Lockdown for CoViD-2019 in Milan: What are the effects on air quality?

Abstract

Based on the rapid spread of the CoViD-2019, a lockdown was declared in the whole Northern Italy by the Government. The application of increasingly rigorous containment measures allowed to reduce the impact of the CoViD-2019 pandemic on the Italian National Health System but at the same time these restriction measures gave also the opportunity to assess the effect of anthropogenic activities on air pollutants in an unprecedented way. This paper aims to study the impact of the partial and total lockdown (PL and TL, respectively) on air quality in the Metropolitan City of Milan. As results, the severe limitation of people movements following the PL and the subsequent TL determined a significant reduction of pollutants concentration mainly due to vehicular traffic (PM₁₀, PM_2.5, BC, benzene, CO, and NO_x). The lockdown led to an appreciable drop in SO₂ only in the city of Milan while it remained unchanged in the adjacent areas. Despite the significant decrease in NO₂ in the TL, the O₃ exhibited a significant increase, probably, due to the minor NO concentration. In Milan and SaA the increase was more accentuated, probably, due to the higher average concentrations of benzene in Milan than the adjacent areas that might have promoted the formation of O₃ in a more significant way.

Keywords: Air monitoring; CoViD; Coronavirus; Ozone; PM(10); SARS-CoV 2.

Graphical abstract

Fig. 1

Map of the Metropolitan City of Milan and its location in the Lombardy region. The sub-areas A and B used in the study are highlighted. Map realized with QGIS (2020).

Fig. 2

Scheme of activities allowed and prohibited from the 1st of January 2020 to the 10th of April 2020 in MeCiMi. a: Christmas holidays; b: some activities (e.g. museums and cinemas) were closed; c: workplace closures, no public transports (in the nearby area of Codogno); d: stricter measures in Codogno (movements outside the area were not allowed).

Fig. 3

Daily average wind speed, rainfall, relative humidity, temperature, and solar irradiance in daylight hours from the 1st of January 2020 to the 10th of April 2020.

Fig. 4

Daily average concentration of PM₁₀, PM_2.5, and BC in Milan, SaA, and SaB during CTRL, PL, and TL periods. The percentages indicate the variations between the periods. Boxplots represent the distance between the first and third quartiles while whiskers are set as the most extreme (lower and upper) data point not exceeding 1.5 times the quartile range from the median. Black curves represent the normal distributions of the data.

Fig. 5

Daily average concentration of benzene (C₆H₆), CO, and SO₂ in Milan, SaA, and SaB during CTRL, PL, and TL periods. The percentages indicate the variations between the periods. Boxplots represent the distance between the first and third quartiles while whiskers are set as the most extreme (lower and upper) data point not exceeding 1.5 times the quartile range from the median. Black curves represent the normal distributions of the data. n.a.: not available.

Fig. 6

Daily average concentration of O₃, NO₂, and NO_x in Milan, SaA, and SaB during CTRL, PL, and TL periods. The percentages indicate the variations between the periods. Boxplots represent the distance between the first and third quartiles while whiskers are set as the most extreme (lower and upper) data point not exceeding 1.5 times the quartile range from the median. Black curves represent the normal distributions of the data.

Fig. 7

Daily average concentration of O₃ as function of daily hours of sunlight and average solar irradiance during daylight hours in CTRL, PL, and TL periods.