Assessing Air Quality Co-Benefits of Decarbonising Energy in the UK

Project ID: 2228cd1252 (You will need this ID for your application)

Research Theme: Energy and Decarbonisation

UCL Lead department: Bartlett School of Sustainable Construction

Project Summary:

The decarbonisation of the energy system is of paramount importance to the UK delivery of our commitment to reach net zero by 2050. The broader advantages of decarbonization are often overlooked when assessing the cost-effectiveness of energy technologies. Whilst the primary goal of decarbonisation is to mitigate climate change, it offers a multitude of additional benefits that deserve consideration, particularly in improving air quality by reducing emissions from fossil fuel combustion.

This project aims to develop a comprehensive hybrid model to assess air quality co-benefits associated with the shift toward net-zero energy in the UK. Specifically, the project objectives encompass:

1) Predicting energy demand in the UK up to the year 2050, under the Shared Socioeconomic Pathways (SSPs) which are adopted by the Intergovernmental Panel on Climate Change (IPCC); 2) Estimating the reduction in fossil fuel consumption during net zero energy transitions, by comparing the Business as Usual (BAU) and a series of decarbonisation scenarios which outline different energy technology roadmap options; 3) Assessing the impacts on air quality of energy decarbonization, employing the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) which is an open-source air quality model.

The student will be based at The Bartlett School of Sustainable Construction, supervised by Prof. D’Maris Coffman and Prof. Zhifu Mi. There is an opportunity to collaborate with a team specializing in air quality modelling at Peking University.

We are looking for a highly capable candidate with a master’s degree in built environment, energy engineering, environmental sciences, mathematics, or other relevant disciplines. The candidate needs to be familiar with at least one programming software package, such as MATLAB, R and Python. It would also be useful (but not essential) for the candidate to have some expertise in any of the followings: energy system modelling, scenario analysis, or air quality model.