12 research outputs found
The greatest air quality experiment ever: Policy suggestions from the COVID-19 lockdown in twelve European cities
COVID-19 (Coronavirus disease 2019) hit Europe in January 2020. By March, Europe was the active centre of the pandemic. As a result, widespread "lockdown" measures were enforced across the various European countries, even if to a different extent. Such actions caused a dramatic reduction, especially in road traffic. This event can be considered the most significant experiment ever conducted in Europe to assess the impact of a massive switch-off of atmospheric pollutant sources. In this study, we focus on in situ concentration data of the main atmospheric pollutants measured in twelve European cities, characterized by different climatology, emission sources, and strengths. We propose a methodology for the fair comparison of the impact of lockdown measures considering the non-stationarity of meteorological conditions and emissions, which are progressively declining due to the adoption of stricter air quality measures. The analysis of these unmatched circumstances allowed us to estimate the impact of a nearly zero-emission urban transport scenario on air quality in 12 European cities. The clearest result, common to all the cities, is that a dramatic traffic reduction effectively reduces NO2 concentrations. In contrast, each city's PM and ozone concentrations can respond differently to the same type of emission reduction measure. From the policy point of view, these findings suggest that measures targeting urban traffic alone may not be the only effective option for improving air quality in cities
ERA5-Land reanalysis.
Meteo variables used in this study and link to the ERA5-Land Reanalysis for the period January 1—June 30 (2016–2020). (DOCX)</p
Percentage concentration differences of pollutants under different conditions.
Percentage changes of PM10 (blue), PM2.5 (red), NO2 (green), and O3 (yellow) of daily mean concentrations. Darker to lighter: dispersive pre-lockdown, dispersive lockdown, dispersive post-lockdown, non-dispersive pre-lockdown, non-dispersive lockdown, non-dispersive post-lockdown. (PDF)</p
Oxford Stringency Index.
Evolution of the Oxford Stringency Index in selected European countries.</p
Concentration data.
Links to PM10, PM2.5, NO2 and O3 concentration data repository for the period January 1—June 30 (2016–2020). (DOCX)</p
Meteorological classes.
Frequencies of occurrence (%) of meteorological classes in 2016–2019 and 2020, during the lockdown and no-lockdown periods. (PDF)</p
Concentration data availability.
Green cells represent concentration data of PM10, PM 2.5, NO2 and O3 available for the individual cities; red cells represent a lack of data. (DOCX)</p