Air quality forecasting system for Southeastern Brazil

TLDR

Southeastern Brazil, the country’s most populous and industrialized region, faces environmental challenges as ozone and fine particulate concentrations routinely exceed national standards, making air‑quality modeling—primarily using BRAMS‑SPM and WRF‑Chem—essential for estimating pollutant levels across its major metropolitan areas. The study aimed to examine how improved vehicle emission factors, climate change, and pollutant concentrations affect air quality and public health in southeastern Brazil. The authors integrated mobile‑source emission factors—derived from in‑tunnel measurements and dynamometer protocols—into a spatial distribution based on street and traffic data, and coupled this module with photochemical models to create a transferable framework for regions lacking detailed emission maps. The resulting pollutant forecasts can guide public‑policy decisions on health impacts, fuel use, and emissions‑regulation programs.

Abstract

Southeastern Brazil, the most populous and developed region of the country, faces various environmental problems associated with the growth of its population in urban areas. It is the most industrialized area in the country, comprising the metropolitan areas of São Paulo, Rio de Janeiro, Belo Horizonte, and other major cities. Air quality is a major concern, because the reported concentrations of certain regulated pollutants, typically ozone and fine particulate, have exceeded national standards. Due to the difficulty in taking measurements over many different areas, air quality modeling is a useful tool to estimate air pollutant concentrations. For southeastern Brazil, air quality modeling has been performed mostly with the Brazilian Regional Atmospheric Modeling System with Simplified Photochemical Module and the Weather Research and Forecast with Chemistry models. One of the main objectives was to study the evolution of air quality associated with improved vehicle emission factors in urban areas, the impact of climate change on air quality, and the relationship between pollutant concentrations and health. Knowledge of mobile source emission factors has been continuously expanded by in-tunnel measurements and dynamometer protocols, which provide accurate data as inputs to photochemical air quality models. The spatial distribution of the mobile source emissions was constructed based on open access data related to the streets and traffic distribution. The mobile emission module was combined to the chemistry modeling and this implementation can be an example to be applied to other places that do not have a spatial distribution of this kind of source. Forecasts of pollutant concentrations can inform public policies, including those addressing the effects of pollutants on health of the general population, and studies of the impacts of using different fuels and implementation of emissions regulations programs.