- Satellite data can fill gaps in knowledge for areas of the world with no ozone monitoring.
- Ozone concentration data from satellites can be used to estimate crop yield loss.
- Results can be used to improve global risk assessment for ozone pollution.
Tropospheric ozone is a greenhouse gas, contributing to climate change. This pollutant is harmful to human and plant health and can have numerous negative impacts within an ecosystem, including effects on plant growth, carbon sequestration and cycling of soil nutrients. Studies show global ozone-induced annual yield losses for crops including soybean (12%), wheat (7%), and rice (6%). Current levels of ozone in the Northern hemisphere are also estimated to reduce total tree biomass by 7%.
While the concentration of ozone is decreasing or levelling out in the USA and Europe, levels continue to rise in developing regions. There are also many areas of the world where ozone concentration data are scarce or difficult to collect. It is important to fill these data gaps, as there could be large impacts of high ozone on global climate and food security.
Recent studies have estimated global crop yield loss using modelled ozone data. However, current models use input data primarily focused on Europe/North America. The use of satellite data allows the impact of ozone to be investigated with a much greater spatiotemporal coverage compared to existing estimates.
Satellite measurements of tropospheric ozone and climate variables could be combined to calculate ozone flux, a measure of ozone uptake by the plant. Using response functions, these data could then be used to estimate ozone-induced yield loss. In addition, satellite measurements of vegetation indices such as NDVI (Normalized Difference Vegetation Index) could be used to provide important information on phenology and where crops are growing, which is needed for estimating ozone impacts on a large scale.
Key questions addressed by this PhD will include i) ‘Can satellite data be used to improve estimates of crop losses in regions that do not have ground-based ozone data?’, ii) ‘Can satellite data of crop phenology improve estimates of timings of key growth stages?’, iii) ‘Which parameters are most influential when using satellite data to predict ozone impacts on vegetation?’ Project results will be used to improve global risk assessment of ozone pollution, contributing to the evidence base used by policy makers to set future emissions targets.
Figure 1: Global percentage yield loss estimates for wheat due to ozone impact, annual average for the period 2010-2012. (Mills et al., 2018)
This is a CENTA Flagship Project
HostUK Centre for Ecology & Hydrology
- Climate and Environmental Sustainability
- Organisms and Ecosystems
Satellite datasets (including ozone concentration, climate variables, vegetation indices) will be collated, for example from Sentinel-3. Supplementary spatial datasets will be sourced using GIS. Data validation using observed ozone concentrations will be used to select the final datasets.
Programming (e.g. using Python) will be used to calculate stomatal conductance, ozone metrics and crop yield loss, following methodology from the Convention on Long-range Transboundary Air Pollution (CLRTAP). Physiological parameters for crops will be derived from existing data from UKCEH. Yield loss estimates will be compared with those from modelled and experimental data. Error analysis will provide uncertainty for estimates from satellite datasets.
Vegetation indices (e.g. NDVI) will be used to investigate the timing of crop growth for a study region. Results will be compared with in situ ground measurements. Sensitivity analysis, including testing parameters of the stomatal conductance model, will be done to determine the effect on estimates of ozone impact.
Training and skills
Students will be awarded CENTA2 Training Credits (CTCs) for participation in CENTA2-provided and ‘free choice’ external training. One CTC equates to 1⁄2 day session and students must accrue 100 CTCs across the three years of their PhD.
Training and skills will be developed via formal courses, one-to-one training and mentoring. An initial training needs assessment will be followed by annual reviews of requirements. Specific techniques will be acquired through hands-on training at UKCEH Bangor and the University of Leicester. This training will include processing of remote sensing data, data quality control and assurance, code documentation and version control, GIS mapping and ozone risk assessment. The student will visit the University of Leicester annually and work alongside students in the Department of Physics and Astronomy. The student will present their results at a variety of meetings and conferences.
Partners and collaboration
The project will develop new partnerships between UKCEH and the University of Leicester, combining more than twenty years of research on ozone impacts on vegetation and extensive experience in working with remote sensing observations.
Dr Jasdeep S Anand is a member of the National Centre for Earth Observation (NCEO). Dr Katrina Sharps and Dr Felicity Hayes coordinate the ICP Vegetation, an international research programme investigating the impacts of air pollutants on vegetation. The programme has extensive links to participants from around the world who are involved in ozone risk assessment and could further advise the student as needed.
For further information, please contact:
Dr Katrina Sharps ([email protected])
UK Centre for Ecology & Hydrology
Environment Centre Wales
If you wish to apply to the project, applications should include:
- A CENTA application form, downloadable from: CENTA application
- A CV with the names of at least two referees (preferably three and who can comment on your academic abilities)
- Submit your application and complete the host institution application process via:: https://le.ac.uk/study/research-degrees/funded-opportunities/centa-phd-studentships Please quote CENTA2-CEH-SHAR when completing the application form.
Applications to be received by the end of the day on Wednesday 11th January 2023.
An initial research plan will be prepared with the supervisory team. A literature review will then be done, forming the introductory chapter of the thesis. Satellite data and spatial datasets will be collated, and data validation will be carried out. Python code will be used to calculate ozone metrics (AOT40 and ozone flux) and stomatal conductance from the satellite data.
Crop yield losses will be estimated from the satellite data, and an error analysis will be done to provide a defined uncertainty for the estimates. Outputs will then be compared with results from modelled data and air filtration experiments. Satellite data on vegetation indices will be used to estimate growing season timings.
Growing season estimates will be compared with data from the ground. Sensitivity analysis will be carried out, e.g. by varying input parameters, to investigate the effect on the estimates of ozone impact.
- Duncan, J.M., Dash, J. & Atkinson, P.M. (2015) The potential of satellite-observed crop phenology to enhance yield gap assessments in smallholder landscapes. Frontiers in Environmental Science, 3, 56. https://doi.org/10.3389/fenvs.2015.00056
- Fishman, J., Creilson, J.K., Parker, P.A., Ainsworth, E.A., Vining, G.G., Szarka, J., Booker, F.L. & Xu, X. (2010) An investigation of widespread ozone damage to the soybean crop in the upper Midwest determined from ground-based and satellite measurements. Atmospheric Environment, 44, 2248–2256. https://doi.org/10.1016/j.atmosenv.2010.01.015
- Mills, G., Sharps, K., Simpson, D., Pleijel, H., Broberg, M., Uddling, J., Jaramillo, F., Davies, W.J., Dentener, F., Van den Berg, M. & Agrawal, M. (2018) Ozone pollution will compromise efforts to increase global wheat production. Global Change Biology, 24(8), 3560-3574. https://doi.org/10.1111/gcb.14157
- Reed, B.C., Brown, J.F., VanderZee, D., Loveland, T.R., Merchant, J.W. & Ohlen, D.O. (1994) Measuring phenological variability from satellite imagery. Journal of Vegetation Science, 5(5), 703-714. https://doi.org/10.2307/3235884
- CLRTAP (2017). Chapter 3 “Mapping critical levels for vegetation”. LRTAP convention modelling and mapping manual. https://icpvegetation.ceh.ac.uk/sites/default/files/FinalnewChapter3v4Oct2017_000.pdf
The office where the student will be based (UKCEH site in Bangor) has a risk assessment in place (which is regularly updated), aiming to ensure the safety of staff and students, and minimise the risk of coming into contact with any respiratory infections.
As all of the work for this PhD will be desk-based, any worsening in severity of the respiratory and contact infection pandemic (e.g. further lockdowns) should not affect project delivery, as the work could be continued from home if necessary, with online access to support from all supervisors.