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  • Artigo IPEN-doc 29836
    Analyzing the influence of vehicular traffic on the concentration of pollutants in the city of São Paulo
    2023 - MOREIRA, GREGORI de A.; CACHEFFO, ALEXANDRE; ANDRADE, IZABEL da S.; LOPES, FABIO JULIANO da S.; GOMES, ANTONIO A.; LANDULFO, EDUARDO
    This study employs surface and remote sensing data jointly with deep learning techniques to examine the influence of vehicular traffic in the seasonal patterns of CO, NO2 , PM2.5, and PM10 concentrations in the São Paulo municipality, as the period of physical distancing (March 2020 to December 2021), due to SARS-CoV-2 pandemic and the resumption of activities, made it possible to observe significant variations in the flow of vehicles in the city of São Paulo. Firstly, an analysis of the planetary boundary layer height and ventilation coefficient was performed to identify the seasons’ patterns of pollution dispersion. Then, the variations (from 2018 to 2021) of the seasonal average values of air temperature, relative humidity, precipitation, and thermal inversion occurrence/position were compared to identify possible variations in the patterns of such variables that would justify (or deny) the occurrence of more favorable conditions for pollutants dispersion. However, no significant variations were found. Finally, the seasonal average concentrations of the previously mentioned pollutants were compared from 2018 to 2021, and the daily concentrations observed during the pandemic period were compared with a model based on an artificial neural network. Regarding the concentration of pollutants, the primarily sourced from vehicular traffic (CO and NO2 ) exhibited substantial variations, demonstrating an inverse relationship with the rate of social distancing. In addition, the measured concentrations deviated from the predictive model during periods of significant social isolation. Conversely, pollutants that were not primarily linked to vehicular sources (PM2.5 and PM10) exhibited minimal variation from 2018 to 2021; thus, their measured concentration remained consistent with the prediction model.
  • Artigo IPEN-doc 27830
    COVID-19 outbreak and air quality
    2021 - MOREIRA, GREGORI de A.; ANDRADE, IZABEL da S.; CACHEFFO, ALEXANDRE; YOSHIDA, ALEXANDRE C.; GOMES, ANTONIO A.; SILVA, JONATAN J. da; LOPES, FABIO J. da S.; LANDULFO, EDUARDO
    This work compares variations in the concentrations and air quality indexes of the pollutants PM10, PM2.5, CO, and NO2, during the COVID-19 outbreak in São Paulo Municipality. Such comparisons considered the period of physical distancing (autumn) and the three first months of economic activities’ resumption (winter). The concentrations and indexes observed in 2020 were compared with their correspondent values measured in the three preceding years. Also, from a supervised machine learning algorithm, the correspondent 2020 expected values were predicted and used in these comparisons. In order to analyze the influence of meteorological conditions, the seasons studied were characterized using remote sensing and surface data. The pollutants predominantly emitted by the vehicle fleet (CO and NO2) had reductions in their concentrations, with values always below the predictions and good air quality indexes. However, the pollutants whose concentration is less dependent on automotive emissions (PM10 and PM2.5) had high proximity to the predictions during the autumn and lower values during some periods in winter. This reduction was not enough to avoid days with a moderate air quality index. The approximation of the average concentrations of PM10, PM2.5, and CO to the prediction, from the second-half August 2020, indicates the influence of activities’ resumption in air quality.
  • Artigo IPEN-doc 27755
    Influence of a biomass-burning event in PM2.5 concentration and air quality
    2021 - MOREIRA, GREGORI de A.; ANDRADE, IZABEL da S.; CACHEFFO, ALEXANDRE; LOPES, FABIO J. da S.; YOSHIDA, ALEXANDRE C.; GOMES, ANTONIO A.; SILVA, JONATAN J. da; LANDULFO, EDUARDO
    Severe biomass burning (BB) events have become increasingly common in South America in the last few years, mainly due to the high number of wildfires observed recently. Such incidents can negatively influence the air quality index associated with PM2.5 (particulate matter, which is harmful to human health). A study performed in the Metropolitan Area of São Paulo (MASP) took place on selected days of July 2019, evaluated the influence of a BB event on air quality. Use of combined remote sensing, a surface monitoring system and data modeling and enabled detection of the BB plume arrival (light detection and ranging (lidar) ratio of (50 ± 34) sr at 532 nm, and (72 ± 45) sr at 355 nm) and how it affected the Ångström exponent (>1.3), atmospheric optical depth (>0.7), PM2.5 concentrations (>25 µg.m−3), and air quality classification. The utilization of high-order statistical moments, obtained from elastic lidar, provided a new way to observe the entrainment process, allowing understanding of how a decoupled aerosol layer influences the local urban area. This new novel approach enables a lidar system to obtain the same results as a more complex set of instruments and verify how BB events contribute from air masses aloft towards near ground ones.