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Using models and data to understand observed changes in tropospheric ozone (SENSE CDT)


School of Geosciences

About the Project

Tropospheric ozone (TrO3) is an important greenhouse gas which also controls the oxidizing capacity of the global atmosphere. At elevated levels it is detrimental to human health and crops. Despite the importance of TrO3 there remain substantial uncertainties associated with understanding its spatial and temporal variations. In this project, you will investigate the importance of competing physical and chemical drivers that are responsible for observed distributions of TrO3. You will achieve this using a cutting-edge atmospheric chemistry transport model and a variety of ground-based, aircraft and satellite measurements of TrO3.

GEOS-Chem model surface ozone (ppb), July 2018
GEOS-Chem model surface ozone (ppb), July 2018. The World Health Organisation recommends an 8-hour running mean limit of ~50 ppb.
Part of the challenge associated with understanding changes in TrO3 is that it is photochemically produced in the atmosphere from the oxidation of volatile organic compounds in the presence of nitrogen oxides. The balance between these two precursor ingredients, which arise from a variety of natural and anthropogenic sources, can result in a net loss or production of TrO3 within different regions. With a TrO3 atmospheric lifetime of a few weeks, this means that regional changes in these precursor emissions can influence TrO3 on a hemispheric scale via atmospheric transport (e.g. Gaudel et al, 2020).

TrO3 is measured by a range of instruments on the ground, high-altitude balloons, commercial aircraft, and satellites. This project will focus on the global data collected by satellites within the context of the new second international Tropospheric Ozone Assessment Report (TOAR-II). TOAR-I reported a wide variety of trends and variations in TrO3 observed by different satellite sensors (Gaudel et al, 2018) but made little attempt to reconcile differences between a) satellite-based estimates from sensors that view different parts of the atmosphere and b) the satellite-based data and values reported by the ground-based observations. This PhD is an opportunity to address these important knowledge gaps in terms of quantifying changes in TrO3 with well-defined uncertainties.

Project Aims

This PhD project will combine a range of recent satellite observation datasets of TrO3, ground-based and balloon-borne measurements, and interpret them using the state-of-the-art GEOS-Chem atmospheric chemistry transport model (http://acmg.seas.harvard.edu/geos/). This model will act as an intermediary between the different datasets.

The project will address the following aims:

1) Quantify observed trends and variations in TrO3 from different satellite datasets and use the GEOS-Chem model to understand whether these sensors provide a consistent picture.

2) Understand to what extent space-borne sensors are consistent with the sparse TrO3 ground-based and aircraft observation networks.

3) Investigate the impacts of changes in anthropogenic, pyrogenic, and biogenic TrO3 precursor emissions on observed TrO3, including the impact of large-scale climate variations (e.g. El Nino) and the Covid-19 pandemic.

As part of the project you will have the opportunity to participate in a short placement at the Rutherford Appleton Laboratory, where you will work with members of the remote sensing group to develop a better understanding of the satellite remote sensing data products.

Supervisory Team

Paul Palmer and Caroline Nichol are academic staff at the University of Edinburgh. Paul leads a research group focused on interpreting satellite measurements of the global troposphere using computational models and theory (http://www.palmergroup.org/). Caroline, an expert in using tower-based and airborne hyperspectral remote sensing data, leads a group on forest remote sensing (https://www.ed.ac.uk/geosciences/people?person=560). Martyn Chipperfield leads a research group at the University of Leeds and is an expert on modelling tropospheric chemistry and analysis of satellite observations (http://homepages.see.leeds.ac.uk/~lecmc/). Brian Kerridge, an expert in developing satellite data products of tropospheric ozone and other trace species, is based at the Rutherford Appleton Laboratory in Oxfordshire where he leads the remote sensing group (https://www.ralspace.stfc.ac.uk/Pages/Remote-Sensing-Group-Members.aspx).

This PhD is part of the NERC and UK Space Agency funded Centre for Doctoral Training "SENSE": the Centre for Satellite Data in Environmental Science. SENSE will train 50 PhD students to tackle cross-disciplinary environmental problems by applying the latest data science techniques to satellite data. All our students will receive extensive training on satellite data and AI/Machine Learning, as well as attending a field course on drones, and residential courses hosted by the Satellite Applications Catapult (Harwell), and ESA (Rome). All students will experience extensive training on professional skills, including spending 3 months on an industry placement. See http://www.eo-cdt.org

Funding Notes

This 3 year 9 month long NERC SENSE CDT award will provide tuition fees (£4,409 for 2020/21), tax-free stipend at the UK research council rate (£15,285 for 2020/21), and a research training and support grant to support national and international conference travel.

References

Gaudel, A, et al., Tropospheric Ozone Assessment Report: Present-day distribution and trends of tropospheric ozone relevant to climate and global atmospheric chemistry model evaluation, Elem Sci Anth, 2018.

Gaudel, A, et al., Aircraft observations since the 1990s reveal increases of tropospheric ozone at multiple locations across the Northern Hemisphere, Science Advances, 2020.

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