship sulfur emission regulation on atmospheric composition and radiative forcing in the North Atlantic. Below, we describe a number of key beneficiaries of our proposed work:

General Public, Environmental Authorities, and Health Agencies:
Air pollution comes with huge health and financial costs. For example, particulate air pollution in the UK is estimated to reduce life expectancy by 6 months, with a cost to the national economy of £16 billion/year (DEFRA, 2015). Our project will increase the understanding of the impact of changing ship emissions on coastal air quality, contributing towards more accurate air quality forecasts in populated coastal regions, and allowing environmental authorities to mitigate and prepare, both practically and economically. This could have direct positive impacts on the health of the wider public, e.g. by providing early warnings to the public for periods of dangerously high air pollution that may be harmful to health. Health agencies will benefit from the potential cost savings associated with improvements to the health of the affected populations. Such benefits are likely to be felt soon after completion of the project (2 - 5 years), and will continue into the future.

Policymakers/advisors:
Our work will directly benefit the IMO, the regulatory body responsible for ship emissions. Our proposed observations will provide valuable information on the percentage and spatial distributions of ships' compliance to the 2020 regulation over the open ocean, which is otherwise difficult to police. We will be able to start providing such information to the IMO soon after the 2020 regulation comes into force.
By increasing our understanding of the role of ship emissions on UK coastal air quality, this research will benefit key government advisory bodies, such as the Department for Environment, Food and Rural Affairs (DEFRA), and influence government policy via the Climate Change and Waste & Air Quality Directorates. The 2020 IMO regulation only deals with sulfur emissions, and thus emissions of other air pollutants (e.g. nitrogen oxides, ozone-precursors) may be 'business as usual'. We will also monitor these pollutants in ship plumes, and by communicating our findings to key policymakers (see Pathways to Impact), our work may influence government policy with regards to ship emissions in populated coastal areas within 3 - 5 years of the project end.

Scientific Bodies/Users:
Besides the effects on air quality, aerosols from ship emissions may cause a cooling of the Earth's climate through their interactions with clouds. Our project will benefit global climate bodies such as the UN Intergovernmental Panel on Climate Change (IPCC), by improving understanding of the climate sensitivity to ship emissions - vital if we are to meet the requirements of the UNFCCC COP21 agreement of limiting the global temperature rise this century to < 2 degC above pre-industrial levels. Academic beneficiaries include those working in fields of atmosphere, ocean, and Earth-system science. For example, the UK Earth System Model (NERC/Met Office collaboration) couples atmosphere/ocean processes to provide predictions of Earth's future climate. Our results will provide important constraints on the magnitude of the aerosol indirect effect in this model, contributing towards more accurate predictions of the future climate.

Publications

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Harder P (2022) Physics-informed learning of aerosol microphysics in Environmental Data Science

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Christensen MW (2022) Opportunistic experiments to constrain aerosol effective radiative forcing. in Atmospheric chemistry and physics

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Watson-Parris D (2022) ClimateBench v1.0: A Benchmark for Data-Driven Climate Projections in Journal of Advances in Modeling Earth Systems

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Watson-Parris D (2022) Shipping regulations lead to large reduction in cloud perturbations. in Proceedings of the National Academy of Sciences of the United States of America

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Manshausen P (2023) Rapid saturation of cloud water adjustments to shipping emissions in Atmospheric Chemistry and Physics

 
Description During the ACRUISE field campaign we utilised the newly developed airmass trajectory and dispersion plume HYSPLIT modelling framework to provide waypoints for the FAAM aircraft to sample the plumes of several dozen ships. The model accurately predicted the locations of the plume (as confirmed by the onboard measurements of NOx emissions) and is currently being used to quantify the cloud property changes associated with aerosol plumes from a variety of stationary sites (volcanic and industrial aerosol sources).

Concurrently, we have developed a database of ship tracks detected from machine learning tools to quantify changes in ship track frequencies, lengths and reflectances. We have found more than 5 million tracks over the 20 year period of the MODIS mission and found clear evidence of a reduction in cloud perturbations due to the new IMO regulations, as well as impacts due to the global COVID-19 pandemic.

