Impact of meteorological conditions on source apportionment of Fine Particulate Matter (PM2.5) in Sao Paulo city

• Grant number: 24/17857-6
• Support Opportunities: Scholarships in Brazil - Master
• Start date: July 01, 2025
• End date: March 31, 2026
• Field of knowledge: Physical Sciences and Mathematics - Geosciences - Meteorology
• Principal Investigator: Maria de Fátima Andrade
• Grantee: Vitoria Rodilha Leão
• Host Institution: Instituto de Astronomia, Geofísica e Ciências Atmosféricas (IAG). Universidade de São Paulo (USP). São Paulo , SP, Brazil
• Associated research grant: 16/18438-0 - São Paulo Metropolitan Area, jointly tracking climate change and air quality - METROCLIMA-MASP, AP.PFPMCG.TEM

Abstract

Atmospheric aerosols affect air quality and human and ecosystem well-being. In Metropolitan Area of Sao Paulo (MASP), Brazil, vehicular emissions and soil dust resuspension are important sources of Fine Particulate Matter (PM2,5), as well as remote sources, such as wildfires, in addition to other indiscriminate sources, such as biogenic emissions and solid fuel combustion. Considering the frequent changes in technology, fuel compositions and atmospheric conditions, an updated study of PM is necessary, especially in regions such as MASP, where source development is complex. This project will use PM and its detailed composition in terms of carbonaceous components (organic and elementar), metals, ions, and sugar, employing distinct analytical procedures to characterize the chemical composition of PM2,5, such as Inductively Coupled Plasma Mass Spectrometry (ICP-MS), high-performance anion-exchange chromatography/pulsed amperometric detection (HPAEC-PAD), Thermal Optical Transmittance (TOT) analysis, and other techniques. Concentrations were monitored on Faculdade de Saúde Pública (FSP; School of Public Health) from University of Sao Paulo, a region next to avenues and natural parks, from May/2022 to January/2023. Source apportionment will be done after applying the Kolmogorov-Zurbenko filter to the data. Source identification will be then performed using receptor models methodology: Enrichment Factor, Principal Component Analysis, Positive Matrix Factorization model and DeltaSA tool. Source apportionment from meteorologically adjusted concentration data will be performed for the first time in Sao Paulo. (AU)