Long-term trends and probability distribution functions of air pollutant concentrations in the megacity of São Paulo

Abstract

Air quality conditions in many urban areas have improved in the last decades as a consequence of air pollution control policies and regulations. Mitigation strategies have been successful in reducing the concentration of primary pollutants like inhalable particulate matter (PM₁₀), but the control of secondary pollutants like tropospheric ozone (O₃) is still challenging in megacities like the Metropolitan Area of São Paulo (MASP) in Brazil. To support the development of effective mitigation strategies, it is crucial to characterize the statistical behavior of air pollutant concentrations and its long-term evolution. Probability Density Functions (PDF) can be useful to model site-specific air quality conditions, providing estimates for the frequency of extreme pollution events and exceedance of air quality standards. The current study aims to characterize which PDF model better fits and characterizes the variability of PM₁₀ and O₃ concentrations in the MASP. For that, daily maximum moving average concentrations were analyzed between 2000 and 2023, characterizing the long-term trends and the frequency of exceedance of air quality standards. PM₁₀ concentrations followed a lognormal PDF, with an expected value of 31 ± 15 µg.m^-3. O₃ followed a Gamma PDF, with an expected value of 68 ± 25 µg.m^-3. A consistent long-term decrease was observed for PM₁₀ (-1.04 ± 0.09 µg.m^-3.yr^-1), while O₃ showed an increasing trend of 0.51 ± 0.04 µg.m^-3.yr^-1 in the summer. In recent years (2021-2023), the probability of exceedance of the World Health Organization guideline was 17.4 and 11.0%, respectively, for PM₁₀ and O₃. In 2020, a statistically significant increase in O3 expected values was observed, possibly associated with changes in the emission patterns of precursors due to the mobility restrictions imposed by the COVID-19 pandemic.