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 PM_2.5 (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), PM_2.5 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.

The lowest region of the troposphere is a turbulent layer known as the atmospheric boundary layer (ABL) and characterized by high daily variability due to the influence of surface forcings. This is the reason why detecting systems with high spatial and temporal resolution, such as lidar, have been widely applied for researching this region. In this paper, we present a comparative analysis on the use of lidar-backscattered signals at three wavelengths (355, 532 and 1064 nm) to study the ABL by investigating the high-order moments, which give us information about the ABL height (derived by the variance method), aerosol layer movement (skewness) and mixing conditions (kurtosis) at several heights. Previous studies have shown that the 1064 nm wavelength, due to the predominance of particle signature in the total backscattered atmospheric signal and practically null presence of molecular signal (which can represent noise in high-order moments), provides an appropriate description of the turbulence field, and thus in this study it was considered a reference. We analyze two case studies that show us that the backscattered signal at 355 nm, even after applying some corrections, has a limited applicability for turbulence studies using the proposed methodology due to the strong contribution of the molecular signature to the total backscatter signal. This increases the noise associated with the high-order profiles and, consequently, generates misinformation. On the other hand, the information on the turbulence field derived from the backscattered signal at 532 nm is similar to that obtained at 1064 nm due to the appropriate attenuation of the noise, generated by molecular component of backscattered signal by the application of the corrections proposed.

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, PM_2.5, 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 (PM_2.5 and PM₁₀) exhibited minimal variation from 2018 to 2021; thus, their measured concentration remained consistent with the prediction model.

The use of radiopharmaceuticals labelled with fluorine-18 in non-invasive imaging, particularly in Positron Emission Tomography (PET), increased significantly during the last decade. However, traditional nucleophilic fluorination synthesis methods in most cases require azeotropic drying steps, leading to loss of activity and increased synthesis time. Microfluidic devices offer improvements with shorter reaction times, higher elution efficiency, and reduced reagent quantities. We developed a novel micro-cartridge for [18F]fluoride trapping and elution, etched in borosilicate optical glass (BK7) using ultrashort laser pulse machining. The micro-cartridge has a bead volume of 17 µL and a maximum capacity of 8.5 mg for anion exchange resin. The micro-cartridge, without the need for QMA preconditioning, exhibited an overall trapping efficiency and recovery efficiency (RE) of (94.09 ± 0.12)% using an activity exceeding 123 GBq of [18F]fluoride. This RE was obtained using 100 µL of a standard solution of anhydrous acetonitrile with Kryptofix 2.2.2, containing only 5 µL of water and 5.4 µmol of K2CO3 for [18F]fluoride elution. This solution was employed directly in the radiosynthesis of [18F]fluoromisonidazole ([18F]FMISO), resulting in a 100% radiochemical conversion (RCC) to THP-protected [18F]FMISO within 10 min at 110 °C. The developed micro-cartridge provides a novel tool for integrating microfluidic chips into conventional cassettes, facilitating more efficient radiopharmaceutical preparation.

We present the first micro-cartridge developed in glass with ultrashort laser pulses machining, applied to radionuclide concentration to synthesize radiopharmaceuticals. The femtosecond laser is an alternative tool for developing these microdevices in different materials.

Femtosecond laser micromachining was adopted to make a glass mixer with complex geometry. This special design promotes more efficient mixing in microreactor with gas-liquid flux at low flow rates, compared to conventional serpentine mixers.