Lessons from the COVID-19 air pollution decrease in Spain: Now what?
We offer an overview of the COVID-19 -driven air quality changes across 11 metropolises in Spain with the focus on lessons learned on how continuing abating pollution. Traffic flow decreased by up to 80% during the lockdown and remained relatively low during the full relaxation (June and July). After the lockdown a significant shift from public transport to private vehicles (+21% in Barcelona) persisted due to the pervasive fear that using public transport might increase the risk of SARS-CoV-2 infection, which need to be reverted as soon as possible. NO2 levels fell below 50% of the WHO annual air quality guidelines (WHOAQGs), but those of PM2.5 were reduced less than expected due to the lower contributions from traffic, increased contributions from agricultural and domestic biomass burning, or meteorological conditions favoring high secondary aerosol formation yields. Even during the lockdown, the annual PM2.5 WHOAQG was exceeded in cities within the NE and E regions with high NH3 emissions from farming and agriculture. Decreases in PM10 levels were greater than in PM2.5 due to reduced emissions from road dust, vehicle wear, and construction/demolition. Averaged O3 daily maximum 8-h (8hDM) experienced a generalized decrease in the rural receptor sites in the relaxation (June–July) with −20% reduced mobility. For urban areas O3 8hDM responses were heterogeneous, with increases or decreases depending on the period and location. Thus, after canceling out the effect of meteorology, 5 out of 11 cities experienced O3 decreases during the lockdown, while the remaining 6 either did not experience relevant reductions or increased. During the relaxation period and coinciding with the growing O3 season (June–July), most cities experienced decreases. However, the O3 WHOAQG was still exceeded during the lockdown and full relaxation periods in several cities. For secondary pollutants, such as O3 and PM2.5, further chemical and dispersion modeling along with source apportionment techniques to identify major precursor reduction targets are required to evaluate their abatement potential. ; The present work was supported by the Spanish Ministerio para la Transición Ecológica y Reto Demográfico (17CAES010), the "Agencia Estatal de Investigación" from the Spanish Ministry of Science and Innovation (IDAEA-CSIC is a Centre of Excellence Severo Ochoa CEX2018-000794-S), FEDER funds under the project CAIAC (PID2019-108990RB-I00), and by the Generalitat de Catalunya (AGAUR 2017 SGR41). We would like to thank the Spanish Meteorological Office (AEMET) for providing meteorological data as well as NASA for providing OMI-NO2 data. BSC co-authors acknowledge the support of the Copernicus Atmosphere Monitoring Service (CAMS), which is implemented by the European Centre for Medium-Range Weather Forecasts (ECMWF) on behalf of the European Commission, the Ministerio de Ciencia, Innovación y Universidades (MICINN) (RTI2018-099894-B-I00, CGL2017-88911-R), the Agencia Estatal de Investigación (PID2019-108086RA-I00/AEI/0.13039/501100011033), the AXA Research Fund, and PRACE and RES for awarding access to Marenostrum4 based in Spain at the Barcelona Supercomputing Center. H. Petetin also acknowledges the European Union's Horizon 2020 - Research and Innovation Framework Programme under the H2020 Marie Skłodowska-Curie Actions grant agreement H2020-MSCACOFUND-2016-754433. ; Peer reviewed
