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Using satellite measurements to improve Indonesian peatland fire emissions of trace gases and particulates (part of the SENSE Centre for Doctoral Training)

  • Full or part time
  • Application Deadline
    Sunday, January 19, 2020
  • Competition Funded PhD Project (UK Students Only)
    Competition Funded PhD Project (UK Students Only)

Project Description

Indonesia contains large areas of carbon-rich peatland that have been drained and cleared of natural vegetation, making them susceptible to burning. Each year, thousands of fires burn across Indonesia’s peatlands resulting in substantial emissions of carbon dioxide (CO2) and other pollutants to the atmosphere. Indonesia’s peatland fires emit up to 700-800 Tg of CO2 per year, more than double UK’s annual CO2 emissions. Aerosol and trace gas emissions from these fires cause serious air pollution resulting in the premature death of 10,000s of people each year.

Current estimates of peatland fire emissions have large uncertainties. This is partly because these fires can burn deep down into carbon-rich organic soils. The depth of this combustion depends on soil moisture and water table depth, which vary in time and space and are poorly constrained by in-situ measurements. Accurate information about peatland fire emissions are needed to inform Indonesia’s national climate plans. Efforts to reduce peat fires through restoring peatlands require detailed understanding of how rewetting peat soils alters fire risk.

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
Project aim and Objectives

This PhD project will combine a range of satellite remote sensing datasets to provide improved understanding of Indonesian peat fires and updated estimates of emissions.

The project will contain the following components:

1) Soil moisture EO data. The project will explore a range of EO soil moisture datasets including ESA CCI and NASA SMAP datasets. Building on the work of Kiely et al. (2019), the project will explore how spatial and temporal variability in soil moisture can impact frequency of fire and peat burn depth.

2) Fire emissions. New understanding from (1) will be used to update peat fire emissions based on the FINN emissions dataset.

3) Air pollutant concentrations. An atmospheric model will be combined with new emissions from (2) to create new estimates of the concentrations of pollutants from Indonesian fires.

4) Aerosol and trace gas EO data. New data of carbon monoxide, nitrogen dioxide and aerosol optical depth from Sentinel-5P will be used to evaluate simulated air pollutant concentrations and as an independent constraint on new emissions.

5) Fire emissions and land-use. Datasets of land-cover and land-cover change will be used to explore how fire emissions depend on land-cover.

Improved understanding of peatland fires will help inform ongoing efforts to reduce fire.

Funding Notes

This 3 year 9 month long NERC EO CDT award will provide tuition fees (£4,500 for 2019/20), tax-free stipend at the UK research council rate (£15,009 for 2019/20), and a research training and support grant to support national and international conference travel.

References

Kiely, L., Spracklen, D. V., Wiedinmyer, C., Conibear, L., Reddington, C. L., Archer-Nicholls, S., Lowe, D., Arnold, S. R., Knote, C., Khan, M. F., Latif, M. T., Kuwata, M., Budisulistiorini, S. H., and Syaufina, L.: New estimate of particulate emissions from Indonesian peat fires in 2015, Atmos. Chem. Phys., 19, 11105–11121, https://doi.org/10.5194/acp-19-11105-2019, 2019.

How good is research at University of Leeds in Earth Systems and Environmental Sciences?

FTE Category A staff submitted: 79.20

Research output data provided by the Research Excellence Framework (REF)

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