2026-B28 From Smoke to Sustainability: Reducing Wood Burning for Cleaner Air and Healthier Lives

PROJECT HIGHLIGHTS

  • Nationally unique air quality supersite triplets (urban background, rural background and mobile) for observations  
  • Opportunity to learn not only observation, but also machine learning and modelling skills 
  • Evidence directly supporting targeted policy interventions to improve air quality 

Overview

Woodburning has emerged as the single most important source of primary fine particulate matter (PM2.5) in Birmingham and likely many other UK cities. Exposure to PM2.5 from wood stoves contributes to hundreds of premature deaths each year in Birmingham and imposes a significant burden on public health, particularly through non-communicable diseases. It also has far-reaching economic impacts, including lost productivity. 

The popularity of domestic wood stoves is increasing rapidly, with an estimated 150,000–200,000 units sold in 2022 alone. While manufacturers often market these stoves as “clean” and “sustainable,” emissions of PM2.5 are in fact highly dependent on the type of fuel and burning conditions. As emissions from traffic and industry decline, woodburning is expected to become an even larger contributor to the UK’s air pollution problem. 

Despite its growing importance, our understanding of woodburning remains limited. Current knowledge of its spatial and temporal patterns at regional and national scales is poor, and the UK’s national emission inventory carries large uncertainties. This gap hinders effective assessment of the true health and environmental impacts of woodburning. 

This studentship will address these challenges by providing robust scientific evidence on the contribution of woodburning to air quality in the West Midlands and across the UK. The project will: 

  • Use the UK’s nationally unique air quality supersite to conduct long-term observations at both urban background and upwind rural sites, capturing seasonal and temporal variation. 
  • Employ mobile measurements to characterise the spatial distribution of woodburning emissions. 
  • Integrate observations into inversion modelling to refine regional and national emission inventories. 
  • Model the impact of woodburning on UK air quality and human health 
  • Work with regional and local authorities to design and evaluate interventions aimed at reducing emissions. 

The outcomes of this research will deliver critical evidence to inform policy at local, regional, and national levels. By identifying effective strategies to reduce woodburning, the project will directly contribute to improving air quality, protecting public health, and supporting the UK’s transition to a cleaner, healthier future. 

Figure 1: Contribution of different air pollution sources to PM2.5 in Birmingham. Produced from data by Srivastava et al., 2015. This figure shows that biomass burning contributed to a quarter of the PM2.5 mass, becoming the most important primary emitted PM2.5.  

A pie chart showing four sources of pollution: 'Biomass burning' in blue, 'Traffic and dust' in orange, 'Secondary' in gray, and 'Others' in yellow.

This project is a CENTA Flagship Project.

Case funding

This project is suitable for CASE funding

Host

  • University of Birmingham

Theme

  • Climate and Environmental Sustainability

Supervisors

Project investigator

Co-investigators

How to apply

Each host has a slightly different application process.
Find out how to apply for this studentship.

All applications must include the CENTA application form.
Choose your application route

  1. Fixed-site observations: One urban background supersite will be located at University campus, and one at an upwind site. Continuous, online monitoring of a range of air pollutants, including black carbon and other PM2.5 constituents, will be measured (minutes to hourly). 
  2. Mobile observations: A mobile supersite in a dedicated electric van will operate along selected routes to map the spatial distribution of airborne particles, including woodsmoke. 
  3. Receptor modelling and machine learning: Receptor models will quantify temporal and spatial variation of woodsmoke PM2.5. Explainable machine learning will help identify controlling factors, such as meteorological conditions. 
  4. Air quality modelling and health impact assessment: A chemical transport model (e.g. WRF-CMAQ) will simulate woodsmoke contributions using national emission inventories, with inverse modelling to refine and improve emissions data. This will then be used to quantify woodburning health impact and develop mitigation strategies.   

DRs will be awarded CENTA Training Credits (CTCs) for participation in CENTA-provided and ‘free choice’ external training. One CTC can be earned per 3 hours training, and DRs must accrue 100 CTCs across the three and a half years of their PhD.  

  • Training will be provided on operating and maintaining a range of advanced instruments for the air quality supersite. 
  • R programming skills and machine learning will be taught including the use of air pollution data analysis packages such as openair. 
  • Develop a skillset of using a high-performance computer and air quality modelling. 
  • Specific training on literature reading, review and scientific writing, and proposal writing will be provided on a regular basis during weekly supervisory meetings.  

This proposal is developed together with  

  1. Worcestershire County Council: supported WM-Air project; strong support for WM-NetZero project in finding a upwind supersite location; regular contacts in air quality issues including PM source apportionment in order to develop measures to improve air quality 
  2. Birmingham City Council: who worked with us in understanding PM2.5 sources and are keen to work out the woodburning hotspots to enable more targeted behaviour and policy actions 
  3. UKCEH, who has made BC measurements in Scotland, and is keen to expand this to the whole of England 

Year 1: Training in supersite instrument operation, R programming if needed, advanced receptor modelling and machine learning; planning for mobile observations; contributing to supersite observations; carry out mobile observations  

Year 2: Continue supersite observations; learn air quality modelling, prepare emission inventories; analysing existing data and submit first paper 

Year 3: Data analysis and manuscript drafting and submission 

Year 4: Thesis drafting and viva 

  1. Srivastava, D., Saksakulkrai, S., Acton, W.J.F., Rooney, D.J., Hall, J., Hou, S., Wolstencroft, M., Bartington, S., Harrison, R.M., Shi, Z. and Bloss, W.J. (2025) ‘Comparative receptor modelling for the sources of fine particulate matter (PM2.5) at urban sites in the UK’, Atmospheric Environment, 343, p. 120963. doi:10.1016/j.atmosenv.2025.120963. 
  2. Defra Air Quality Expert Group (2017) The potential air quality impacts from biomass combustion. Available at: https://uk-air.defra.gov.uk/assets/documents/reports/cat11/1708081027_170807_AQEG_Biomass_report.pdf (Accessed: 11/09/2025) 
  3. Shi, Z., Song, C., Liu, B., Lu, G., Xu, J., Vu, T.V., Elliot, R.J.R., Li, W., Bloss, W.J. and Harrison, R.M. (2021) ‘Abrupt but smaller than expected changes in surface air quality attributable to COVID-19 lockdowns’, Science Advances, 7(3), p. eabd6696. doi:10.1126/sciadv.abd6696. 
  4. Mazzeo, A., Zhong, J., Hood, C., Smith, S., Stocker, J., Xai, X. and Bloss, W.J. (2022) ‘Modelling the impact of national vs. local emission reduction on PM2.5 in the West Midlands, UK using WRF-CMAQ’, Atmosphere, 13(3), p. 377. doi:10.3390/atmos13030377. 

Further details and How to Apply

For any enquiries related to this project please contact:

Zongbo Shi, School of Geography Earth and Environmental Sciences, University of Birmingham, Birmingham, B15 2TT, United Kingdom, Email: [email protected], Telephone: 01214149128, Webpage:  https://clean-air-research.org.uk/ 

 To apply to this project:  

  • You must include a CV with the names of at least two referees (preferably three) who can comment on your academic abilities.  
  • Please submit your application and complete the host institution application process via: https://sits.bham.ac.uk/lpages/LES068.htm.   Please select the PhD Geography and Environmental Science (CENTA) 2026/27 Apply Now button. The CENTA Studentship Application Form 2026 and CV can be uploaded to the Application Information section of the online form.  Please quote 2026-B28 when completing the application form.  

 Applications must be submitted by 23:59 GMT on Wednesday 7th January 2026.   

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