Changes in air pollution during COVID-19 lockdown in Spain: A multi-city study

Abstract

The COVID-19 pandemic has escalated into one of the largest crises of the 21st Century. The new SARS-CoV-2 coronavirus, responsible for COVID-19, has spread rapidly all around the world. The Spanish Government was forced to declare a nationwide lockdown in view of the rapidly spreading virus and high mortality rate in the nation. This study investigated the impact of short-term lockdown during the period from March 15th to April 12th 2020 on the atmospheric levels of CO, SO₂, PM₁₀, O₃, and NO₂ over 11 representative Spanish cities. The possible influence of several meteorological factors (temperature, precipitation, wind, sunlight hours, minimum and maximum pressure) on the pollutants' levels were also considered. The results obtained show that the 4-week lockdown had significant impact on reducing the atmospheric levels of NO₂ in all cities except for the small city of Santander as well as CO, SO₂, and PM₁₀ in some cities, but resulted in increase of O₃ level.

Keywords: Air quality; COVID-19; Lockdown; Meteorology; Pollution.

Graphical abstract

Fig. 1

Locations of the 11 cities considered for the analysis. The coordinates used were those of the cities’ pollution stations. The borders of the different Spanish provinces are plotted in gray.

Fig. 2

Percentage variations in pollutant levels in each of the cities under study between March 17th-March 31st 2019 and March 15th-March 29th 2020 (a), and between April 1st-April 14th 2019 and March 30th-April 12th 2020 (b).

Fig. 3

City-specific marginal effects estimated by Eq. (1) for NO₂ levels in each of the three study periods. Differences between marginal effects are statistically significant when the associated confidence intervals do not overlap.

Fig. 4

City-specific marginal effects estimated by Eq. (1) for O₃ levels in each of the three periods. Differences between marginal effects are statistically significant when the associated confidence intervals do not overlap.

Fig. 5

City-specific marginal effects estimated by Eq. (1) for PM₁₀ levels in the three study periods. Differences between marginal effects are statistically significant when the associated confidence intervals do not overlap.

Fig. 6

City-specific marginal effects estimated by Eq. (1) for SO₂ levels in each of the three periods. Differences between marginal effects are statistically significant when the associated confidence intervals do not overlap.

Fig. 7

City-specific marginal effects estimated by Eq. (1) for CO levels in each of the three periods. Differences between marginal effects are statistically significant when the associated confidence intervals do not overlap.