Analysis of the Effect of the Truck Strike and COVID-19 on the concentration of NO_x and O_3 in the Metropolitan Region of the Vale do Paraiba, São Paulo, Brazil

Ludmilla Manera Conti ； Dirceu Luís Herdies ； Débora Souza Alvim ； Sergio Machado Corrêa

《Aerosol and Air Quality Research》 22卷8期 (2022/08) Pp. 1-14+ap1-6-003

https://doi.org/10.4209/aaqr.210364

摘要

The daily diurnal data pattern of nitrogen oxides (NO, NO_2) and ozone (O_3), temperature, relative humidity, pressure, wind direction and speed and solar radiation were studied from 2017 to 2020 within a period of 21 days in two towns in Paraiba Valley: São José dos Campos (SJC) and Guaratinguetá (GRT). In 2018, there was a truckers' strike in Brazil and in 2020 a partial lockdown was imposed in response to the coronavirus pandemic; in this study, Machine Learning techniques and a multivariate statistical analysis were conducted to compare these different periods. During both 2018 and 2020, there was a reduction in the NO and NO_2 concentrations, (particularly NO), which is a primary pollutant during peak hours of vehicular traffic; this was notably the case in 2018 owing to the truckers' strike. Through an application of the Tukey test, a comparison was made between the NO, NO_2 and O_3 data which showed that there was a similarity in each element of the dataset on a decreasing scale, however they continue to be statistically significant. Regarding the Principal Component Analysis (PCA), this procedure identified the first major component for both towns in the entire study period and explained around 42% of the data and the proper interconnections between the data, with a strong positive influence of O_3 concentrations, temperature (T), wind speed (WS) and solar radiation (SR). In addition, when analyzing data by means of the Boruta algorithm, there was a considerable difference in the variables that influence O_3 concentrations, with GRT showing NO_2 and relative humidity, while SJC, NO_2 and global solar radiation were the most important variables for feature selection.

關鍵字

Air Pollution ； COVID-19 pandemic ； Strike ； Machine Learning ； PCA