- Novel use of state-of-the-art computer models & satellite data sets to examine air quality over a poorly explored region
- Extensive training in data analysis techniques, programming skills, and high performance computing
- Excellent opportunities for international networking
Air-quality in Iranian cities is often much worse than, for example, more publicised air-pollution events in China, yet it has been seldom investigated; only a handful of studies exist for the Persian region.
Furthermore, emissions of pollutants gases, such as nitrogen oxides (NOx = NO2 + NO), within this region are only expected to increase in the future owing to the presence of large industrialised areas, high population densities, inefficient transport networks, and lack of regulatory air-quality controls. The main goal of this project is to use space-borne measurements of atmospheric composition and world-leading state-of-the-art models to improve our understanding of air pollution over the Persian Gulf and surrounding area, and to determine long-term changes in the region’s air-quality.
Specifically, the student will combine a chemical-transport model called GEOS-Chem with more than 10 years of satellite data to (a) determine the controlling mechanisms which influence the observed variability of major tropospheric pollutants (NOx, ozone, carbon monoxide, formaldehyde, particulate aerosol matter);
(b) investigate how sectorial emissions of NOx and volatile organic compounds affect ozone production, and (c) assess how severe dust episodes affect local air-quality. They will also have the exciting opportunity to investigate a wide breadth of additional topics e.g., pollutant ship emissions along sea-lane tracks, detection of changes in air-quality due to regional conflicts, and satellite estimates of biogenic emissions from regions of irrigated desert.
The student will develop a GEOS-Chem high spatial resolution nested-grid simulation for the Persian Gulf domain, to investigate the complex relationships between precursor emissions, atmospheric transport and tropospheric photochemistry, to determine what controls air-quality over this region. The student will integrate the latest regional emission inventories within GEOS-Chem, and then evaluate model performance by comparing simulated trace gas and aerosol distributions against coincident satellite observations from several instruments, including IASI, OMI, MODIS, MISR and GOME-2.
Top-down precursor emission estimates will be inferred from the satellite observations where prior emission data is scarce or particularly poor, to resolve any model discrepancies. Different chemical mechanisms will also be assessed to determine their effectiveness at reproducing key pollutants. The student will then apply time series analysis to over decade’s worth of satellite atmospheric composition measurements to infer recent changes in air-pollution for the major cities and industrial areas within this domain.
Training and Skills
This project offers the candidate an excellent opportunity to work with the latest generation of models, and satellite data, to assess air pollution over the Persian Gulf. The student will study a wide variety of topics covering: (1) chemistry-transport modelling, (2) data visualisation & analysis, including validation of model data using in-situ and satellite observations, and (3) remote sensing techniques and interpretation of retrieved quantities. The student will work with existing computer models and add to them under supervised guidance. The student will learn FORTRAN, IDL and shell-scripting computer languages, and gain experience of high performance computing within a Linux environment.
CENTA students are required to complete 45 days training throughout their PhD including a 10 day placement. In the first year, students will be trained as a single cohort on environmental science, research methods and core skills. Throughout the PhD, training will progress from core skills sets to master classes specific to the student's projects and themes.
Year 1: Extensive training in the use of GEOS-Chem. Development of the GEOS-Chem nested-grid Persian Gulf simulation, including the integration of new emission inventories and assessment of chemical mechanisms.
Year 2: Detailed analysis of satellite observations of tropospheric composition and air-quality trend detection. Case studies of severe pollution episodes.
Year 3: Application of the new GEOS-Chem simulation to investigate air-quality issues and pollutant emissions over the Persian Gulf region (student can & will influence topic choice).
Partners and collaboration (including CASE)
Dr Michael Barkley is Lecturer in Climate Change Adaptation and a past NERC Fellow. His expertise is in investigating mapping reactive carbon emissions from space using a combination of models and multiple satellite data sets. He has over a decade’s experience of retrieving and interpreting satellite observations of tropospheric chemistry, and a strong background in chemistry-transport modelling.
The GEOS-Chem model is hosted by the Atmospheric Modelling Group based at Harvard University (Boston,USA). The student will be expected to work closely with the GEOS-Chem support team in the development of the nested-grid simulation. Student attendance at the international bi-annual GEOS-Chem workshop, held at Harvard University, will be mandatory and offers an excellent opportunity for networking. The student will also develop close links with the international satellite retrieval teams.
Interested applicants are strongly advised to contact Dr Michael Barkley (email@example.com) before applying.