Air quality modeling in the metropolitan area of São Paulo, Brazil: A review.

Numerous studies have used air quality models to estimate pollutant concentrations in the Metropolitan Area of São Paulo (MASP) by using different inputs and assumptions. Our objectives are to summarize these studies, compare their performance, configurations, and inputs, and recommend areas of further research. We examined 29 air quality modeling studies that focused on ozone (O3) and fine particulate matter (PM2.5) performed over the MASP, published from 2001 to 2023. The California Institute of Technology airshed model (CIT) was the most used offline model, while the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) was the most used online model. Because the main source of air pollution in the MASP is the vehicular fleet, it is commonly used as the only anthropogenic input emissions. Simulation periods were typically the end of winter and during spring, seasons with higher O3 and PM2.5 concentrations. Model performance for hourly ozone is good with half of the studies with Pearson correlation above 0.6 and root mean square error (RMSE) ranging from 7.7 to 27.1 ppb. Fewer studies modeled PM2.5 and their performance is not as good as ozone estimates. Lack of information on emission sources, pollutant measurements, and urban meteorology parameters is the main limitation to perform air quality modeling. Nevertheless, researchers have used measurement campaign data to update emission factors, estimate temporal emission profiles, and estimate volatile organic compounds (VOCs) and aerosol speciation. They also tested different emission spatial disaggregation approaches and transitioned to global meteorological reanalysis with a higher spatial resolution. Areas of research to explore are further evaluation of models' physics and chemical configurations, the impact of climate change on air quality, the use of satellite data, data assimilation techniques, and using model results in health impact studies. This work provides an overview of advancements in air quality modeling within the MASP and offers practical approaches for modeling air quality in other South American cities with limited data, particularly those heavily impacted by vehicle emissions.

Major Regional-Scale Production of O3 and Secondary Organic Aerosol in Remote Amazon Regions from the Dynamics and Photochemistry of Urban and Forest Emissions.

The Amazon rainforest suffers increasing pressure from anthropogenic activities. A key aspect not fully understood is how anthropogenic atmospheric emissions within the basin interact with biogenic emissions and impact the forest's atmosphere and biosphere. We combine a high-resolution atmospheric chemical transport model with an improved emissions inventory and in-situ measurements to investigate a surprisingly high concentration of ozone (O3) and secondary organic aerosol (SOA) 150-200 km downwind of Manaus city in an otherwise pristine forested region. We show that atmospheric dynamics and photochemistry determine a gross production of secondary pollutants seen in the simulation. After sunrise, the erosion of the nocturnal boundary layer mixes natural forest emissions, rich in biogenic volatile organic compounds, with a lofted pollution layer transported overnight, rich in nitrogen oxides and formaldehyde. As a result, O3 and SOA concentrations greater than ∼47 ppbv and 1.8 µg m-3, respectively, were found, with maximum concentrations occurring at 2 pm LT, 150-200 km downwind of Manaus city. These high concentrations affect a large primary forested area of about 11,250 km2. These oxidative areas are under a NOx-limited regime so that changes in NOx emissions from Manaus have a significant impact on O3 and SOA production.