A two decades study on ozone variability and trend over the main urban areas of the São Paulo state, Brazil

• Published in: Environmental science and pollution research international 2019-11, Vol.26 (31), p.31699-31716
• Main Authors: Schuch, Daniel, de Freitas, Edmilson Dias, Espinosa, Sergio Ibarra, Martins, Leila Droprinchinski, Carvalho, Vanessa Silveira Barreto, Ramin, Bruna Ferreira, Silva, Jayne Sousa, Martins, Jorge Alberto, de Fatima Andrade, Maria
• Format: Article
• Language: English
• Subjects: Air Pollution - analysis; Air quality; Aquatic Pollution; Atmospheric Protection/Air Quality Control/Air Pollution; Brazil; Diesel fuels; Earth and Environmental Science; Ecotoxicology; Emission measurements; Environment; Environmental Chemistry; Environmental Health; Environmental Monitoring - methods; Environmental science; Gasohol; Mathematical models; Normal distribution; Outdoor air quality; Ozone; Ozone - analysis; Quantiles; Radiation effects; Regression analysis; Regression models; Research Article; Residential areas; Residential location; Statistical analysis; Statistical models; Time series; Trends; Urban areas; Waste Water Technology; Water Management; Water Pollution Control
• ISSN: 0944-1344; 1614-7499
• DOI: 10.1007/s11356-019-06200-z

In this paper, we analyze the variability of the ozone concentration over São Paulo Macrometropolis, as well the factors, which determined the tendency observed in the last two decades. Time series of hourly ozone concentrations measured at 16 automated stations from an air quality network from 1996 to 2017 were analyzed. The temporal variability of ozone concentrations exhibits well-defined daily and seasonal patterns. Ozone presents a significant positive correlation between the number of cases (thresholds of 100–160 μg m −3 ) and the fuel sales of gasohol and diesel. The ozone concentrations do not exhibit significant long-term trends, but some sites present positive trends that occurs in sites in the proximity of busy roads and negative trends that occurs in sites located in residential areas or next to trees. The effect of atmospheric process of transport and ozone formation was analyzed using a quantile regression model (QRM). This statistical model can deal with the nonlinearities that appear in the relationship of ozone and other variables and is applicable to time series with non-normal distribution. The resulting model explains 0.76% of the ozone concentration variability (with global coefficient of determination R 1 = 0.76) providing a better representation than an ordinary least square regression model (with coefficient of determination R 2 = 0.52); the effect of radiation and temperature are the most critical in determining the highest ozone quantiles.