Analysis of Particulate Matter Fraction in an Urban Area, Brazil

RAFAELA SQUIZZATO, Thiago Nogueira, Caroline Fernanda Hei Wikuats, Maria de Fatima Andrade, Edmilson Dias de Freitas, University of São Paulo

     Abstract Number: 381
     Working Group: Urban Aerosols

Abstract
Utilizing sustainable fuel alternatives is crucial for reducing atmospheric emissions, especially in major cities where vehicular traffic is the primary source of pollution. Even cities that have good urban planning, like Curitiba in the state of Paraná, air pollution can still be a challenge. The present study focuses on analyzing diurnal, seasonal, and weekly patterns of PM2.5 and PM10 in Curitiba’s central area. The station, currently managed by the Water and Land Institute, is situated in Ouvidor Pardinho square, which has moderate traffic, mainly from cars, with the surrounding area characterized by low buildings and some trees. Hourly data from 2023 was analyzed using the Openair package provided by the R software. The analyzes revealed that the concentrations of PM2.5 (mean: 9.7 ± 8.6 µg m-3) and PM10 (mean: 20.5 ± 17 µg m-3) exceeded the new guideline values set by the World Health Organization (WHO), mainly in winter. During the winter months (June, July, and August), the highest concentrations of PM2.5 and PM10 were observed with South winds. In autumn (March, April and May), the highest concentrations occurred from North/Northwest and East directions, for both fractions. In terms of diurnal behavior, particulate matter concentrations peaked above 10 µg m-3 (PM2.5) and 20 µg m-3 (PM10) in the early morning (6 a.m) and late afternoon (6 p.m), directly related to the circulation of vehicles in the area. Additionally, on weekends, a smoothing out of concentration peaks during rush hour can be observed. Despite having a significant local impact, particulate matter concentrations can be influenced by sources from further away. However, to better understand this behavior, a more comprehensive study involving chemical composition analysis on filters is needed to assist in identifying sources.