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Accuracy evaluation of reanalysis data on air pollutant concentrations in the metropolitan area of Sao Paulo

Grant number: 22/16238-5
Support Opportunities:Scholarships in Brazil - Scientific Initiation
Effective date (Start): February 01, 2023
Effective date (End): January 31, 2024
Field of knowledge:Physical Sciences and Mathematics - Geosciences - Meteorology
Principal Investigator:Luciana Varanda Rizzo
Grantee:Marina Spina Paiva
Host Institution: Instituto de Física (IF). Universidade de São Paulo (USP). São Paulo , SP, Brazil

Abstract

Air pollution is one of the main environmental problems in urban areas, with impacts to human health and quality of life. In order to quantify impacts and design mitigation actions, air quality monitoring is essential. However, the distribution of air quality monitoring stations is unequal and insufficient in Brazil. Reanalysis data products can be an alternative to characterize air quality in regions where the in-situ monitoring is lacking. This undergrad research Project aims to evaluate the accuracy of reanalysis data in representing aerosol and trace gases concentrations in the Metropolitan Area of São Paulo (MASP), between 2014 and 2019. Four of the air pollutants monitored in governmental air quality stations will be considered: PM10, PM2.5, NO2 and O3. Data from two reanalysis projects will be evaluated: CAMS (Copernicus Atmospheric Monitoring Service), which provides estimates of surface air pollutant concentrations with a 0.75ox0.75o spatial resolution, and MERRA-2 (Modern-Era Retrospective analysis for Research and Applications), with resolution of 0.5ºx0.625º. Reanalysis and in situ data will be collocated in space and time, in order to evaluate correlations, bias and seasonal patterns. In this way, the performance of air quality reanalysis products will be assessed, as well as the strengths and weaknesses of each product. Such assessment is unprecedent for the MASP and may be expanded for other Brazilian regions in the near future, aiming to contribute to air quality characterization in regions where in-situ monitoring is insufficient.

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