Improved understanding and mitigation of wintertime air pollution through combining modelling and laboratory measurements
Motivation
Exposure to ambient air pollution is one of the world’s leading health risks, resulting in approximately 4 million premature deaths worldwide each year, and in the UK its health burden is on par with heart disease, cancer, and obesity. Winter months pose particular challenges for air quality. Cold and still weather conditions coincide with enhanced emissions, for example from domestic heating, and trapping of pollution close to the ground under temperature inversions, which inhibit circulation and dispersal of accumulated emissions. Under these conditions, pollution levels can build rapidly to unhealthy levels. In the UK, medical experts have raised strong concerns about the health consequences of winter pollution exposure, especially for children.
In recent years, London has experienced several severe winter pollution episodes when air pollution abundances have reached the highest levels of harmful air quality index, driven by enhanced particulate concentrations. These incidents almost always coincided with cold, calm weather, showing a strong link between atmospheric conditions and accumulated pollution. Wintertime events are also common in other regions of the world with much higher levels of air pollution. For example, the North China Plain region of China has been subject extreme pollution haze episodes during winter, exacerbated by strong emissions and meteorological drivers.
London air pollution in January 2022. Photo: Malcolm Park / Alamy
Addressing the problem of winter air pollution episodes requires a deep understanding of how pollutants behave in the atmosphere as well as their emission sources. This is particularly the case for particulate pollution, which comprises a complex mixture of primary (directly emitted) and secondary (produced in the atmosphere) components of varied chemical composition. An incomplete understanding of atmospheric chemical processes under cold and dark conditions, hinders our knowledge of the balance between primary and secondary sources of PM in polluted winter environments.
Recently, the ALPACA study (https://alpaca.community.uaf.edu/alpaca-field-study/), has shed new light on how pollutants are formed and transformed under cold, dark conditions. However, important gaps remain, particularly in understanding how secondary pollutants are processed when sunlight is scarce, and photochemical oxidation processes that dominate in sunlit environments are largely negated. Filling these gaps is vital for developing effective strategies to protect public health and reduce the harmful effects of winter air pollution. There is increasing evidence that heterogeneous chemical processes (that is processing of gas phase pollutants on the surfaces of aerosol particles) are of key importance for atmospheric oxidants in winter environments, however many specific aspects of this are still uncertain, and information needed to adequately include such processes in model forecasts of wintertime air pollution is lacking. In this PhD project, new laboratory and modelling studies will be combined to address these knowledge gaps.
Aim
The overall aim of this PhD project is to carry out laboratory and model investigations to elucidate new knowledge of heterogeneous production and loss of gas-phase atmospheric species and apply these in regional wintertime pollution studies of the UK and northeast China. The student will engage in both laboratory experiments and regional air quality modelling using the WRF-CMAQ system, with flexibility to tailor the balance of lab and modelling work to their interests.
Key Objectives:
- Laboratory Investigations: Conduct and/or analyse experiments on the uptake and production of reactive nitrogen species and atmospheric radicals on various aerosol types (e.g., from wood burning and traffic) under conditions relevant to wintertime UK and China.
- Model Development: Use lab data to develop parameterisations for improved representation of heterogeneous processes in the WRF-CMAQ model.
- Regional Simulations: Run and analyse WRF-CMAQ simulations to assess the impact of updated heterogeneous chemistry on particulate pollution and NO₂ predictions during extreme winter pollution events in England and the North China Plain.
- Policy Evaluation: Use the enhanced model to evaluate the effectiveness of different pollution mitigation strategies and their health benefits in both regions.
Outcomes and impact
This project will deliver improved model processes for simulating wintertime air pollution, and effectiveness of winter pollution mitigation strategies. The work undertaken by the student will lead to publications in the scientific literature. The work will also contribute to international assessment programmes on Arctic pollutants (the Arctic Monitoring and Assessment Programme of the Arctic Council), ensuring effective dissemination to the wider scientific and policy-facing communities.
Relevant recent publications produced by our supervised PhD students:
Lab data study of radical uptake to aerosol: https://acp.copernicus.org/articles/23/5679/2023/acp-23-5679-2023.pdf
Application of regional CMAQ model to China: https://www.nature.com/articles/s41612-025-01054-4.pdf
Model study of power plant pollution in Fairbanks, Alaska: https://pubs.acs.org/doi/full/10.1021/acsestair.5c00030
Training and Environment
The student will gain interdisciplinary training in:
- Atmospheric modelling and analysis
- Laboratory techniques for studying chemical kinetics
- Interpretation of observational and satellite data
- Numerical modelling and supercomputing
The student will be supported by active atmospheric chemistry and pollution research groups in SEE and in the School of Chemistry. You will benefit from existing cross-campus collaboration between the Schools, and join a large vibrant research team spanning observations, process modelling and Earth System modelling.
Further Reading
ALPACA Overview paper: https://pubs.acs.org/doi/full/10.1021/acsestair.3c00076