Event Details

DSNE seminar with Stuart Grange, Empa - Swiss Federal Laboratories for Materials Science and Technology / York

The restrictions placed on society in early 2020 across Europe to slow the transmission of COVID-19 were unprecedented and had a range of environmental consequences. Air pollutant and CO2 emissions decreased during the period of reduced population mobility, but the quantification of the effect on local air quality is complicated by the unusual weather situation which affected most of Europe in early 2020. To robustly control for the meteorological conditions experienced, observationally-derived machine learning models were trained to explain concentrations for ~250 air quality monitoring sites across European urban areas. Post-training, these models were used in predictive-mode to calculate a counterfactual (or a business as usual scenario) which the observed concentrations could be readily compared with. Additionally, to link the intervention dates with pollutant concentration change, change point models were used to objectively identify and quantify these events. The results indicated that nitrogen dioxide (NO2, primarily a traffic pollutant) decreased by about a third, while ozone (O3, a secondary pollutant) increased by about 25 % due to its chemical relationship with NO2 when considering urban Europe as a whole. These results have implications for European air quality management and will be discussed.

Join Microsoft Teams Meeting

Learn more about Teams | Meeting options

By using this service you agree to LU T&Cs - Use the Help Button for tips

Help | Legal