- Timely investigation into emerging issues surrounding air pollution composition/exposure, wide spread disease (focusing of COVID-19) and inequalities in society (g. socioeconomic status, ethnicity and access to health and welfare support).
- Application of mixed-methods, systems approach, looking holistically at air pollution and linkages to COVID-19 instance and outcome in society, using direct atmospheric composition measurements with health and demographic data.
- Application of findings for future policy in air quality, climate and health.
This project aims to investigate emerging issues around air pollution and wide spread disease (focusing on COVID-19) and inequalities in society, namely, socioeconomic status, ethnicity and access to health/welfare support.
Research Questions-1: Are members of UK lower income and/or BAME communities exposed to higher levels of air pollution than other demographics; are these citizens being relatively disadvantaged by current UK planning (housing), social welfare and health policies; and how could health and air pollution policies be adjusted to mitigate this?
Research Questions-2: Do linkages exist (in existing data) between air pollution exposure, socioeconomic status, ethnicity and access to health/welfare support, and outcome and severity of COVID-19?
The global pandemic resulted in early recognition of an ethnic disparity in vulnerability to contracting diseases such as COVID-19, and outcome severity . Bio-culturally, this inter-population variation in susceptibility relates to more than biology or genes. Early research suggests that socio-economic factors e.g. employment and housing status may have led to health disparities and resulted in inequalities during the COVID-19 pandemic, and that there may also be linkages with respect to these health inequalities/outcomes and exposure to air pollution, a growing global threat to health with deprived areas of society often suffering from greatest exposure despite contributing least to emissions. This consequential link between socioeconomic deprivation, housing, ethnicity, air pollution exposure and health risks need to be explored to ensure health equality and social justice in society moving forward.
Unfortunately, only early exploratory studies have been conducted on these issues during the COVID-19 pandemic, as such there exists a major research gap in understanding spatio-temporal evolution of air pollution and its impacts linked to health inequalities and ethnic disparity on the backdrop of a major pandemic. This PhD aims to address this research gap using quantitative and qualitative techniques to investigate linkages between key air pollutants, COVID-19 instance and outcome, and socio-economic descriptors (e.g. ethnicity and deprivation) and also to understand the impacts of key policies on low-income and BAME communities, and the structural issues that need to be tackled that often mean such communities get pushed to more vulnerable living areas of society.
This is a CENTA Flagship Project
HostUniversity of Leicester
- Climate and Environmental Sustainability
Mixed-methods, systems approach looking holistically at instances and outcomes of COVID-19 in low-income and/or BAME communities, and linkages to air pollution composition/levels, using direct atmospheric measurements (in-situ and satellite) and complex health and demographic data. Advanced quantitative data analyses will be employed to interrogate NERC, Environment Agency and ESA (Sentinel-5P) air quality, and ONS/HDRUK epidemiological/health and demographic datasets, and relate these to ESRC Understanding Society datasets since 2009 (when ethnicity boost samples were introduced). Analysis[5/6] will employ GIS, chemical/dispersion modelling, satellite data analysis (with partners, Satellite Applications Catapult) and a range of statistical decomposition techniques. Findings will be used to devise key questions for in-depth interviews with senior health/environment policy makers, and focus groups with stakeholders/practitioners to explore perceptions/understanding of relationships between air pollution and health inequalities; knowledge gained will be used to develop a health policy toolkit to increase knowledge on socio-economic health inequalities related to air pollution.
Training and skills
The student will join the Air Quality Group at the University of Leicester (~20 people) and benefit from the group’s extensive expertise in air pollution, data analysis techniques, atmospheric modelling, field work skills and logistics planning. The student will also be part of/be supported by the University of Brighton Centre for Earth Observation Science. Targeted training will be given to conduct the extensive data analysis, including in social science methods. In addition to CENTA training, we offer lecture courses that are directly relevant to the project, e.g. Earth System Science.
Partners and collaboration
The PhD partners with Satellite Applications Catapult , working with the Geospatial Analysis and Health and Wellbeing teams, whose complimentary work looks to enable uptake of satellite data to help in environment and healthcare sectors.
The PhD will work alongside/be part of teams within the National Centre for Earth Observation Science and the U. Brighton Centre for Earth Observation Science and feed into/be supported by their activities (e.g. using NEODAAS remote sensing analysis). The PhD will use air quality data from Environment Agency/NPL and will collaborate with members of their air quality teams.
Potential applicants are welcome to discuss the project informally and obtain further information from the project supervisors:
Prof. Paul Monks ([email protected]) – Department of Chemistry, Univ. of Leicester, Leicester LE1 7RH.
Dr Kevin Wyche ([email protected]) – School of Applied Sciences, Univ. of Brighton, BN2 4GJ.
