Impact of the use of biofuels and biomass on the formation of ultrafine particles in southeastern Brazil

Abstract

The Southeast region of Brazil is the most developed and populous (about 89.5 million inhabitants) with industrialized areas and metropolitan regions in its four states (São Paulo, Minas Gerais, Rio de Janeiro and Espírito Santo), but with problems of air pollution. In Brazil, a large percentage of deaths (71.6%) for the year 2019 due to air pollution is associated with fine particulate matter. The biggest concern is with the high risk of exposing the population to ultrafine particles. These can reach the alveoli and travel to other essential organs of the body, with both acute and chronic effects. Consequently, it is important to know the formation of ultrafine particles, whether they are emitted directly or formed in the atmosphere (secondary formation from the emission of gaseous compounds). In this way, this doctoral project proposal aims to study the formation of ultrafine particles and evaluate it in the scenario of fuel change in the road transport sector. The Brazilian government's RenovaBio program, in order to fulfill the commitments assumed in the Paris Agreement, considers increasing the share of biofuels to 18% in the energy matrix by 2030. As a result, the use of an air quality model will be the main tool to assess the impact of the current and future scenario in urban areas in southeastern Brazil.This doctoral project proposal considers the use of models to study the formation of ultrafine particles. The meteorological part will be evaluated with the Weather Research and Forecasting (WRF) model, which will provide the fields of meteorological variables to the Community Multiscale Air Quality Modeling System (CMAQ) chemical model. These models make it possible to evaluate meteorological and chemical processes isolated. Regarding the emissions' data, anthropogenic and natural sources will be considered for the simulation of the transport of pollutants and chemical reactions of gases and particles. Experimental data and measurements of meteorological and air quality parameters will support the work to evaluate the performance of the models.