Project highlights

  • Produce long-term global datasets of short-lived pollutants and precursors that will be used throughout the atmospheric modelling community
  • Develop fast and accurate retrieval schemes of short-lived pollutants and precursors
  • Compare the accuracy of fast schemes with more traditional retrieval approaches

Overview

Climate change and air quality are the most pressing environmental issues of our lifetime, and they are inextricably linked.

Nitrogen oxides (primarily produced through combustion processes) and volatile organic compounds are precursors of tropospheric ozone, a strong greenhouse gas and one of the largest components of the radiative forcing of climate (after carbon dioxide and methane). They are also precursors of secondary aerosols, also known as particulate matter, the most harmful form of air pollution, particularly if smaller than 2.5 micron in diameter (PM2.5) and are able to penetrate deep into the lungs, blood streams and brain, leading to ill health and premature death.  These aerosols are reflective, scattering solar radiation back to space, and tend to have a cooling effect on climate.  Therefore, efforts to improve air quality will likely lead to further increases in temperature.  On the other hand, these temperature increases will lead to changes in the chemistry associated with tropospheric ozone formation.  Increases in temperature will also lead to an increase in the VOCs emitted from vegetation, providing more ozone and PM2.5 precursor.

A number of atmospheric sounders, with low radiometric noise and high spectral resolution, measure upwelling radiances in the thermal infrared spectral region; from these measurements we can determine the concentrations of many short-lived pollutants and precursors, e.g. ammonia, largely arising from agricultural sources (primarily ammonia-based fertilizers and animal manure), which significantly contributes to the formation of PM2.5; isoprene, the dominant biogenic volatile organic compound emitted by vegetation, which is chemically reactive and leads to the production of tropospheric ozone and secondary aerosols; as well as a wealth of pollutants produced from fires, such as methanol, formic acid, peroxyacetyl nitrate, ethene, and ethyne.

We live in an age when satellite-based measurements of atmospheric composition are becoming more and more ubiquitous.  The ever increasing amounts of data available, which are only going to increase in the future, will require smarter and faster computational methods to extract meaningful information from these observations.  Traditional retrieval methods based on line-by-line radiative transfer models are slow but accurate.  The challenge is to maintain this accuracy whilst significantly improving the speed.

CENTA Flagship

This is a CENTA Flagship Project

Host

National Centre for Earth Observation

Theme

  • Climate and Environmental Sustainability

Supervisors

Project investigator

  • Dr Jeremy Harrison (National Centre for Earth Observation and University of Leicester)

 

Co-investigators

  • Prof John Remedios (NCEO and University of Leicester)
  • Dr Stephan Havemann (UK Met Office, Exeter)

How to apply

Methodology

There are currently three IASI (Infrared Atmospheric Sounding Interferometer) instruments in orbit, on MetOp-A (launched 2006), MetOp-B (2012), and MetOp-C (2018), with IASI-NG (New Generation) on MetOp-SG-A due for launch in 2021; the latter possesses improved signal-to-noise and spectral resolution.  There are two CrIS (Cross-track Infrared Sounder) instruments on Suomi-NPP (launched 2011), and NOAA-20 (2017), with a third planned on JPSS-2 (expected launch in 2022).

The student will first perform benchmark retrievals for a number of short-lived pollutants and precursors from IASI and CrIS measurements using an existing retrieval code, the University of Leicester IASI Retrieval Scheme (ULIRS), which has a proven credibility in retrieving trace gas abundances from IASI spectra and uses a line-by-line radiative transfer model known as the RFM.  The student will need to adapt this code for application to CrIS measurements.

The student will then implement a number of fast techniques and compare these against the benchmark results established initially.  These techniques include fast radiative transfer models such as the Havemann-Taylor Fast Radiative Transfer Code (HT-FRTC); linear retrieval methods involving the calculation of hyperspectral range indices; and machine learning techniques such as artificial neural networks.

 

Training and skills

This studentship provides an exciting opportunity to work with cutting-edge satellite observations and atmospheric radiative transfer techniques in a challenging area of atmospheric science.  This project covers a range of topics: atmospheric spectroscopy; remote sensing; retrieval techniques; atmospheric chemistry; data visualisation & analysis.  The National Centre for Earth Observation (NCEO) will provide additional training opportunities via its researchers’ forum and regular conferences/workshops, and enable the student to interact with scientists working in Earth Observation on a national level.  There will also be the opportunity to attend and present at international conferences.

Partners and collaboration

This project has been co-developed and will be jointly supervised by scientists from the National Centre for Earth Observation (NCEO) based at the University of Leicester, and the Met Office, one of CENTA’s Level-1 end-user partners. The NCEO is a distributed NERC research centre providing the UK with national capability in EO science. The student will work closely with the Met Office to apply and develop fast retrieval schemes using IASI and CrIS data.

