Journal cover Journal topic
Atmospheric Chemistry and Physics An interactive open-access journal of the European Geosciences Union
Journal topic

Journal metrics

Journal metrics

  • IF value: 5.414 IF 5.414
  • IF 5-year value: 5.958 IF 5-year
  • CiteScore value: 9.7 CiteScore
  • SNIP value: 1.517 SNIP 1.517
  • IPP value: 5.61 IPP 5.61
  • SJR value: 2.601 SJR 2.601
  • Scimago H <br class='hide-on-tablet hide-on-mobile'>index value: 191 Scimago H
    index 191
  • h5-index value: 89 h5-index 89
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: research article 25 May 2020

Submitted as: research article | 25 May 2020

Review status
This preprint is currently under review for the journal ACP.

Meteorology-normalized impact of COVID-19 lockdown upon NO2 pollution in Spain

Hervé Petetin1, Dene Bowdalo1, Albert Soret1, Marc Guevara1, Oriol Jorba1, Kim Serradell1, and Carlos Pérez García-Pando1,2 Hervé Petetin et al.
  • 1Barcelona Supercomputing Center, Barcelona, Spain
  • 2ICREA, Passeig Lluís Companys 23, 08010 Barcelona, Spain

Abstract. The spread of the new coronavirus (COVID-19) forced the Spanish Government to implement extensive lockdown measures to reduce the number of hospital admissions, starting on March 14th 2020. Over the following days and weeks, strong reductions of nitrogen dioxide (NO2) pollution were reported in many regions of Spain. A substantial part of these reductions is obviously due to decreased local and regional anthropogenic emissions. Yet, the confounding effect of meteorological variability hinders a reliable quantification of the lockdown impact upon the observed pollution levels. Our study uses machine learning (ML) models fed by meteorological data along with other time features to estimate the business-as-usual NO2 mixing ratios that would have been observed in the absence of the lockdown. We then quantify the so-called meteorology-normalized NO2 reductions induced by the lockdown measures by comparing the business-as-usual with the actually observed NO2 mixing ratios. We applied this analysis for a selection of urban background and traffic stations covering the more than 50 Spanish provinces and islands.

The ML predictive models were found to perform remarkably well in most locations. During the period of study, going from the enforcement of the state of alarm in Spain on March 14th to April 23rd, we found the lockdown measures to be responsible for a 50 % reduction of NO2 levels on average over all provinces and islands. The lockdown in Spain has gone through several phases with different levels of severity in the mobility restrictions. As expected the meteorology-normalized change of NO2 was found to be stronger during the phases II (the most stringent one) and III than during phase I. In the largest agglomerations where both urban background and traffic stations were available, a stronger meteorology-normalized NO2 change is highlighted at traffic stations compared to urban background ones. Our results are consistent with foreseen (although still uncertain) changes in anthropogenic emissions induced by the lockdown. We also show the importance of taking into account meteorological variability for accurately assessing the impact of the lockdown on NO2 levels, in particular at fine spatial and temporal scales.

Meteorology-normalized estimates such as the ones presented here are crucial to reliably quantify the health implications of the lockdown due to reduced air pollution.

Hervé Petetin et al.

Interactive discussion

Status: open (until 20 Jul 2020)
Status: open (until 20 Jul 2020)
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
[Subscribe to comment alert] Printer-friendly Version - Printer-friendly version Supplement - Supplement

Hervé Petetin et al.

Hervé Petetin et al.


Total article views: 998 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
668 323 7 998 4 8
  • HTML: 668
  • PDF: 323
  • XML: 7
  • Total: 998
  • BibTeX: 4
  • EndNote: 8
Views and downloads (calculated since 25 May 2020)
Cumulative views and downloads (calculated since 25 May 2020)

Viewed (geographical distribution)

Total article views: 911 (including HTML, PDF, and XML) Thereof 911 with geography defined and 0 with unknown origin.
Country # Views %
  • 1



No saved metrics found.


No discussed metrics found.
Latest update: 05 Jul 2020
Publications Copernicus
Short summary
To control the spread of the COVID-19 coronavirus, the Spanish Government recently implemented a strict lockdown of the population, which has strongly reduced the levels of nitrogen dioxide (NO2), one of the most critical air pollutant in Spain. This study quantifies the contribution of the lockdown on these reduced NO2 levels in Spain, taking into account the confounding effect of meteorology with artificial intelligence techniques.
To control the spread of the COVID-19 coronavirus, the Spanish Government recently implemented a...