By linking these findings with high resolution ship emissions data we are able to calculate global estimates of cloud sensitivities to these emissions under varying environmental conditions. Not all these perturbations manifest as tracks however and by extending the above HYSPLIT methodology to the whole Atlantic Ocean we have found evidence of significant changes in cloud liquid water path due to shipping which has not been demonstrated before. These 'invisible' shiptracks could constitute a considerable aerosol forcing that had hitherto remained hidden.
Exploitation Route The measurements of shipping pollution could be of high relevance for users in the air pollution sector.

We will make our database of shiptracks in clouds available for other climate researchers.
Sectors Environment

Transport

 
Title ClimateBench benchmark suite 
Description Benchmark suite for climate model emulation 
Type Of Material Data analysis technique 
Year Produced 2022 
Provided To Others? Yes  
Impact Will allow for full emulation of climate model intercomparison output in support of political decision making. 
URL https://github.com/duncanwp/ClimateBench
 
Title ClimateBench benchmarking dataset 
Description ClimateBench benchmarking dataset 
Type Of Material Database/Collection of data 
Year Produced 2022 
Provided To Others? Yes  
Impact Benchmarking data for ClimateBench climate model emulation framework. 
URL https://doi.org/10.5281/zenodo.5196512
 
Title Dataset of invisible ship tracks 
Description Dataset of invisible ship tracks 
Type Of Material Database/Collection of data 
Year Produced 2022 
Provided To Others? Yes  
Impact scientific research 
URL https://www.nature.com/articles/s41586-022-05122-0#data-availability
 
Title Ship track detection using machine learning and plume modelling 
Description Clouds polluted by oceangoing vessels appear as quasi-linear features when viewed from satellite imagery. We have developed, and are testing, a novel machine learning algorithm based on a convolutional neural network to identify ship tracks from satellite near infrared imagery. The training dataset for this algorithm is based on the hand-logged ship tracks from Christensen and Stephens (2012), doi:10.1029/2011JD017125. The database will provide insight into the changes in ship track frequency, length and reflectance associated with the new regulations on shipping emissions from the International Maritime Organisation. We have also applied the National Oceanic and Atmospheric Administration (NOAA) Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model to point-source pollution sources including ship stacks, volcanos and industrial power plants to quantify the impact of sulphur dioxide concentrations on changes in cloud radiative, microphysical and microphysical clouds. 
Type Of Material Computer model/algorithm 
Year Produced 2020 
Provided To Others? No  
Impact The United Kingdom Chemistry and Aerosols (UKCA) multi-scale unified atmosphere research model is being used to quantify the impact of the IMO on climate change. This newly generated database will be used to constrain and elucidate process-scale interactions in the model for better prediction of climate change and overall model performance of aerosol-cloud interactions. 
 
Title Shiptrack detection data 
Description Shiptrack detection data 
Type Of Material Database/Collection of data 
Year Produced 2022 
Provided To Others? Yes  
Impact scientific use 
URL https://www.pnas.org/doi/10.1073/pnas.2206885119#data-availability
 
Description Aerosol Clouds Precipitation Climate initiative 
Organisation Global Energy and Water Exchanges Project
Country United States 
Sector Charity/Non Profit 
PI Contribution I am on the steering committee of the international Aerosol Clouds Precipitation Climate initiative sponsored by iLeaps, GEWEX and IGAC.
Collaborator Contribution I am on the steering committee of the international Aerosol Clouds Precipitation Climate initiative sponsored by iLeaps, GEWEX and IGAC.
Impact Workshops and two intercomparison studies.
Start Year 2016
 
Title Machine learning tools for detection and segmentation of features in satellite data 
Description Machine learning tools for detection and segmentation of features in satellite data 
Type Of Technology Software 
Year Produced 2021 
Open Source License? Yes  
Impact Ability to search entire satellite record for cloud features. 
 
Description Invited seminar 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach Regional
Primary Audience Postgraduate students
Results and Impact Invisible Ship Tracks: What can we learn about the aerosol effect on clouds and climate from previously unseen ship-polluted clouds?
Centre for Atmospheric Sciences, Cambridge, UK, invited talk
Year(s) Of Engagement Activity 2022