 

Further details

Dr Jeremy Harrison is the NCEO’s spectroscopy leader and capability leader in atmospheric radiative transfer.  Based in the Earth Observation Science (EOS) group at the University of Leicester, his expertise lies in atmospheric spectroscopy, atmospheric radiative transfer, and the remote sensing of trace gases.

Prof John Remedios is the Director of the NCEO, and an expert in the remote sensing of trace gases.

Dr Stephan Havemann is an observation based research scientist at the Met Office, specialising in the development of fast radiative transfer and variational retrieval codes.

Interested applicants are invited to contact Dr Jeremy Harrison (jh592@leicester.ac.uk). Note that all potential applicants are strongly advised to make contact before applying.

https://www2.le.ac.uk/departments/physics/people/jeremyharrison/jeremyharrison


Please visit the University of Leicester website for application guidance:

https://le.ac.uk/study/research-degrees/funded-opportunities/centa-phd-studentships

 

This is a CENTA Flagship Project

These have been selected because the project meets specific characteristics such as CASE support, collaboration with our CENTA high-level end-users, diversity of the supervisory team, career development of the supervisory team, collaboration with one of our Research Centre Partners (BGS, CEH, NCEO, NCAS) or student co-designed project. These characteristics are a CENTA priority. Studentships associated with Flagship projects will be provided exactly the same level of support as all other studentships.

 

Possible timeline

Year 1

Adapt ULIRS software to handle CrIS data.  Perform benchmark retrievals of short-lived pollutants and precursors from CrIS and IASI radiance spectra using ULIRS.  Validate ULIRS retrievals against in situ and aircraft measurements where appropriate.

Year 2

Perform retrievals using alternative fast schemes, incorporating for example the Havemann-Taylor Fast Radiative Transfer Code (HT-FRTC), linear retrieval methods, and machine learning techniques.

Year 3

Perform detailed comparisons of fast retrieval outputs against benchmark results.  Investigate reasons for any differences, and tweak fast schemes if necessary.  Draw conclusions on the suitability of the various fast schemes to perform accurate retrievals of short-lived pollutants and precursors from CrIS and IASI radiance spectra, as well as determine their strengths and weaknesses.

Further reading

Clarisse, L., Clerbaux, C., Dentener, F. et al. Global ammonia distribution derived from infrared satellite observations. Nature Geosci 2, 479–483 (2009). https://doi.org/10.1038/ngeo551

Clarisse, L., et al. Thermal infrared nadir observations of 24 atmospheric gases. Geophys. Res. Lett. 38, L10802 (2011). https://doi.org/10.1029/2011GL047271

Clarisse, L., Van Damme, M., Gardner, W. et al. Atmospheric ammonia (NH3) emanations from Lake Natron’s saline mudflats. Sci Rep 9, 4441 (2019). https://doi.org/10.1038/s41598-019-39935-3

Dudhia, A. The Reference Forward Model (RFM). J. Quant. Spect. Rad. Trans. 186, 243-253 (2017). https://doi.org/10.1016/j.jqsrt.2016.06.018

Fu, D., Millet, D.B., Wells, K.C. et al. Direct retrieval of isoprene from satellite-based infrared measurements. Nat Commun 10, 3811 (2019). https://doi.org/10.1038/s41467-019-11835-0

Havemann, S., Thelen, J.-C., Taylor, J.P., Harlow, R.C. The Havemann-Taylor Fast Radiative Transfer Code (HT-FRTC): A multipurpose code based on principal components. J. Quant. Spect. Rad. Trans. 220, 180-192 (2018). https://doi.org/10.1016/j.jqsrt.2018.09.008

Illingworth, S. M., et al. ULIRS, an optimal estimation retrieval scheme for carbon monoxide using IASI spectral radiances: sensitivity analysis, error budget and simulations.  Atmos. Meas. Tech. 4, 269-288 (2011). https://doi.org/10.5194/amt-4- 269-2011

Van Damme, M., Clarisse, L., Whitburn, S. et al. Industrial and agricultural ammonia point sources exposed. Nature 564, 99–103 (2018). https://doi.org/10.1038/s41586-018-0747-1

Wells, K.C., Millet, D.B., Payne, V.H. et al. Satellite isoprene retrievals constrain emissions and atmospheric oxidation. Nature 585, 225–233 (2020). https://doi.org/10.1038/s41586-020-2664-3

COVID-19

This project is predominantly computer-based, and can be performed either in an office environment or remotely at home if necessary.  If working at home due to covid-19 restrictions, an internet connection is required in order to access university and NERC computing facilities, software and EO data.  Meetings with the supervisory team will be held safely and physically distanced, where permissible, or using online videoconferencing software.