To apply to this project please visit: https://le.ac.uk/study/research-degrees/funded-opportunities/centa-phd-studentships
Generic CENTA training and training specific to this project. The student will be taught the fundamental principles of a range of advanced atmospheric monitoring equipment, including satellite instruments, and how and what data they acquire. The student will also be taught how to analyse atmospheric data and use key software, including R (OpenAir), SNAP and ENVI (for Sentinel-5P), ArcGIS (for geospatial analysis) and ADMS and Fortran (for modelling). The student will also conduct extensive literature analysis to underpin their project (including policy) and advance their fundamental understanding of the subject area. The student will begin gathering and analysis of georeferenced historic time-series air quality data of target locations (i.e. Leicester, London, Birmingham) and satellite data across the UK, and begin chemical/dispersion modelling. During year 1 the student will apply for Research Ethics approval.
The student will begin gathering and analysis of georeferenced (LSOA) historic socio-economic data (e.g. demographic, ethnicity, deprivation, socioeconomic status, access to health/welfare support) and COVID-19 data (e.g. instance, outcome, death status, date, testing etc). They will conduct an initial ensemble analysis of historic in-situ data, satellite data, socio-economic and public health statistics (including instances of COVID-19) using a range of advanced statistical and geospatial techniques to address the research questions. During year 2, the student will spend time on placement with project partner, Satellite Applications Catapult, working collaboratively on the geospatial analyses. Toward the end of the year, the student will begin designing interviews for health/environment policy makers, and focus groups for stakeholders/practitioners.
During year 3, the student will conclude analysis of historic data. Draw conclusions on linkages between air pollution levels, socio-economic status, ethnicity and impact of COVID-19 in detail in target areas (i.e. Leicester, London, Birmingham) and in general across the wider UK. They will conduct interviews with health/environment policy makers, and focus groups with stakeholders/practitioners and develop a health policy toolkit to increase knowledge of socio-economic health inequalities related to air pollution.
 Monks, P.S. (2020) ‘Coronavirus: lockdown’s effect on air pollution provides rare glimpse of low-carbon future?’ Available at: https://theconversation.com/coronavirus-lockdowns-effect-on-air-pollution-provides-rare-glimpse-of-low-carbon-future-134685.
 Intensive Care National Audit & Research Centre (2020) ‘ICNARC report on COVID-19 in critical care’.
 Brunt, H., Barnes, J., Jones, S.J., Longhurst, J.W.S., Scally, G. and Hayes E. (2017) ‘Air pollution, deprivation and health: Understanding relationships to add value to local air quality management policy and practice in Wales, UK’, Journal of Public Health, 39(3), pp.485-497.
 Williams, M.L., Beevers S., Kitwiroon N., Dajnak D., Walton H., Lott M.C., Pye S., Fecht D., Toledano M.B. and Holland M. (2018) ‘Public health air pollution impacts of pathway options to meet the 2050 UK Climate Change Act target: a modelling study’. NIHR Journals Library, Southampton (UK); 2018. PMID: 29927565.
 Wyche, K.P., Nichols, M., Parfitt, H., Beckett, P., Gregg, D.J., Smallbone, K.L. and Monks, P.S. (2021) ‘Changes in ambient air quality and atmospheric composition and reactivity in the South East of the UK as a result of the COVID-19 lockdown’, Science of the Total Environment, 755, p.142526.
 Jenkins, N., Parfitt, H., Nicholls, M., Beckett, P., Wyche, K., Smallbone, K., Gregg, D. and Smith, M., (2020), ‘Estimation of changes in air pollution emissions, concentrations and exposure during the COVID-19 outbreak in the UK: Report for The Air Quality Expert Group, on behalf of Defra: Analysis of air quality changes experienced in Sussex and Surrey since the COVID-19 outbreak’.
 Wyche, K.P., Monks, P.S., Smallbone, K.L., Hamilton, J.F., Alfarra, M.R., Rickard, A.R., McFiggans, G.B., Jenkin, M.E., Bloss, W.J., Ryan, A.C., Hewitt, C.N. and MacKenzie, A.R. (2015) ‘Mapping gas-phase organic reactivity and concomitant secondary organic aerosol formation: chemometric dimension reduction techniques for the deconvolution of complex atmospheric data sets’, Atmos. Chem. Phys., 15, p. 8077-8100.
The project has a high degree of COVID-19 resilience as it can be executed completely via a remote desk-based scenario. The data required to complete the project has already been acquired by the various data providers (NERC, Environment Agency, EPSRC, ONS/HDRUK) and access has already been granted. Also, access has been granted to the required ONS saferoom by remote VPN. Project meetings and all interviews and focus groups can be conducted remotely via the various available platforms if required.