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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. [ABSTRACT FROM AUTHOR]

This paper investigates the performance of seven methods of retrieving the planetary boundary layer height (PBLH) from lidar measurements carried out in the Metropolitan Region of São Paulo (MRSP) during two MCITY - BRAZIL field campaigns of 2013. The performance is objectively assessed considering as reference the PBLH retrieved from rawinsonde carried out every 3 h during these campaigns. The role of clouds and aerosol load in the performance of the seven methods is analysed considering three case study scenarios representative of typical atmospheric conditions in the MRSP : (a) winter clean atmosphere, (b) summer low clouds and aerosol multilayers, (c) summer sea-breeze intrusion. Corroborating the case study results, the objective analysis indicated that most of the lidar methods retrieved PBLH closer to the top of the entrainment zone than the mixed layer, contradicting their definition. During daytime, the Wavelet Covariance Transform Method performs better than all the other six methods. The Inflexion Point Method performed better to estimate the Residual Layer height during night-time. In average, the diurnal evolution of the PBLH and its local rate of change based on lidar and rawinsonde measurements are in agreement. • Most analysed lidar methods estimate the Entrainment Zone height. • Sea-breeze can reduce the aerosol concentration in the Residual Layer. • The Wavelet Covariance Transform has the best result among the analysed methods. • Lidar methods require an adaptation to the local climate conditions. [ABSTRACT FROM AUTHOR]

• Higher variations occurred in pollutants more dependent on the vehicle emissions. • In autumn, the values observed of PM10 and PM2.5 are similar to predict ones. • The reduction in pollutant concentration did not avoid high pollutions episodes. • Activities resumption collaborates with an increase in pollutant concentration. [ABSTRACT FROM AUTHOR]

The Planetary Boundary Layer (PBL) is an important part of the atmosphere that is relevant in different atmospheric fields like pollutant dispersion, and weather forecasting. In this study, we analyze four and five-year datasets of measurements gathered with a ceilometer and a microwave radiometer to study the PBL structure respectively, in the mid-latitude urban area of Granada (Spain). The methodologies applied for the PBL Height (PBLH) detection (gradient method for ceilometer and the combination of parcel method and temperature gradient method for microwave radiometer) provided a description in agreement with the literature about the PBL structure under simple scenarios. Then, the PBLH behavior is characterized by a statistical study of the convective and stable situations, so that the PBLH was obtained from microwave radiometer measurements. The analysis of the PBLH statistical study shows some agreement with other PBLH studies such as daily pattern and yearly cycle, and the discrepancies were explained in terms of distinct latitudes, topography and climate conditions. Finally, it was performed a joint long-term analysis of the residual layer (RL) provided by ceilometer and the stable and convective layer heights determined by microwave radiometer, offering a complete picture of the PBL evolution by synergetic combination of remote sensing techniques. The PBL behavior has been used for explaining the daily cycle of Black Carbon (BC) concentration, used as tracer of the pollutants emissions associated to traffic. • PBLH detection from the combination of ceilometer (PBLH Ceilometer) and MWR (PBLH MWR) measurements. • PBLH long-term analyses. • Statistical analysis of Black Carbon concentration and Ventilation Coefficient. • RL long-term analyses. [ABSTRACT FROM AUTHOR]