Preprints
https://doi.org/10.5194/amt-2023-15
https://doi.org/10.5194/amt-2023-15
08 Feb 2023
 | 08 Feb 2023
Status: this preprint is currently under review for the journal AMT.

Long-term airborne measurements of pollutants over the UK, including during the COVID-19 pandemic, to support air quality model development and evaluation

Angela Mynard, Joss Kent, Eleanor R. Smith, Andy Wilson, Kirsty Wivell, Noel Nelson, Matthew Hort, James Bowles, David Tiddeman, Justin M. Langridge, Benjamin Drummond, and Steven J. Abel

Abstract. The ability of regional air quality models to skilfully represent pollutant distributions throughout the atmospheric column is important to enabling their skilful prediction at the surface. This provides a requirement for model evaluation at elevated altitudes, though observation datasets available for this purpose are limited. This is particularly true of those offering sampling over extended time periods. To address this requirement and support evaluation of regional air quality models such as the UK Met Offices Air Quality in the Unified Model (AQUM), a long-term, quality assured, dataset of the three-dimensional distribution of key pollutants has been collected over the southern United Kingdom from June 2019 to April 2022. This sampling period encompasses operations during the global COVID-19 pandemic, and as such the dataset serves an additional application in providing a unique resource with which to explore changes in atmospheric composition associated with reduced emissions during this period. Measurements were collected using the Met Office Atmospheric Survey Aircraft (MOASA), a Cessna-421 instrumented for this project to measure gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol. This paper provides a technical introduction to the MOASA measurement platform, flight strategies and instrumentation. The MOASA air quality dataset includes 63 flight sorties (totaling over 150 hours of sampling), the data from which are openly available for use. Example case studies using data from these sorties are presented, which include an analysis of the spatial scales of measured pollutant variability, initial work to evaluate performance of the AQUM regional air quality model, and an introduction to the vertical structure of pollutants observed during repeated flight patterns over Greater London, including during the COVID-19 impacted period.

Angela Mynard et al.

Status: open (extended)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse

Angela Mynard et al.

Angela Mynard et al.

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Short summary
Air quality models are key in understanding complex air pollution processes and assist in developing strategies to mitigate the impacts of air pollution. The ability of regional air quality models to skilfully represent pollutant distributions aloft is important to enabling their skilful prediction at the surface. To assist in model development and evaluation, a long-term, quality assured, dataset of the 3-dimensional distribution of key pollutants has been collected over the UK (2019–2022).