The knowledge of exposure to the airborne particle emitted from three-dimensional (3D) printing activities is becoming a crucial issue due to the relevant spreading of such devices in recent years. To this end, a low-cost desktop 3D printer based on fused deposition modeling (FDM) principle was used. Particle number, alveolar-deposited surface area, and mass concentrations were measured continuously during printing processes to evaluate particle emission rates (ERs) and factors. Particle number distribution measurements were also performed to characterize the size of the emitted particles. Ten different materials and different extrusion temperatures were considered in the survey. Results showed that all the investigated materials emit particles in the ultrafine range (with a mode in the 10-30-nm range), whereas no emission of super-micron particles was detected for all the materials under investigation. The emission was affected strongly by the extrusion temperature. In fact, the ERs increase as the extrusion temperature increases. Emission rates up to 1×10 particles min were calculated. Such high ERs were estimated to cause large alveolar surface area dose in workers when 3D activities run. In fact, a 40-min-long 3D printing was found to cause doses up to 200 mm .

The COVID-19 occurrence is causing a global request for effective measures aimed at mitigating the infection spread. Facemasks have been identified as an essential device for people to protect themselves as well as the others from aerosol containing virus. Facemasks provide a critical barrier, reducing the number of infectious viruses or bacteria in exhaled breath. The present review describes the most relevant literature studies on materials and processing technologies used for facemask development and testing. Antibacterial and antiviral treatments are considered. Testing methods for measuring the actual performance are explained in detail. Strategies related to end use are analyzed in terms of reuse, the sanitization process, and recycling. This work derives from a synergic, multidisciplinary, and interdepartmental collaboration in the workgroup of Tuscia University, founded in response to the COVID-19 pandemic, aimed at providing scientific support and information on facemask materials.

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Emission of particles from laser printers in office environments is claimed to have impact on human health due to likelihood of exposure to high particle concentrations in such indoor environments. In the present paper, particle emission characteristics of 110 laser printers from different manufacturers were analyzed, and estimations of their emission rates were made on the basis of measurements of total concentrations of particles emitted by the printers placed in a chamber, as well as particle size distributions. The emission rates in terms of number, surface area and mass were found to be within the ranges from 3.39×10partmin to 1.61×10partmin, 1.06×10mmmin to 1.46×10mmmin and 1.32×10μgmin to 1.23×10μgmin, respectively, while the median mode value of the emitted particles was found equal to 34nm. In addition, the effect of laser printing emissions in terms of employees' exposure in offices was evaluated on the basis of the emission rates, by calculating the daily surface area doses (as sum of alveolar and tracheobronchial deposition fraction) received assuming a typical printing scenario. In such typical printing conditions, a relatively low total surface area dose (2.7mm) was estimated for office employees with respect to other indoor microenvironments including both workplaces and homes. Nonetheless, for severe exposure conditions, characterized by operating parameters falling beyond the typical values (i.e. smaller office, lower ventilation, printer located on the desk, closer to the person, higher printing frequency etc.), significantly higher doses are expected.

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The increased traffic emissions and reduced ventilation of urban street canyons lead to the formation of high particle concentrations as a function of the related flow field and geometry. In this context, the use of advanced modelling tools, able to evaluate particle concentration under different traffic and meteorological conditions, may be helpful.In this work, a numerical scheme based on the non-commercial fully explicit AC-CBS algorithm, and the one-equation Spalart-Allmaras turbulence model, was developed to perform numerical simulations of fluid flow and ultrafine particle dispersion in different street canyon configurations and under different wind speed and traffic conditions. The proposed non-commercial numerical tool was validated through a comparison with data drawn from the scientific literature.The results obtained from ultrafine particle concentration simulations show that as the building height increases the dispersion of particles in the canyon becomes weaker, due to the restricted interaction between the flow field in the street canyon and the undisturbed flow. Higher values of approaching wind speed facilitate the dispersion of the particles. The traffic effect has been evaluated by imposing different values of particles emission, depending on the vehicles type, with the lowest concentration values obtained for the Euro 6 vehicles, and the highest for High Duty Vehicles. A parametric analysis was also performed concerning the exposure to particles of pedestrians in different positions at the road level as a function of street canyon geometry, traffic mode, and wind speed. The worst exposure (1.25 × 10 6 part./cm 3 ) was found at the leeward side for an aspect ratio H/W = 1, wind speed of 5 m/s when High Duty Vehicles traffic was considered.

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Concentrations of ultrafine particles (UFP) are generally elevated in the near-roadway environment due to traffic-related pollution. Exposure to UFP has been linked to adverse health effects for communities living near major roadways. Strategies to mitigate near-roadway air pollution include vehicle emission regulations, as well as installation of physical barriers such as walls, tree stands, and shrubs. Numerical simulation tools can be very useful to investigate the effectiveness of these barriers in mitigating air pollution. In the present work, a Reynolds-Averaged Navier-Stokes (RANS) based computational fluid dynamics (CFD) solver is used to predict filtration of UFP by vegetation. The RANS equations for turbulent flow are combined with a dry deposition velocity model and three different wake turbulence models. Reasonably good predictions of pressure drop across the vegetation and particle penetration efficiency are obtained when compared with available wind tunnel experiments for high leaf area density (LAD) in the range 69-263 m 2 =m 3 . It is found that the model predictions are sensitive to the choice of wake turbulence model and certain model parameters. The model predictions also suggest that thin roadside vegetation with local LAD 5 m 2 =m 3 is only partially effective in filtering UFP, especially when the vegetation thickness is less than 10 m along the direction of the wind. EDITOR Nicole RiemerCONTACT Satbir Singh