Crop yield and soil carbon turnover models are parameterized by using data from carefully controlled and measured field and lab experiments and when used spatially in predictive mode are driven by existing spatial data sets of weather, climate, soil types and land use at various scales. While this is adequate at a 1kmx1km spatial scale to provide average values for a country or region, fine scales are needed to predict a crops’ yield and the resulting impact on soil carbon at a farm scale. Farm scale predictions are need to inform investment decisions or whether or not to grow a particular crop in a particular field. This requires model validation using data from actual commercial scale plantings and most likely the inclusion of new factors in the model. A process based model MiscanFor has been developed to predict energy yields, soil carbon turnover and the greenhouse gas emissions from perennial bioenergy crops. These are a giant C4 grass - Miscanthus and Short Rotation Coppice Willow that are being grown at various locations in the UK as a biomass fuel. There are currently around 10,000 ha of Miscanthus and 3000 ha willow planted in the UK. To increase this area requires improved crop varieties and new agronomy to speed up the crop establishment and improve the yields. However, there is a significant knowledge gap around the impacts of these new hybrids and agronomies on the overall greenhouse gas emissions caused during the establishment of these bioenergy crops. Emissions during establishment on both arable and grassland systems will be quantified and used to improve our models which aim to project the overall greenhouse gas removal of perennial biomass crops.
Objective of the PhD:
The object on the PhD project is to quantify the actual greenhouse gas (GHG) removal (GGR) from the atmosphere by growing perennial bioenergy crops and using the harvested biomass in bioenergy carbon capture and storage (BECCS) systems. This will be achieved by gathering new data of crop establishment for novel genotypes and agronomy to understand the drivers for crop establishment under commercial farm conditions and further develop the models for use in the field environment. The project will involve gathering data about yields, agronomy used, soil conditions, GHG exchange, microclimate and the hydrology of commercial Miscanthus and willow crops and their position in the landscape from two contrasting sites in the UK. This will involve a mix of field, lab and desk work. The MiscanFor and Ecosse models will be the platforms used to develop a tool that can be used by farmers and land owners to optimize GGR.
Training in all aspects of the bioenergy carbon capture and storage value chain from the seed production, agronomy, harvesting and fuel preparation and use, conducting farm and soil surveys and synthesising the survey data, programming models in FORTRAN, and R and using ARCGIS to analyse spatial data.
Computer programming using a scientific language (eg. C, C++, Python, Fortran, Matlab, R) and or ArcGIS would be helpful but could also be part of the training, as well as a willingness to collect field data on farms producing Miscanthus and willow.
Informal enquiries are encouraged, please contact Professor Astley Hastings (email@example.com) for further information.
- Formal applications can be completed online: https://www.abdn.ac.uk/pgap/login.php
- You should apply for Biological Sciences (PhD) to ensure your application is passed to the correct team.
- Please clearly note the name of the supervisor and project title on the application form. If you do not mention the project title and the supervisor on your application it will not be considered for the studentship.
- Please include a cover letter / Personal Statement specific to the project you are applying for, an up-to-date copy of your academic CV, and relevant educational certificates and transcripts.
- Please note: you DO NOT need to provide a research proposal with this application
- General application enquiries can be made to firstname.lastname@example.org