The main goal of this study was to improve the knowledge of ultrafine particle number distributions in large urban areas and also to call the attention to the importance of these particles on assessing health risks. Measurements of aerosol size distributions were performed during 2 weeks, with distinct pollutant concentrations (polluted and clean periods), on the rooftop of a building located in downtown of the megacity of São Paulo, Brazil. CO, NO2, PM10, SO2, and O3 concentrations and meteorological variables were also used. Aerosol size distribution measurements showed that geometric mean diameters of the size spectra in the polluted period are on average considerably larger than those in the clean one. Besides the fact that total number of ultrafine particles did not show significant differences, during the polluted period, geometric mean diameter was larger than during the clean one. The results of a mathematical model of particle deposition on human respiratory tract indicated a more significant effect of smaller particles fraction of the spectra, which predominate under clean atmospheric conditions. The results also indicated that urban environmental conditions usually considered good for air quality, under the criteria of low mass concentration, do not properly serve as air quality standard to very small particles. In the size range of ultrafine particles, this traditional clean atmospheric condition can offer a strong risk to pulmonary hazards, since the cleansing of the atmosphere creates good conditions to increase the concentration of nucleation mode particles.

In the present study, the physical parameterizations of the Weather Research and Forecasting (WRF) model are verified for making accurate inferences about the dynamics of the Thermal Internal Boundary Layer (TIBL) generated by sea breeze in an urban center with an island in a bay along a coastal region with rugged topography. The simulations were performed using parameterizations from Yonsei University (YSU), Mellor-Yamada-Janjic (MYJ) and Asymmetric Convective Model version 2 (ACM2) for the atmospheric boundary layer (ABL) and Noah and Rapid Update Cycle (RUC) for the Land Surface Model (LSM). The data inferred by the WRF model were compared with those obtained by a Surface Meteorological Station (SMS) and by measurements generated using Light Detection and Ranging (LIDAR), Sonic Detection and Ranging (SODAR) and radiosonde. The simulations showed that although the object of this research was a region with high geographical complexity, the YSU parameterization set (non-local closure) for the ABL and the Noah parameterization for the LSM presented satisfactory results in determining ABL height generated by the sea breeze on the day in question.

With the unexpected arrival of the COVID-19 pandemic, countries worldwide were forced to take measures to curb its transmission. Mobility restrictions policies were the primary preventive measures applied around the globe. In addition to reducing the disease spread, they resulted in air quality changes in urbanized areas. In this sense, this study aimed to investigate how the mobility restrictions imposed by public policies impacted the air quality in Brazil during the COVID-19 2020 outbreak. Therefore, air quality (CO, NO2, PM10, PM2.5, and O3) and urban mobility datasets available in five populous Brazilian states (São Paulo, Rio de Janeiro, Espírito Santo, Paraná, and Rio Grande do Sul) were analyzed. Variations in air pollutant concentrations were verified by comparing the period during mobility restrictions (2020) and the average concentrations found before the restrictions (2015-2019). In addition, spatial assessment of changes was evaluated using tropospheric NO2 column densities from the TROPOMI. Although there was no national regulation regarding mobility restrictions, the results show that the reduction in urban mobility was similar for all the analyzed states. Following the mobility behavior, reducing air pollutant concentrations were significant for the first 30 days of restrictions. During this period, the most substantial reductions were observed for CO in the State of Rio Grande do Sul (-53%), NO2 in Rio de Janeiro (-34%), and PM10 in Espírito Santo (-23%). The exception was observed for O3, which followed the world trend of increasing concentrations (e.g., 40% increase in Paraná). Spatially, it was possible to evidence that large urban centers (with a large vehicle fleet) were the ones that showed the most significant reduction in NO2. However, when analyzing longer periods (over 90 days), there is a trend towards an increase in the concentrations of primary pollutants and a consequent reduction in O3, reflecting the significant increase in mobility rates.

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