Monitoring air pollutants over time is essential for identifying and addressing trends, which may help improve air quality management and safeguard public health. This study investigates the spatio-temporal variability of air quality in the Metropolitan Area of Curitiba (MAC), Brazil, focusing on six pollutants (SO2, NO2, NOx, O3, CO, and PM10) measured at eight monitoring stations from 2003 to 2017. We conducted statistical analyses, including diurnal cycles, seasonal variability, spatio-temporal correlations, conditional bivariate probability functions, Theil-Sen trend analysis, and comparison with national quality standards (NAQS) and World Health Organization (WHO) guidelines. The analyses revealed large variations in pollutant concentrations across the study area. For instance, stations strongly impacted by industrial emissions presented the highest mean annual SO2 (20-28 μg/m3) and PM10 (32-34 μg/m3) concentrations, while those mostly impacted by traffic showed elevated NO2 (31-39 μg/m3), NOx (63-86 μg/m3) and CO (0.6-0.8 mg/m3) concentrations. The two residential stations recorded the highest O3 concentrations (annual mean of 30-32 μg/m3). Seasonal and diurnal patterns varied by pollutant, with winter experiencing higher concentrations and O3 peaking in spring. SO2 concentrations presented no clear seasonal or diurnal cycle patterns, and showed the highest spatial variability. Significant decreasing annual trends were observed for SO2 (-5.9%), NO2 (-2.6%), NOx (-2.6%), CO (-5.4%), and PM10 (-3.7%), which suggests the success of emission reduction programs implemented in the road transportation and industrial sectors. However, O3 concentrations increased at most stations (+3.3%/yr), likely due to reduced NOx emissions, increased emissions of volatile organic compounds from on-road transport biofuels, and regional O3 transport. Although exceedances of NAQS decreased over time, concentrations of most pollutants remained above WHO guidelines, except for CO. These results highlight the importance of targeted emission control strategies for both industrial and vehicular sources to improve local air quality and inform future policy decisions.
Keywords: Air quality; Emission control policies; Monitoring networks; Spatio-temporal variability; Trend analysis.
© 2024 The Authors.