How mobility restrictions policy and atmospheric conditions impacted air quality in the State of São Paulo during the COVID-19 outbreak

Abstract

Mobility restrictions are among actions to prevent the spread of the COVID-19 pandemic and have been pointed as reasons for improving air quality, especially in large cities. However, it is crucial to assess the impact of atmospheric conditions on air quality and air pollutant dispersion in the face of the potential variability of all sources. In this study, the impact of mobility restrictions on the air quality was analyzed for the most populous Brazilian State, São Paulo, severely impacted by COVID-19. Ground-based air quality data (PM₁₀, PM_2.5, CO, SO₂, NO_x, NO₂, NO, and O₃) were used from 50 automatic air quality monitoring stations to evaluate the changes in concentrations before (January 01 - March 25) and during the partial quarantine (March 16 - June 30). Rainfall, fires, and daily cell phone mobility data were also used as supplementary information to the analyses. The Mann-Whitney U test was used to assess the heterogeneity of the air quality data during and before mobility restrictions. In general, the results demonstrated no substantial improvements in air quality for most of the pollutants when comparing before and during restrictions periods. Besides, when the analyzed period of 2020 is compared with the year 2019, there is no significant air quality improvement in the São Paulo State. However, special attention should be given to the Metropolitan Area of São Paulo (MASP), due to the vast population residing in this area and exposed to air pollution. The region reached an average decrease of 29% in CO, 28% in NO_x, 40% in NO, 19% in SO₂, 15% in PM_2.5, and 8% in PM₁₀ concentrations during the mobility restrictions period compared to the same period in 2019. The only pollutant that showed an increase in concentration was ozone, with a 20% increase compared to 2019 during the mobility restrictions period. Before the mobility restrictions period, the region reached an average decrease of 30% in CO, 39% in NO_x, 63% in NO, 12% in SO₂, 23% in PM_2.5, 18% in PM₁₀, and 16% in O₃ concentrations when compared to the same period in 2019. On the other hand, Cubatão, a highly industrialized area, showed statistically significant increases above 20% for most monitored pollutants in both periods of 2020 compared to 2019. This study reinforces that the main driving force of pollutant concentration variability is the dynamics of the atmosphere at its various time scales. An abnormal rainy season, with above average rainfall before the restrictions and below average after it, generated a scenario in which the probable significant reductions in emissions did not substantially affect the concentration of pollutants.

Keywords: Air pollutants; Air quality; Coronavirus disease; Mobility restriction.

Graphical abstract

Fig. 1

Population density for Brazilian states, emphasizing the São Paulo State (SP).

Fig. 2

Location of air quality monitoring stations used in this study, São Paulo State. The contours shown are the Hydrographic Units for Water Resources Management – HUWRM. The colors indicated in the numbers refer to the respective economic vocation of each HUWRM. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)

Fig. 3

PM₁₀ concentration (μg·m⁻³) for HUWRMs in the State of São Paulo. The light gray area represents the interval between the minimum and maximum. The dark gray line represents the average for the historical series; blue and red lines represent the average for the years 2019 and 2020, respectively. The vertical dashed black line indicates the 76th day of the year 2020 when the first restrictions were started. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)

Fig. 4

Same as in Fig. 3, but for PM_2.5 (μg·m⁻³).

Fig. 5

Same as in Fig. 3, but for CO (ppm).

Fig. 6

Same as in Fig. 3, but for SO₂ (μg·m⁻³).

Fig. 7

Same as in Fig. 3, but for NO_X (ppb).

Fig. 8

Same as in Fig. 3, but for NO₂ (μg·m⁻³).

Fig. 9

Same as in Fig. 3, but for NO (μg·m⁻³).

Fig. 10

Same as in Fig. 3, but for O₃ (μg·m⁻³).

Fig. 11

Evolution in the displacement of cell phone users during the first half of 2020. The vertical dashed line indicates the 76th day of the year 2020 when the first restrictions were started.

Fig. 12

Monthly number of fire outbreaks for 2019 (blue bars), 2020 (red bars), and historical average (2003–2018) (gray bars) for the State of São Paulo. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)